From 56b04fe38dbfab0c00aa13cd14ef9a883bd5e025 Mon Sep 17 00:00:00 2001 From: Mario G <63501500+gronert-m@users.noreply.github.com> Date: Wed, 9 Oct 2024 17:48:47 -0400 Subject: [PATCH 1/2] Prep ARM ILCS First step, writing the CSD --- .../ARM/ILCS/1. Introduction to ARM ILCS.md | 90 ++++++++++++++++++ .../ARM/ILCS/utilities/AILCS.pdf | Bin 0 -> 19995 bytes .../ARM/ILCS/utilities/a7_absent_2008.png | Bin 0 -> 18880 bytes .../ARM/ILCS/utilities/a7_absent_2013.png | Bin 0 -> 27317 bytes 4 files changed, 90 insertions(+) create mode 100644 Support/B - Country Survey Details/ARM/ILCS/1. Introduction to ARM ILCS.md create mode 100644 Support/B - Country Survey Details/ARM/ILCS/utilities/AILCS.pdf create mode 100644 Support/B - Country Survey Details/ARM/ILCS/utilities/a7_absent_2008.png create mode 100644 Support/B - Country Survey Details/ARM/ILCS/utilities/a7_absent_2013.png diff --git a/Support/B - Country Survey Details/ARM/ILCS/1. Introduction to ARM ILCS.md b/Support/B - Country Survey Details/ARM/ILCS/1. Introduction to ARM ILCS.md new file mode 100644 index 000000000..fb9c9b366 --- /dev/null +++ b/Support/B - Country Survey Details/ARM/ILCS/1. Introduction to ARM ILCS.md @@ -0,0 +1,90 @@ +# Introduction to [Full Name of Survey] ([Survey Acronym)] + +- [What is the ARM survey?](#what-is-the-arm-ilcs) +- [What does the ARM survey cover?](#what-does-the-arm-ilcs-cover) +- [Where can the data be found?](#where-can-the-data-be-found) +- [What is the sampling procedure?](#what-is-the-sampling-procedure) +- [What is the significance level?](#what-is-the-geographic-significance-level) +- [Other noteworthy aspects](#other-noteworthy-aspects) + +## What is the ARM ILCS? + +The Integrated Living Conditions Survey (ILCS) was first conducted in Armenia in 1996 (in a one-month period), followed by the one in 1998/99; thereafter, it has been conducted every year +since 2001. The GLD version only covers the years 2008 to 2013, since Armenia also has a labour force survey since 2014. + +## What does the ARM ILCS cover? + +The Armenian ILCS covers all standard modules of a living conditions survey (household assets, health, labor, savings). Moreover, it contains a diary of daily expenditures (food and non-food). The harmonization covers the following years with the following sample sizes: + +| Year | # of Households | # of Individuals | +| :------- | :-------- | :-------- | +| 2008 | 7,872 | 32,756 | +| 2009 | 7,872 | 32,362 | +| 2010 | 7,872 | 32,353 | +| 2011 | 7,872 | 31,024 | +| 2012 | 5,184 | 20,134 | +| 2013 | 5,184 | 19,831 | + +## Where can the data be found? + +The data are publicly available on the website of the Statistical Committee of the Republic of Armenia (ARMSTAT). The data are stored in series for [the households](https://armstat.am/en/?nid=205), [the household members](https://armstat.am/en/?nid=206), and [the consumption diaries](https://armstat.am/en/?nid=207). The site additionally links to the World Bank Microdata Library + +## What is the sampling procedure? + +The GLD team has only found documentation on the sampling procedure for 2008 and 2009. However, there is no reason to assume this does not hold for years 2010 to 2013. The following passage explains the stratified, two stage sampling approach. It is taken from the [2009 AILCS document available here](utilities/AILCS.pdf): + +> The sampling frame for 2009 was designed according to the database of addresses of all households in the country developed on basis of the 2001 Population Census results, with the +technical assistance of the World Bank. + +> The sample consisted of two parts – master sample and supplementary sample. + +> 1. For the purpose of drawing the master sample, the sample frame was divided into 48 strata including 12 communities of Yerevan City (currently, the administrative districts). +Communities in all regions were grouped into three categories: large towns with 15.000 and more inhabitants, small towns with less than 15.000 inhabitants, and villages. Large towns +formed 16 groups (strata), while small towns and villages formed 10 strata each. + +> According to this division, a random two-tier sample was drawn, stratified by regions and by Yerevan. All regions and Yerevan, as well as all urban and rural communities were included +in the sample in accordance to the shares of their resident households within the total number of households in the country. In the first round, enumeration districts – that is primary sample +units to be surveyed during the year – were selected. The ILCS 2009 sample included 46 enumeration districts in urban and 18 enumeration districts in rural communities per month. + +> 2. The supplementary sample was drawn from the list of the villages included in MCA-Armenia road rehabilitation projects. Then, enumeration districts of the villages already included in +the master sample were excluded from this list. Eighteen enumeration districts were selected per month from among the remaining ones. Thus, the sample of rural communities doubled. + +> 3. After merging the master and supplementary samples, the households to be surveyed were selected in the second round. A total of 656 households were surveyed per month, of which +368 and 288 households from urban and rural communities, respectively. + + +## What is the geographic significance level? + +Survey data provide for a minimum representativeness by regions (variable `subnatid1`). + +## Other noteworthy aspects + +### Age restriction of the questionnaire labor market module + +While most surveys limit the market module to all people aged above lower age threshold (commonly 15 years of age), the Armenian ILCS is limited also by an upper age threshold. Only people aged 15 to 75 respond to the labor market module and thus have labor variables. Given the low labor forceparticipation of people aged 76 and older, it can be assumed that the labor force participation of the population 15+ is lower than the one that can be calculated. + +### Handling of absentees + +The Armenian ILCS surveys include a question whether household members are absent (defined as not being in the household for the whole survey month). The below shows screenshots of this question in the 2008 and 2013 questionnaires. + +| Questionnaire 2008 | Questionnaire 2013 | +|------------------------------------------------------------------|-----------------------------------------------------------------| +| ![Education question in ARM LFS](utilities/a7_absent_2008.png) | ![Education question in ARM LFS](utilities/a7_absent_2013.png) | + +There are 1,274 household members aged between 15 and 75 coded as absent for whome there is no labor market information. The number for 2013 is 1,323. Absentees are being skipped in the labor market module despite the questionnaire having no direct skip pattern. + +As a consequence, `lstatus` and all labor variables are missing for this group of people. However, we have information on their personal details (sex, age, marital status) and their education, as well as a weight variable. + +Normally, the population for whom `lstatus` is defined (i.e., `lstatus` is 1, 2, or 3) should be the same as that of household members in working age (here, ages 15 to 75). This is not the case here. Hence, the below calculations are not equal: + +```math +\frac{\text{people aged 15-75 with lstatus 1 or 2}}{\text{people aged 15-75 with lstatus 1, 2, or 3}} \neq \frac{\text{people aged 15-75 with lstatus 1 or 2}}{\text{people aged 15-75}} +``` + +The GLD harmonization has kept the absentees in the data. They can be identified by having missing values for `lstatus` despite being aged 15 to 75. + +The only exception are 228 individuals in 2013 who are coded as absent but answer some labor market questions (though not all the ones they should). All are coded as completing their military service. They are coded as not in the labour force (`lstatus == 3`). This way we match the numbers reported by ARMSTAT. + +### Coding of education variables + +Text \ No newline at end of file diff --git a/Support/B - Country Survey Details/ARM/ILCS/utilities/AILCS.pdf b/Support/B - Country Survey Details/ARM/ILCS/utilities/AILCS.pdf new file mode 100644 index 0000000000000000000000000000000000000000..e499bee0af7185b36b1bafd09537d6ba8f9f92ab GIT binary patch literal 19995 zcmeHvbzGEN^EfEoAt9iwh)4+Au#0pF(yf%lE+yR^0xF%-B@H5|lptUsp&+S%bccwf zC<6YT1@n5}_r3Ri-_P%_clq$y^PDqhX3oq!XJ^hib55zr$nir35R|7Tr#gEn$zU)L z1Y~b&4H6LnD_PlLO`NQ}uow^&tOSCh(P$)C6$C?oWkE9TB>o78 zMnnHt2Zf-8eybCNL;hF?g9!cx2ZKY9zri8lztM#WLIGjnK0kOy05bYx9TJN84Icz2 zs_%VWoJ_22uuha@fY3Dod4u3cu$mLr4G=8?Edl&X5K6LBr({*-D9L_N9wiwZabO!b)4lX#BX(*kg`I%n<19gtc?|hFIF(&INdM2Eh-Mt6}c~2owYX*uhwt{8@huth2qVlNrDp46rYN z(S6=<-2TJ{uH|4@asUBfbXr<45Dc(A9K03+1l#8uC<=n$xK|$-0$_UfW|~+ReK0UL zfVHq5E{0%P50`VAIEDZW=QN=p+?#}h{fQC|=K&>6S5p_9n6#W+vHLvXNXuZI&77

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zOA;KrKP6yJ6U5Z-CE;3iDJRY+B76-T;3WzxBvK~3uPVFAUzLkJ9r%PoW2mTdn~Lx} zPWjWd`0s&R{Bj`ie!JcN=}73~3I6qj5ttp#{ldTQn}Ixzp1hFJ%lS?D3=q-(>py!EQshjm{K!bYIa|2>mK$s1 zQqr>iW+A6-@WV~(gTr?78_bfY<6}BwlJDNda!y80Dv7IV09UB`J$3Lz2$O0E_cp1* z?-t-$q*{W9+MtIMu?PPK!OAKMZ9W6_@`eU&ck@JXpb;>PH0Puj4B>(Rmnx<-{eSrR ka7X@6{#U_+Pw&M-rEow~w Date: Fri, 18 Oct 2024 15:25:31 -0400 Subject: [PATCH 2/2] Add in code, addendums to CSD --- .../ARM_2008_ILCS_V01_M_V01_A_GLD_ALL.do | 1753 +++++++++++++++ .../ARM_2009_ILCS_V01_M_V01_A_GLD_ALL.do | 1798 ++++++++++++++++ .../ARM_2010_ILCS_V01_M_V01_A_GLD_ALL.do | 1767 +++++++++++++++ .../ARM_2011_ILCS_V01_M_V01_A_GLD_ALL.do | 1782 +++++++++++++++ .../ARM_2012_ILCS_V01_M_V01_A_GLD_ALL.do | 1818 ++++++++++++++++ .../ARM_2013_ILCS_V01_M_V01_A_GLD_ALL.do | 1904 +++++++++++++++++ .../ARM/ILCS/1. Introduction to ARM ILCS.md | 26 +- .../ARM/ILCS/utilities/education_vars.png | Bin 0 -> 18161 bytes 8 files changed, 10847 insertions(+), 1 deletion(-) create mode 100644 GLD/ARM/ARM_2008_ILCS/ARM_2008_ILCS_V01_M_V01_A_GLD/Programs/ARM_2008_ILCS_V01_M_V01_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2009_ILCS/ARM_2009_ILCS_V01_M_V01_A_GLD/Programs/ARM_2009_ILCS_V01_M_V01_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2010_ILCS/ARM_2010_ILCS_V01_M_V01_A_GLD/Programs/ARM_2010_ILCS_V01_M_V01_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2011_ILCS/ARM_2011_ILCS_V01_M_V01_A_GLD/Programs/ARM_2011_ILCS_V01_M_V01_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2012_ILCS/ARM_2012_ILCS_V01_M_V01_A_GLD/Programs/ARM_2012_ILCS_V01_M_V01_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2013_ILCS/ARM_2013_ILCS_V01_M_V01_A_GLD/Programs/ARM_2013_ILCS_V01_M_V01_A_GLD_ALL.do create mode 100644 Support/B - Country Survey Details/ARM/ILCS/utilities/education_vars.png diff --git a/GLD/ARM/ARM_2008_ILCS/ARM_2008_ILCS_V01_M_V01_A_GLD/Programs/ARM_2008_ILCS_V01_M_V01_A_GLD_ALL.do b/GLD/ARM/ARM_2008_ILCS/ARM_2008_ILCS_V01_M_V01_A_GLD/Programs/ARM_2008_ILCS_V01_M_V01_A_GLD_ALL.do new file mode 100644 index 000000000..e32232861 --- /dev/null +++ b/GLD/ARM/ARM_2008_ILCS/ARM_2008_ILCS_V01_M_V01_A_GLD/Programs/ARM_2008_ILCS_V01_M_V01_A_GLD_ALL.do @@ -0,0 +1,1753 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +==============================================================================================%%*/ + +/* ----------------------------------------------------------------------- + +<_Program name_> ARM_2008_ILCS_V01_M_V01_A_GLD_ALL.do +<_Application_> Stata 18 <_Application_> +<_Author(s)_> World Bank Jobs Group (gld@worldbank.org) +<_Date created_> 2024-09-11 + +------------------------------------------------------------------------- + +<_Country_> Armenia +<_Survey Title_> Integrated Living Conditions Survey +<_Survey Year_> 2008 +<_Study ID_> https://microdatalib.worldbank.org/index.php/catalog/2615 +<_Data collection from_> [MM/YYYY] +<_Data collection to_> [MM/YYYY] +<_Source of dataset_> [Source of data, e.g. NSO] +<_Sample size (HH)_> [#] +<_Sample size (IND)_> [#] +<_Sampling method_> [Brief description] +<_Geographic coverage_> [To what level is data significant] +<_Currency_> [Currency used for wages] + +----------------------------------------------------------------------- + +<_ICLS Version_> [Version of ICLS for Labor Questions] +<_ISCED Version_> [Version of ICLS for Labor Questions] +<_ISCO Version_> [Version of ICLS for Labor Questions] +<_OCCUP National_> [Version of ICLS for Labor Questions] +<_ISIC Version_> [Version of ICLS for Labor Questions] +<_INDUS National_> [Version of ICLS for Labor Questions] + +----------------------------------------------------------------------- +<_Version Control_> + +* Date: [YYYY-MM-DD] - [Description of changes] +* Date: [YYYY-MM-DD] - [Description of changes] + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +==============================================================================================%%*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m +set varabbrev off + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD-Harmonization/529026_MG/Countries" +local country "ARM" +local year "2008" +local survey "ILCS" +local vermast "V01" +local veralt "V01" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + +* Check whether there is a weight file +local has_wf = fileexists("`path_in_stata/weight.dta'") + +* Start with HH +use "`path_in_stata'/hh.dta" + +* If there is a weight file, merge it in +if `has_wf' { + merge 1:1 recno using "`path_in_stata/weight.dta'", assert(match) nogen +} + +* Add member roster +merge 1:m recno using "`path_in_stata'/mem.dta", assert(match) nogen + +* 2008 has employment in mem.dta + +* Add number labels +numlabel, add force + +/*%%============================================================================================= + 2: Survey & ID +==============================================================================================%%*/ + +{ + +*<_countrycode_> + gen str4 countrycode = "ARM" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname = "ILCS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey = "GLD" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v = "ICLS-13" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version = "" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version = "" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version = "isic_3.1" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year = 2008 + label var year "Year of survey" +* + + +*<_vermast_> + gen vermast = "`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen veralt = "`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization = "GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year= 2008 + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month = date + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> +/* <_hhid_note> + + Values are running number. Would have preferred making it a string with 0001 to 5184, but leave as is since + GMD has it this way. For PID concatenate this with 01-12 but leave as is. + + */ + gen hhid = recno + label var hhid "Household ID" +* + + +*<_pid_> + gen pid = memnum + label var pid "Individual ID" +* + + +*<_weight_> + * Weight already exists + *gen weight = . + label var weight "Survey sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + gen weight_q = . + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + gen psu = . + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu = . + label var ssu "Secondary sampling units" +* + + +*<_strata_> + gen strata = . + label var strata "Strata" +* + + +*<_wave_> + gen wave = . + label var wave "Survey wave" +* + + +*<_panel_> + gen panel = "" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no = . + label var visit_no "Visit number in panel" +* + +} + + +/*%%============================================================================================= + 3: Geography +==============================================================================================%%*/ + +{ + +*<_urban_> + * typev is 0 if YErevan, 1 if urban (other), rural is 2 + gen byte urban = inrange(typev, 0,1) + replace urban = 0 if typev == 2 + label var urban "Location is urban" + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban +* + + +*<_subnatid1_> +/* <_subnatid1_note> + + The variable is string and country-specific categorical. Numeric entries are coded in string format using the following naming convention: "1 – Hatay". That is, the variable itself is to be string, not a labelled numeric vector. + + Example of entries would be "1 - Alaska", "2 - Arkansas", ... + + */ + gen str subnatid1 = "" + replace subnatid1 = "1 - Yerevan" if marz == 1 + replace subnatid1 = "2 - Aragatsotn" if marz == 2 + replace subnatid1 = "3 - Ararat" if marz == 3 + replace subnatid1 = "4 - Armavir" if marz == 4 + replace subnatid1 = "5 - Gegharkunik" if marz == 5 + replace subnatid1 = "6 - Lori" if marz == 6 + replace subnatid1 = "7 - Kotayk" if marz == 7 + replace subnatid1 = "8 - Shirak" if marz == 8 + replace subnatid1 = "9 - Syunik" if marz == 9 + replace subnatid1 = "10 - Vayoc Dzor" if marz == 10 + replace subnatid1 = "11 - Tavush" if marz == 11 +* + + +*<_subnatid2_> + gen str subnatid2 = "" + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen str subnatid3 = "" + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> +/* <_subnatidsurvey_note> + + Variable denoting lowest administrative info to which the survey is still significat. + See entry in GLD Guidelines (https://github.com/worldbank/gld/blob/main/Support/A%20-%20Guides%20and%20Documentation/GLD_1.0_Guidelines.docx) for more details + + */ + gen str subnatidsurvey = "" + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> +/* <_subnatid1_prev_note> + + subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + + */ + gen subnatid1_prev = . + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev = . + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev = . + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code = . + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code = . + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code = . + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + + +/*%%============================================================================================= + 4: Demography +==============================================================================================%%*/ + +{ + +*<_hsize_> + * If keep all + gen hsize = members + /* * If drop absentees + gen helper = 1 + egen hh_abs_no = total(helper), by(recno) + replace hsize = hsize - hh_abs_no + drop helper hh_abs_no + */ + label var hsize "Household size" +* + + +*<_age_> + * Already in there + *gen age = . + label var age "Individual age" +* + + +*<_male_> + gen male = a1_1 + recode male (2 = 0) + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + gen relationharm = a1_2 + recode relationharm (4 = 3) (6 = 4) (7 = 5) (8 = 6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +* + + +*<_relationcs_> + clonevar relationcs = a1_2 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen byte marital = a1_5 + recode marital (3 = 5) (5 = 3) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed", replace + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all" + label values eye_dsablty dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values hear_dsablty dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values walk_dsablty dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values conc_dsord dsablty + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values slfcre_dsablty dsablty + label var slfcre_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values comm_dsablty dsablty + label var comm_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +==============================================================================================%%*/ + + +{ + +* Migration questions are at household level this year - cannot use + +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + label values migrated_binary lblmigrated_binary + label var migrated_binary "Individual has migrated" +* + + +*<_migrated_years_> + gen migrated_years = . + label var migrated_years "Years since latest migration" +* + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + label de lblmigrated_from_urban 0 "Rural" 1 "Urban" + label values migrated_from_urban lblmigrated_from_urban + label var migrated_from_urban "Migrated from area" +* + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + label de lblmigrated_from_cat 1 "From same admin3 area" 2 "From same admin2 area" 3 "From same admin1 area" 4 "From other admin1 area" 5 "From other country" + label values migrated_from_cat lblmigrated_from_cat + label var migrated_from_cat "Category of migration area" +* + + +*<_migrated_from_code_> + gen migrated_from_code = . + *label de lblmigrated_from_code + *label values migrated_from_code lblmigrated_from_code + label var migrated_from_code "Code of migration area as subnatid level of migrated_from_cat" +* + + +*<_migrated_from_country_> + gen migrated_from_country = . + label var migrated_from_country "Code of migration country (ISO 3 Letter Code)" +* + + +*<_migrated_reason_> + gen migrated_reason = . + label de lblmigrated_reason 1 "Family reasons" 2 "Educational reasons" 3 "Employment" 4 "Forced (political reasons, natural disaster, …)" 5 "Other reasons" + label values migrated_reason lblmigrated_reason + label var migrated_reason "Reason for migrating" +* + + +} + + +/*%%============================================================================================= + 6: Education +==============================================================================================%%*/ + + +{ + +*<_ed_mod_age_> + +/* <_ed_mod_age_note> + +Education module is only asked to those XX and older. + + */ + +gen byte ed_mod_age = 6 +label var ed_mod_age "Education module application age" + +* + +*<_school_> + gen byte school = 0 + replace school = 1 if e2_4 == 1 + label var school "Attending school" + la de lblschool 0 "No" 1 "Yes" + label values school lblschool +* + + +*<_literacy_> + gen byte literacy = 1 + replace literacy = 0 if e2_2 == 0 + replace literacy = . if mi(e2_2) + label var literacy "Individual can read & write" + la de lblliteracy 0 "No" 1 "Yes" + label values literacy lblliteracy +* + + +*<_educy_> + * Number of years is a combination of level (e2_2) and years in that course (e2_3) + gen byte educy =. + replace educy = 0 if e2_2 == 0 + replace educy = e2_3 if e2_2 == 1 & inrange(e2_3,0,4) + replace educy = 4 + e2_3 if e2_2 == 2 & inrange(e2_3,0,5) + replace educy = 9 + e2_3 if e2_2 == 3 & inrange(e2_3,0,3) + replace educy = 9 + e2_3 if e2_2 == 4 & inrange(e2_3,0,2) + replace educy = 9 + e2_3 if e2_2 == 5 & inrange(e2_3,0,5) + replace educy = 12 + e2_3 if e2_2 == 6 & inrange(e2_3,0,7) + replace educy = 16 + e2_3 if e2_2 == 7 & inrange(e2_3,0,4) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7 =. + replace educat7 = 1 if e2_2 == 0 + replace educat7 = 2 if e2_2 == 1 & e2_3 < 4 + replace educat7 = 3 if e2_2 == 1 & e2_3 == 4 + replace educat7 = 4 if e2_2 == 2 + replace educat7 = 5 if inrange(e2_2, 3, 4) + replace educat7 = 6 if e2_2 == 5 + replace educat7 = 7 if inrange(e2_2, 6, 7) + label var educat7 "Level of education 1" + la de lbleducat7 1 "No education" 2 "Primary incomplete" 3 "Primary complete" 4 "Secondary incomplete" 5 "Secondary complete" 6 "Higher than secondary but not university" 7 "University incomplete or complete", replace + label values educat7 lbleducat7 +* + + +*<_educat5_> + gen byte educat5 = educat7 + recode educat5 4=3 5=4 6 7=5 + label var educat5 "Level of education 2" + la de lbleducat5 1 "No education" 2 "Primary incomplete" 3 "Primary complete but secondary incomplete" 4 "Secondary complete" 5 "Some tertiary/post-secondary" + label values educat5 lbleducat5 +* + + +*<_educat4_> + gen byte educat4 = educat7 + recode educat4 (2 3 4 = 2) (5=3) (6 7=4) + label var educat4 "Level of education 3" + la de lbleducat4 1 "No education" 2 "Primary" 3 "Secondary" 4 "Post-secondary" + label values educat4 lbleducat4 +* + + +*<_educat_orig_> + clonevar educat_orig = e2_2 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced = . + label var educat_isced "ISCED standardised level of education" +* + + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var "school literacy educy educat7 educat5 educat4 educat_orig educat_isced" + +foreach v of local ed_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < ed_mod_age & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < ed_mod_age & !missing(age) ) + } +} + + +* + + +} + + +/*%%============================================================================================= + 7: Training +==============================================================================================%%*/ + + +{ + +*<_vocational_> + gen vocational = . + label de lblvocational 0 "No" 1 "Yes" + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type = . + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l = . + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u = . + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen str vocational_field_orig = "" + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed = . + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + + +/*%%============================================================================================= + 8: Labour +==============================================================================================%%*/ + + +*<_minlaborage_> + gen byte minlaborage = 15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + gen byte lstatus = . + + * Employed if either has work (d1_1) or will go back (d1_2) + replace lstatus = 1 if d1_1 == 1 | d1_2 == 1 + + * Unemployed if looking for a job (yes to d4_5 two forms) and willing to accept (yes to d4_14) + replace lstatus = 2 if inrange(d4_5, 1, 2) & d4_14 == 1 + + * Remaining people would all go to NLF but since data is 15-75 and there is the absentee issue, define precisely + replace lstatus = 3 if (d4_5 == 3 & d4_14 == 2) | (d4_5 == 3 & d4_14 == 1) | (inrange(d4_5, 1, 2) & d4_14 == 2) + + replace lstatus = . if age < minlaborage + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + gen byte potential_lf = 0 + replace potential_lf = 1 if (d4_5 == 3 & d4_14 == 1) | (inrange(d4_5, 1, 2) & d4_14 == 2) + replace potential_lf = . if age < minlaborage & age != . + replace potential_lf = . if lstatus != 3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment = . + replace underemployment = . if age < minlaborage & age != . + replace underemployment = . if lstatus != 1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=. + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=. + replace unempldur_l = 0 if d4_11 == 1 + replace unempldur_l = 1 if d4_11 == 2 + replace unempldur_l = 4 if d4_11 == 3 + replace unempldur_l = 7 if d4_11 == 4 + replace unempldur_l = 13 if d4_11 == 5 + replace unempldur_l = 25 if d4_11 == 6 + replace unempldur_l = 49 if d4_11 == 7 + replace unempldur_l = . if lstatus != 2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=. + replace unempldur_u = 1 if d4_11 == 1 + replace unempldur_u = 3 if d4_11 == 2 + replace unempldur_u = 6 if d4_11 == 3 + replace unempldur_u = 12 if d4_11 == 4 + replace unempldur_u = 24 if d4_11 == 5 + replace unempldur_u = 48 if d4_11 == 6 + replace unempldur_u = 999 if d4_11 == 7 + replace unempldur_u = . if lstatus != 2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* + +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat = d1_7 + recode empstat (2 = 1) (5 = 2) (6 = 4) (7 = 5) + label var empstat "Employment status during past week primary job 7 day recall" + la de lblempstat 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat lblempstat +* + + +*<_ocusec_> +/* <_ocusec_note> + + While other years have code 2 as "municipality", here it is "community". Translating from Armenian + gives the same. Of the 98 answers, if weighted, 40% work in Public Admin, 23.4% in education, 13.3% + in provision of public services (culture, sport, ...). They are also 98% with contract. + Assume this is public as well + + Code 4 is "mixed - with government particiaption, send to state owned" + + */ + gen byte ocusec = d1_6 + recode ocusec (2 7 = 1) (3 5 6 = 2) (4 = 3) + label var ocusec "Sector of activity primary job 7 day recall" + la de lblocusec 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec lblocusec +* + + +*<_industry_orig_> + gen industry_orig = d1_4 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic = "" + replace industrycat_isic = "A" if d1_4 == 1 + replace industrycat_isic = "B" if d1_4 == 2 + replace industrycat_isic = "C" if d1_4 == 3 + replace industrycat_isic = "D" if d1_4 == 4 + replace industrycat_isic = "E" if d1_4 == 5 + replace industrycat_isic = "F" if d1_4 == 6 + replace industrycat_isic = "G" if d1_4 == 7 + replace industrycat_isic = "H" if d1_4 == 8 + replace industrycat_isic = "I" if d1_4 == 9 + replace industrycat_isic = "J" if d1_4 == 10 + replace industrycat_isic = "K" if d1_4 == 11 + replace industrycat_isic = "L" if d1_4 == 12 + replace industrycat_isic = "M" if d1_4 == 13 + replace industrycat_isic = "N" if d1_4 == 14 | d1_4 == 15 + replace industrycat_isic = "O" if d1_4 == 16 + replace industrycat_isic = "P" if d1_4 == 17 + replace industrycat_isic = "Q" if d1_4 == 18 + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen byte industrycat10 = . + replace industrycat10 = 1 if inrange(d1_4, 1, 2) + replace industrycat10 = 2 if d1_4 == 3 + replace industrycat10 = 3 if d1_4 == 4 + replace industrycat10 = 4 if d1_4 == 5 + replace industrycat10 = 5 if d1_4 == 6 + replace industrycat10 = 6 if inrange(d1_4, 7, 8) + replace industrycat10 = 7 if d1_4 == 9 + replace industrycat10 = 8 if inrange(d1_4, 10, 11) + replace industrycat10 = 9 if d1_4 == 12 + replace industrycat10 = 10 if inrange(d1_4, 13, 18) + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4 = industrycat10 + recode industrycat4 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4 "Broad Economic Activities classification, primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig = . + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco) + *int_classif_universe, var(occup_isco) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_> + gen byte occup = . + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_occup_skill_> + gen occup_skill = . + replace occup_skill = 3 if inrange(occup, 1, 3) + replace occup_skill = 2 if inrange(occup, 4, 8) + replace occup_skill = 1 if occup == 9 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_wage_no_compen_> + egen double wage_no_compen = rowtotal(d1_17 d1_18), missing + replace wage_no_compen = . if lstatus != 1 | empstat == 2 | wage_no_compen == 0 + label var wage_no_compen "Last wage payment primary job 7 day recall" +* + + +*<_unitwage_> + gen byte unitwage = 5 + replace unitwage = . if mi(wage_no_compen) + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours = d1_14 + replace whours = . if whours == 0 | lstatus != 1 + label var whours "Hours of work in last week primary job 7 day recall" +* + + + +*<_wmonths_> + gen wmonths = . + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> +/* <_wage_total_note> + + Use gross wages when available and net wages only when gross wages are not available. + This is done to make it easy to compare earnings in formal and informal sectors. + + */ + gen wage_total = . + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + gen byte contract = 0 + replace contract = 1 if d1_7 == 1 + replace contract = . if lstatus != 1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins = . + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec = . + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union = . + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen firmsize_l = . + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen firmsize_u= . + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + + +{ +*<_empstat_2_> + gen byte empstat_2 = d2_4 + recode empstat_2 (2 = 1) (5 = 2) (6 = 4) (7 = 5) + label var empstat_2 "Employment status during past week secondary job 7 day recall" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2 = d2_3 + recode ocusec_2 (2 7 = 1) (3 5 6 = 2) (4 = 3) + label var ocusec_2 "Sector of activity secondary job 7 day recall" + label values ocusec_2 lblocusec +* + + +*<_industry_orig_2_> + gen industry_orig_2 = d2_2 + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2 = "" + replace industrycat_isic_2 = "A" if d2_2 == 1 + replace industrycat_isic_2 = "B" if d2_2 == 2 + replace industrycat_isic_2 = "C" if d2_2 == 3 + replace industrycat_isic_2 = "D" if d2_2 == 4 + replace industrycat_isic_2 = "E" if d2_2 == 5 + replace industrycat_isic_2 = "F" if d2_2 == 6 + replace industrycat_isic_2 = "G" if d2_2 == 7 + replace industrycat_isic_2 = "H" if d2_2 == 8 + replace industrycat_isic_2 = "I" if d2_2 == 9 + replace industrycat_isic_2 = "J" if d2_2 == 10 + replace industrycat_isic_2 = "K" if d2_2 == 11 + replace industrycat_isic_2 = "L" if d2_2 == 12 + replace industrycat_isic_2 = "M" if d2_2 == 13 + replace industrycat_isic_2 = "N" if d2_2 == 14 | d2_2 == 15 + replace industrycat_isic_2 = "O" if d2_2 == 16 + replace industrycat_isic_2 = "P" if d2_2 == 17 + replace industrycat_isic_2 = "Q" if d2_2 == 18 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen byte industrycat10_2 = . + replace industrycat10_2 = 1 if inrange(d2_2, 1, 2) + replace industrycat10_2 = 2 if d2_2 == 3 + replace industrycat10_2 = 3 if d2_2 == 4 + replace industrycat10_2 = 4 if d2_2 == 5 + replace industrycat10_2 = 5 if d2_2 == 6 + replace industrycat10_2 = 6 if inrange(d2_2, 7, 8) + replace industrycat10_2 = 7 if d2_2 == 9 + replace industrycat10_2 = 8 if inrange(d2_2, 10, 11) + replace industrycat10_2 = 9 if d2_2 == 12 + replace industrycat10_2 = 10 if inrange(d2_2, 13, 18) + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2 = industrycat10_2 + recode industrycat4_2 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2 "Broad Economic Activities classification, secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2 = . + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2 = "" + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_2_> + gen byte occup_2 = . + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_occup_skill_2_> + gen occup_skill_2 = . + replace occup_skill_2 = 3 if inrange(occup_2, 1, 3) + replace occup_skill_2 = 2 if inrange(occup_2, 4, 8) + replace occup_skill_2 = 1 if occup_2 == 9 + la de lblskill2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2 lblskill2 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_wage_no_compen_2_> + egen double wage_no_compen_2 = rowtotal(d2_11 d2_12), missing + replace wage_no_compen_2 = . if mi(empstat_2) | empstat_2 == 2 | wage_no_compen_2 == 0 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2 = 5 + replace unitwage_2 = . if mi(wage_no_compen_2) + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2 = . + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2 = . + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2 = . + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen firmsize_l_2 = . + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen firmsize_u_2 = . + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others = . + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others = . + label var t_wage_nocompen_others "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others = . + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total = . + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total = . + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total = . + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ + +*<_lstatus_year_> + gen byte lstatus_year = . + replace lstatus_year=. if age < minlaborage & age != . + label var lstatus_year "Labor status during last year" + la de lbllstatus_year 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus_year lbllstatus_year +* + +*<_potential_lf_year_> + gen byte potential_lf_year = . + replace potential_lf_year=. if age < minlaborage & age != . + replace potential_lf_year = . if lstatus_year != 3 + label var potential_lf_year "Potential labour force status" + la de lblpotential_lf_year 0 "No" 1 "Yes" + label values potential_lf_year lblpotential_lf_year +* + + +*<_underemployment_year_> + gen byte underemployment_year = . + replace underemployment_year = . if age < minlaborage & age != . + replace underemployment_year = . if lstatus_year == 1 + label var underemployment_year "Underemployment status" + la de lblunderemployment_year 0 "No" 1 "Yes" + label values underemployment_year lblunderemployment_year +* + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ + +*<_empstat_year_> + gen byte empstat_year = . + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + +*<_ocusec_year_> + gen byte ocusec_year = . + label var ocusec_year "Sector of activity primary job 12 month recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + +*<_industry_orig_year_> + gen industry_orig_year = . + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year = . + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(industrycat_isic_year) + *int_classif_universe, var(industrycat_isic_year) universe(ISIC) + count + *list + *assert `r(N)' == 0 + restore + + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + +*<_industrycat10_year_> + gen byte industrycat10_year = . + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "Broad Economic Activities classification, primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year = . + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen occup_isco_year = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco_year) + *int_classif_universe, var(occup_isco_year) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year = . + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_occup_skill_year_> + gen occup_skill_year = . + replace occup_skill_year = 3 if inrange(occup_year, 1, 3) + replace occup_skill_year = 2 if inrange(occup_year, 4, 8) + replace occup_skill_year = 1 if occup_year == 9 + la de lblskillyear 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_year lblskillyear + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_wage_no_compen_year_> --- this var has the same name as other and when quoted in the keep and order codes is repeated. + gen double wage_no_compen_year = . + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year = . + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year = . + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year = . + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year = . + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year = . + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year = . + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year = . + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year = . + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen firmsize_l_year = . + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen firmsize_u_year = . + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year = . + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year = . + label var ocusec_2_year "Sector of activity secondary job 12 month recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year = . + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year = . + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year = . + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "Broad Economic Activities classification, secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year = . + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year = "" + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year = . + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year = . + replace occup_skill_2_year = 3 if inrange(occup_2_year, 1, 3) + replace occup_skill_2_year = 2 if inrange(occup_2_year, 4, 8) + replace occup_skill_2_year = 1 if occup_2_year == 9 + la de lblskilly2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2_year lblskilly2 + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year = . + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year = . + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year = . + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year = . + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year = . + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + +*<_firmsize_l_2_year_> + gen firmsize_l_2_year = . + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen firmsize_u_2_year = . + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year = . + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year = . + label var t_wage_nocompen_others_year "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 12 month recall" +* + +*<_t_wage_others_year_> + gen t_wage_others_year = . + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year = . + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year = . + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year = . + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs = . + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual = . + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc = . + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome = t_wage_total_year + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`out_file'", replace + +* diff --git a/GLD/ARM/ARM_2009_ILCS/ARM_2009_ILCS_V01_M_V01_A_GLD/Programs/ARM_2009_ILCS_V01_M_V01_A_GLD_ALL.do b/GLD/ARM/ARM_2009_ILCS/ARM_2009_ILCS_V01_M_V01_A_GLD/Programs/ARM_2009_ILCS_V01_M_V01_A_GLD_ALL.do new file mode 100644 index 000000000..3c631f184 --- /dev/null +++ b/GLD/ARM/ARM_2009_ILCS/ARM_2009_ILCS_V01_M_V01_A_GLD/Programs/ARM_2009_ILCS_V01_M_V01_A_GLD_ALL.do @@ -0,0 +1,1798 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +==============================================================================================%%*/ + +/* ----------------------------------------------------------------------- + +<_Program name_> ARM_2009_ILCS_V01_M_V01_A_GLD_ALL.do +<_Application_> Stata 18 <_Application_> +<_Author(s)_> World Bank Jobs Group (gld@worldbank.org) +<_Date created_> 2024-09-11 + +------------------------------------------------------------------------- + +<_Country_> Armenia +<_Survey Title_> Integrated Living Conditions Survey +<_Survey Year_> 2009 +<_Study ID_> https://microdatalib.worldbank.org/index.php/catalog/2615 +<_Data collection from_> [MM/YYYY] +<_Data collection to_> [MM/YYYY] +<_Source of dataset_> [Source of data, e.g. NSO] +<_Sample size (HH)_> [#] +<_Sample size (IND)_> [#] +<_Sampling method_> [Brief description] +<_Geographic coverage_> [To what level is data significant] +<_Currency_> [Currency used for wages] + +----------------------------------------------------------------------- + +<_ICLS Version_> [Version of ICLS for Labor Questions] +<_ISCED Version_> [Version of ICLS for Labor Questions] +<_ISCO Version_> [Version of ICLS for Labor Questions] +<_OCCUP National_> [Version of ICLS for Labor Questions] +<_ISIC Version_> [Version of ICLS for Labor Questions] +<_INDUS National_> [Version of ICLS for Labor Questions] + +----------------------------------------------------------------------- +<_Version Control_> + +* Date: [YYYY-MM-DD] - [Description of changes] +* Date: [YYYY-MM-DD] - [Description of changes] + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +==============================================================================================%%*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m +set varabbrev off + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD-Harmonization/529026_MG/Countries" +local country "ARM" +local year "2009" +local survey "ILCS" +local vermast "V01" +local veralt "V01" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + +* Check whether there is a weight file +local has_wf = fileexists("`path_in_stata'/weight.dta") + +* Start with HH +use "`path_in_stata'/hh.dta" + +* If there is a weight file, merge it in +if `has_wf' { + merge 1:1 recno using "`path_in_stata'/weight.dta", assert(match) nogen +} + +* Add member roster +merge 1:m recno using "`path_in_stata'/mem.dta", assert(match) nogen + +* Add employment section +merge 1:1 recno memnum using "`path_in_stata'/d1", assert(match master) nogen + +* Add number labels +numlabel, add force + +/*%%============================================================================================= + 2: Survey & ID +==============================================================================================%%*/ + +{ + +*<_countrycode_> + gen str4 countrycode = "ARM" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname = "ILCS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey = "GLD" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v = "ICLS-13" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version = "" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version = "" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version = "isic_3.1" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year = 2009 + label var year "Year of survey" +* + + +*<_vermast_> + gen vermast = "`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen veralt = "`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization = "GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year= 2009 + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month = date + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> +/* <_hhid_note> + + Values are running number. Would have preferred making it a string with 0001 to 5184, but leave as is since + GMD has it this way. For PID concatenate this with 01-12 but leave as is. + + */ + gen hhid = recno + label var hhid "Household ID" +* + + +*<_pid_> + gen pid = memnum + label var pid "Individual ID" +* + + +*<_weight_> + * Weight already exists + *gen weight = . + label var weight "Survey sampling weight" +* + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + gen weight_q = . + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + * PSU already exists + *gen psu = . + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu = recno + label var ssu "Secondary sampling units" +* + + +*<_strata_> + gen strata = . + label var strata "Strata" +* + + +*<_wave_> + gen wave = . + label var wave "Survey wave" +* + + +*<_panel_> + gen panel = "" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no = . + label var visit_no "Visit number in panel" +* + +} + + +/*%%============================================================================================= + 3: Geography +==============================================================================================%%*/ + +{ + +*<_urban_> + * typev is 0 if YErevan, 1 if urban (other), rural is 2 + gen byte urban = inrange(typev, 0,1) + replace urban = 0 if typev == 2 + label var urban "Location is urban" + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban +* + + +*<_subnatid1_> +/* <_subnatid1_note> + + The variable is string and country-specific categorical. Numeric entries are coded in string format using the following naming convention: "1 – Hatay". That is, the variable itself is to be string, not a labelled numeric vector. + + Example of entries would be "1 - Alaska", "2 - Arkansas", ... + + */ + gen str subnatid1 = "" + replace subnatid1 = "1 - Yerevan" if marz == 1 + replace subnatid1 = "2 - Aragatsotn" if marz == 2 + replace subnatid1 = "3 - Ararat" if marz == 3 + replace subnatid1 = "4 - Armavir" if marz == 4 + replace subnatid1 = "5 - Gegharkunik" if marz == 5 + replace subnatid1 = "6 - Lori" if marz == 6 + replace subnatid1 = "7 - Kotayk" if marz == 7 + replace subnatid1 = "8 - Shirak" if marz == 8 + replace subnatid1 = "9 - Syunik" if marz == 9 + replace subnatid1 = "10 - Vayoc Dzor" if marz == 10 + replace subnatid1 = "11 - Tavush" if marz == 11 +* + + +*<_subnatid2_> + gen str subnatid2 = "" + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen str subnatid3 = "" + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> +/* <_subnatidsurvey_note> + + Variable denoting lowest administrative info to which the survey is still significat. + See entry in GLD Guidelines (https://github.com/worldbank/gld/blob/main/Support/A%20-%20Guides%20and%20Documentation/GLD_1.0_Guidelines.docx) for more details + + */ + decode urban, generate(helper) + generate subnatidsurvey = string(urban) + " - " + helper + drop helper + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> +/* <_subnatid1_prev_note> + + subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + + */ + gen subnatid1_prev = . + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev = . + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev = . + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code = . + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code = . + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code = . + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + + +/*%%============================================================================================= + 4: Demography +==============================================================================================%%*/ + +{ + +*<_hsize_> + * If keep all + gen hsize = members + /* * If drop absentees + gen helper = 1 + egen hh_abs_no = total(helper), by(recno) + replace hsize = hsize - hh_abs_no + drop helper hh_abs_no + */ + label var hsize "Household size" +* + + +*<_age_> + * Already in there + *gen age = . + label var age "Individual age" +* + + +*<_male_> + gen male = a1_1 + recode male (2 = 0) + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + gen relationharm = a1_2 + recode relationharm (4 = 3) (6 = 4) (7 = 5) (8 = 6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +* + + +*<_relationcs_> + clonevar relationcs = a1_2 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen byte marital = a1_5 + recode marital (3 = 5) (5 = 3) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed", replace + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all" + label values eye_dsablty dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values hear_dsablty dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values walk_dsablty dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values conc_dsord dsablty + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values slfcre_dsablty dsablty + label var slfcre_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values comm_dsablty dsablty + label var comm_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +==============================================================================================%%*/ + + +{ + +* Migration is not done as it is much more narrowly defined as migrated and returned. Thus anyone who +* migrated from their home town to the capital city would not be included. + +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + label values migrated_binary lblmigrated_binary + label var migrated_binary "Individual has migrated" +* + + +*<_migrated_years_> + gen migrated_years = . + label var migrated_years "Years since latest migration" +* + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + label de lblmigrated_from_urban 0 "Rural" 1 "Urban" + label values migrated_from_urban lblmigrated_from_urban + label var migrated_from_urban "Migrated from area" +* + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + label de lblmigrated_from_cat 1 "From same admin3 area" 2 "From same admin2 area" 3 "From same admin1 area" 4 "From other admin1 area" 5 "From other country" + label values migrated_from_cat lblmigrated_from_cat + label var migrated_from_cat "Category of migration area" +* + + +*<_migrated_from_code_> + gen migrated_from_code = . + *label de lblmigrated_from_code + *label values migrated_from_code lblmigrated_from_code + label var migrated_from_code "Code of migration area as subnatid level of migrated_from_cat" +* + + +*<_migrated_from_country_> + gen migrated_from_country = . + label var migrated_from_country "Code of migration country (ISO 3 Letter Code)" +* + + +*<_migrated_reason_> + gen migrated_reason = . + label de lblmigrated_reason 1 "Family reasons" 2 "Educational reasons" 3 "Employment" 4 "Forced (political reasons, natural disaster, …)" 5 "Other reasons" + label values migrated_reason lblmigrated_reason + label var migrated_reason "Reason for migrating" +* + + +} + + +/*%%============================================================================================= + 6: Education +==============================================================================================%%*/ + + +{ + +*<_ed_mod_age_> + +/* <_ed_mod_age_note> + +Education module is only asked to those XX and older. + + */ + +gen byte ed_mod_age = 6 +label var ed_mod_age "Education module application age" + +* + +*<_school_> + gen byte school = 0 + replace school = 1 if e2_4 == 1 + label var school "Attending school" + la de lblschool 0 "No" 1 "Yes" + label values school lblschool +* + + +*<_literacy_> + gen byte literacy = 1 + replace literacy = 0 if e2_2 == 0 + replace literacy = . if mi(e2_2) + label var literacy "Individual can read & write" + la de lblliteracy 0 "No" 1 "Yes" + label values literacy lblliteracy +* + + +*<_educy_> + * Number of years is a combination of level (e2_2) and years in that course (e2_3) + gen byte educy =. + replace educy = 0 if e2_2 == 0 + replace educy = e2_3 if e2_2 == 1 & inrange(e2_3,0,4) + replace educy = 4 + e2_3 if e2_2 == 2 & inrange(e2_3,0,5) + replace educy = 9 + e2_3 if e2_2 == 3 & inrange(e2_3,0,3) + replace educy = 9 + e2_3 if e2_2 == 4 & inrange(e2_3,0,2) + replace educy = 9 + e2_3 if e2_2 == 5 & inrange(e2_3,0,5) + replace educy = 12 + e2_3 if e2_2 == 6 & inrange(e2_3,0,7) + replace educy = 16 + e2_3 if e2_2 == 7 & inrange(e2_3,0,4) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7 =. + replace educat7 = 1 if e2_2 == 0 + replace educat7 = 2 if e2_2 == 1 & e2_3 < 4 + replace educat7 = 3 if e2_2 == 1 & e2_3 == 4 + replace educat7 = 4 if e2_2 == 2 + replace educat7 = 5 if inrange(e2_2, 3, 4) + replace educat7 = 6 if e2_2 == 5 + replace educat7 = 7 if inrange(e2_2, 6, 7) + label var educat7 "Level of education 1" + la de lbleducat7 1 "No education" 2 "Primary incomplete" 3 "Primary complete" 4 "Secondary incomplete" 5 "Secondary complete" 6 "Higher than secondary but not university" 7 "University incomplete or complete", replace + label values educat7 lbleducat7 +* + + +*<_educat5_> + gen byte educat5 = educat7 + recode educat5 4=3 5=4 6 7=5 + label var educat5 "Level of education 2" + la de lbleducat5 1 "No education" 2 "Primary incomplete" 3 "Primary complete but secondary incomplete" 4 "Secondary complete" 5 "Some tertiary/post-secondary" + label values educat5 lbleducat5 +* + + +*<_educat4_> + gen byte educat4 = educat7 + recode educat4 (2 3 4 = 2) (5=3) (6 7=4) + label var educat4 "Level of education 3" + la de lbleducat4 1 "No education" 2 "Primary" 3 "Secondary" 4 "Post-secondary" + label values educat4 lbleducat4 +* + + +*<_educat_orig_> + clonevar educat_orig = e2_2 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced = . + label var educat_isced "ISCED standardised level of education" +* + + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var "school literacy educy educat7 educat5 educat4 educat_orig educat_isced" + +foreach v of local ed_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < ed_mod_age & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < ed_mod_age & !missing(age) ) + } +} + + +* + + +} + + +/*%%============================================================================================= + 7: Training +==============================================================================================%%*/ + + +{ + +*<_vocational_> + gen vocational = . + label de lblvocational 0 "No" 1 "Yes" + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type = . + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l = . + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u = . + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen str vocational_field_orig = "" + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed = . + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + + +/*%%============================================================================================= + 8: Labour +==============================================================================================%%*/ + + +*<_minlaborage_> + gen byte minlaborage = 15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + gen byte lstatus = 1 if !mi(d1_4a) + + * For unemployed we need looking for a job (d2_5) and willing to accept (d3_11) + * Ensured all who looked answer the willing question + count if inrange(d3_5,1,2) & mi(d3_11) + assert `r(N)' == 0 + replace lstatus = 2 if lstatus == . & inrange(d3_5, 1, 2) & d3_11 == 1 + + * Normally, I would set all others to NLF, but given that we have the absentees, assign only to no in d2_5 + replace lstatus = 3 if lstatus == . & d3_5 == 3 + replace lstatus = 3 if lstatus == . & inrange(d3_5, 1, 2) & d3_11 == 2 + + replace lstatus = . if age < minlaborage + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + gen byte potential_lf = 0 + * Either not looking but would accept or looking but would not accept + replace potential_lf = 1 if (d3_5 == 3 & d3_11 == 1) | (inrange(d3_5,1,2) & d3_11 == 2) + replace potential_lf = . if age < minlaborage & age != . + replace potential_lf = . if lstatus != 3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment = . + replace underemployment = 1 if d1_25a == 1 + replace underemployment = 0 if d1_25a == 2 + replace underemployment = . if age < minlaborage & age != . + replace underemployment = . if lstatus != 1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=. + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=. + replace unempldur_l = 0 if d3_13 == 1 + replace unempldur_l = 1 if d3_13 == 2 + replace unempldur_l = 4 if d3_13 == 3 + replace unempldur_l = 7 if d3_13 == 4 + replace unempldur_l = 13 if d3_13 == 5 + replace unempldur_l = 25 if d3_13 == 6 + replace unempldur_l = 49 if d3_13 == 7 + replace unempldur_l = . if lstatus != 2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=. + replace unempldur_u = 1 if d3_13 == 1 + replace unempldur_u = 3 if d3_13 == 2 + replace unempldur_u = 6 if d3_13 == 3 + replace unempldur_u = 12 if d3_13 == 4 + replace unempldur_u = 24 if d3_13 == 5 + replace unempldur_u = 48 if d3_13 == 6 + replace unempldur_u = 999 if d3_13 == 7 + replace unempldur_u = . if lstatus != 2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* + +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat = d1_8a + recode empstat (2 3 = 1) (4 = 3) (5 6 8 = 4) (7 = 2) (90 = 5) + label var empstat "Employment status during past week primary job 7 day recall" + la de lblempstat 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status", replace + label values empstat lblempstat +* + + +*<_ocusec_> + gen byte ocusec = d1_9a + recode ocusec (2 = 1) (3/5 = 2) + replace ocusec = . if lstatus != 1 + label var ocusec "Sector of activity primary job 7 day recall" + la de lblocusec 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec lblocusec +* + + +*<_industry_orig_> + decode d1_5a, gen(industry_orig) + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic = "" + replace industrycat_isic = "A" if d1_5a == 1 + replace industrycat_isic = "B" if d1_5a == 2 + replace industrycat_isic = "C" if d1_5a == 3 + replace industrycat_isic = "D" if d1_5a == 4 + replace industrycat_isic = "E" if d1_5a == 5 + replace industrycat_isic = "F" if d1_5a == 6 + replace industrycat_isic = "G" if d1_5a == 7 + replace industrycat_isic = "H" if d1_5a == 8 + replace industrycat_isic = "I" if d1_5a == 9 + replace industrycat_isic = "J" if d1_5a == 10 + replace industrycat_isic = "K" if d1_5a == 11 + replace industrycat_isic = "L" if d1_5a == 12 + replace industrycat_isic = "M" if d1_5a == 13 + replace industrycat_isic = "N" if d1_5a == 14 + replace industrycat_isic = "O" if d1_5a == 15 + replace industrycat_isic = "P" if d1_5a == 16 + replace industrycat_isic = "Q" if d1_5a == 17 + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen byte industrycat10 = . + replace industrycat10 = 1 if inrange(d1_5a, 1, 2) + replace industrycat10 = 2 if d1_5a == 3 + replace industrycat10 = 3 if d1_5a == 4 + replace industrycat10 = 4 if d1_5a == 5 + replace industrycat10 = 5 if d1_5a == 6 + replace industrycat10 = 6 if inrange(d1_5a, 7, 8) + replace industrycat10 = 7 if d1_5a == 9 + replace industrycat10 = 8 if inrange(d1_5a, 10, 11) + replace industrycat10 = 9 if d1_5a == 12 + replace industrycat10 = 10 if inrange(d1_5a, 13, 17) + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4 = industrycat10 + recode industrycat4 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4 "Broad Economic Activities classification, primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig = . + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco) + *int_classif_universe, var(occup_isco) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_> + gen byte occup = . + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_occup_skill_> + gen occup_skill = . + replace occup_skill = 3 if inrange(occup, 1, 3) + replace occup_skill = 2 if inrange(occup, 4, 8) + replace occup_skill = 1 if occup == 9 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_wage_no_compen_> + egen double wage_no_compen = rowtotal(d1_17a d1_19a), missing + replace wage_no_compen = . if lstatus != 1 | empstat == 2 | wage_no_compen == 0 + label var wage_no_compen "Last wage payment primary job 7 day recall" +* + + +*<_unitwage_> + gen byte unitwage = 5 + replace unitwage = . if mi(wage_no_compen) + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours = d1_26a + replace whours = . if whours == 0 | lstatus != 1 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths = . + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> +/* <_wage_total_note> + + Use gross wages when available and net wages only when gross wages are not available. + This is done to make it easy to compare earnings in formal and informal sectors. + + */ + gen wage_total = . + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + gen byte contract = 0 + replace contract = 1 if d1_8a == 1 | d1_8a == 2 + replace contract = . if lstatus != 1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins = . + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec = . + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union = . + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen firmsize_l = . + replace firmsize_l = 1 if d1_11a == 1 + replace firmsize_l = 6 if d1_11a == 2 + replace firmsize_l = 16 if d1_11a == 3 + replace firmsize_l = 31 if d1_11a == 4 + replace firmsize_l = 50 if d1_11a == 5 + replace firmsize_l = 100 if d1_11a == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_l = 100 if ocusec == 1 & mi(firmsize_l) + + replace firmsize_l = . if lstatus != 1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen firmsize_u= . + replace firmsize_u = 5 if d1_11a == 1 + replace firmsize_u = 15 if d1_11a == 2 + replace firmsize_u = 30 if d1_11a == 3 + replace firmsize_u = 49 if d1_11a == 4 + replace firmsize_u = 99 if d1_11a == 5 + replace firmsize_u = 9999 if d1_11a == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_u = 9999 if ocusec == 1 & mi(firmsize_u) + + replace firmsize_u = . if lstatus != 1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + + +{ +*<_empstat_2_> + gen byte empstat_2 = d1_8b + recode empstat_2 (2 = 1) (5 6 = 4) (7 = 2) (0 = .) + label var empstat_2 "Employment status during past week secondary job 7 day recall" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2 = d1_9b + recode ocusec_2 (2 = 1) (3/5 = 2) (0 = .) + replace ocusec_2 = . if mi(empstat_2) + label var ocusec_2 "Sector of activity secondary job 7 day recall" + label values ocusec_2 lblocusec +* + + +*<_industry_orig_2_> + decode d1_5b, gen(industry_orig_2) + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2 = "" + replace industrycat_isic_2 = "A" if d1_5b == 1 + replace industrycat_isic_2 = "B" if d1_5b == 2 + replace industrycat_isic_2 = "C" if d1_5b == 3 + replace industrycat_isic_2 = "D" if d1_5b == 4 + replace industrycat_isic_2 = "E" if d1_5b == 5 + replace industrycat_isic_2 = "F" if d1_5b == 6 + replace industrycat_isic_2 = "G" if d1_5b == 7 + replace industrycat_isic_2 = "H" if d1_5b == 8 + replace industrycat_isic_2 = "I" if d1_5b == 9 + replace industrycat_isic_2 = "J" if d1_5b == 10 + replace industrycat_isic_2 = "K" if d1_5b == 11 + replace industrycat_isic_2 = "L" if d1_5b == 12 + replace industrycat_isic_2 = "M" if d1_5b == 13 + replace industrycat_isic_2 = "N" if d1_5b == 14 + replace industrycat_isic_2 = "O" if d1_5b == 15 + replace industrycat_isic_2 = "P" if d1_5b == 16 + replace industrycat_isic_2 = "Q" if d1_5b == 17 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen byte industrycat10_2 = . + replace industrycat10_2 = 1 if inrange(d1_5b, 1, 2) + replace industrycat10_2 = 2 if d1_5b == 3 + replace industrycat10_2 = 3 if d1_5b == 4 + replace industrycat10_2 = 4 if d1_5b == 5 + replace industrycat10_2 = 5 if d1_5b == 6 + replace industrycat10_2 = 6 if inrange(d1_5b, 7, 8) + replace industrycat10_2 = 7 if d1_5b == 9 + replace industrycat10_2 = 8 if inrange(d1_5b, 10, 11) + replace industrycat10_2 = 9 if d1_5b == 12 + replace industrycat10_2 = 10 if inrange(d1_5b, 13, 17) + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2 = industrycat10_2 + recode industrycat4_2 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2 "Broad Economic Activities classification, secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2 = . + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2 = "" + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_2_> + gen byte occup_2 = . + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_occup_skill_2_> + gen occup_skill_2 = . + replace occup_skill_2 = 3 if inrange(occup_2, 1, 3) + replace occup_skill_2 = 2 if inrange(occup_2, 4, 8) + replace occup_skill_2 = 1 if occup_2 == 9 + la de lblskill2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2 lblskill2 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_wage_no_compen_2_> + egen double wage_no_compen_2 = rowtotal(d1_17b d1_19b), missing + replace wage_no_compen_2 = . if mi(empstat_2) | empstat_2 == 2 | wage_no_compen_2 == 0 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2 = 5 + replace unitwage_2 = . if mi(wage_no_compen_2) + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2 = d1_26b + replace whours_2 = . if whours_2 == 0 | mi(empstat_2) + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2 = . + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2 = . + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen firmsize_l_2 = . + replace firmsize_l_2 = 1 if d1_11b == 1 + replace firmsize_l_2 = 6 if d1_11b == 2 + replace firmsize_l_2 = 16 if d1_11b == 3 + replace firmsize_l_2 = 31 if d1_11b == 4 + replace firmsize_l_2 = 50 if d1_11b == 5 + replace firmsize_l_2 = 100 if d1_11b == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_l_2 = 100 if ocusec_2 == 1 & mi(firmsize_l_2) + + replace firmsize_l_2 = . if mi(empstat_2) + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen firmsize_u_2 = . + replace firmsize_u_2 = 5 if d1_11b == 1 + replace firmsize_u_2 = 15 if d1_11b == 2 + replace firmsize_u_2 = 30 if d1_11b == 3 + replace firmsize_u_2 = 49 if d1_11b == 4 + replace firmsize_u_2 = 99 if d1_11b == 5 + replace firmsize_u_2 = 9999 if d1_11b == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_u_2 = 9999 if ocusec_2 == 1 & mi(firmsize_u_2) + + replace firmsize_u_2 = . if mi(empstat_2) + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others = . + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others = . + label var t_wage_nocompen_others "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others = . + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total = . + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total = . + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total = . + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ + +*<_lstatus_year_> + gen byte lstatus_year = . + replace lstatus_year=. if age < minlaborage & age != . + label var lstatus_year "Labor status during last year" + la de lbllstatus_year 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus_year lbllstatus_year +* + +*<_potential_lf_year_> + gen byte potential_lf_year = . + replace potential_lf_year=. if age < minlaborage & age != . + replace potential_lf_year = . if lstatus_year != 3 + label var potential_lf_year "Potential labour force status" + la de lblpotential_lf_year 0 "No" 1 "Yes" + label values potential_lf_year lblpotential_lf_year +* + + +*<_underemployment_year_> + gen byte underemployment_year = . + replace underemployment_year = . if age < minlaborage & age != . + replace underemployment_year = . if lstatus_year == 1 + label var underemployment_year "Underemployment status" + la de lblunderemployment_year 0 "No" 1 "Yes" + label values underemployment_year lblunderemployment_year +* + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ + +*<_empstat_year_> + gen byte empstat_year = . + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + +*<_ocusec_year_> + gen byte ocusec_year = . + label var ocusec_year "Sector of activity primary job 12 month recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + +*<_industry_orig_year_> + gen industry_orig_year = . + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year = . + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(industrycat_isic_year) + *int_classif_universe, var(industrycat_isic_year) universe(ISIC) + count + *list + *assert `r(N)' == 0 + restore + + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + +*<_industrycat10_year_> + gen byte industrycat10_year = . + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "Broad Economic Activities classification, primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year = . + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen occup_isco_year = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco_year) + *int_classif_universe, var(occup_isco_year) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year = . + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_occup_skill_year_> + gen occup_skill_year = . + replace occup_skill_year = 3 if inrange(occup_year, 1, 3) + replace occup_skill_year = 2 if inrange(occup_year, 4, 8) + replace occup_skill_year = 1 if occup_year == 9 + la de lblskillyear 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_year lblskillyear + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_wage_no_compen_year_> --- this var has the same name as other and when quoted in the keep and order codes is repeated. + gen double wage_no_compen_year = . + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year = . + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year = . + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year = . + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year = . + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year = . + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year = . + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year = . + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year = . + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen firmsize_l_year = . + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen firmsize_u_year = . + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year = . + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year = . + label var ocusec_2_year "Sector of activity secondary job 12 month recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year = . + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year = . + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year = . + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "Broad Economic Activities classification, secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year = . + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year = "" + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year = . + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year = . + replace occup_skill_2_year = 3 if inrange(occup_2_year, 1, 3) + replace occup_skill_2_year = 2 if inrange(occup_2_year, 4, 8) + replace occup_skill_2_year = 1 if occup_2_year == 9 + la de lblskilly2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2_year lblskilly2 + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year = . + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year = . + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year = . + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year = . + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year = . + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + +*<_firmsize_l_2_year_> + gen firmsize_l_2_year = . + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen firmsize_u_2_year = . + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year = . + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year = . + label var t_wage_nocompen_others_year "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 12 month recall" +* + +*<_t_wage_others_year_> + gen t_wage_others_year = . + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year = . + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year = . + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year = . + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs = . + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual = . + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc = . + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome = t_wage_total_year + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`out_file'", replace + +* diff --git a/GLD/ARM/ARM_2010_ILCS/ARM_2010_ILCS_V01_M_V01_A_GLD/Programs/ARM_2010_ILCS_V01_M_V01_A_GLD_ALL.do b/GLD/ARM/ARM_2010_ILCS/ARM_2010_ILCS_V01_M_V01_A_GLD/Programs/ARM_2010_ILCS_V01_M_V01_A_GLD_ALL.do new file mode 100644 index 000000000..0ebad0fd0 --- /dev/null +++ b/GLD/ARM/ARM_2010_ILCS/ARM_2010_ILCS_V01_M_V01_A_GLD/Programs/ARM_2010_ILCS_V01_M_V01_A_GLD_ALL.do @@ -0,0 +1,1767 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +==============================================================================================%%*/ + +/* ----------------------------------------------------------------------- + +<_Program name_> ARM_2010_ILCS_V01_M_V01_A_GLD_ALL.do +<_Application_> Stata 18 <_Application_> +<_Author(s)_> World Bank Jobs Group (gld@worldbank.org) +<_Date created_> 2024-09-11 + +------------------------------------------------------------------------- + +<_Country_> Armenia +<_Survey Title_> Integrated Living Conditions Survey +<_Survey Year_> 2010 +<_Study ID_> https://microdatalib.worldbank.org/index.php/catalog/2615 +<_Data collection from_> [MM/YYYY] +<_Data collection to_> [MM/YYYY] +<_Source of dataset_> [Source of data, e.g. NSO] +<_Sample size (HH)_> [#] +<_Sample size (IND)_> [#] +<_Sampling method_> [Brief description] +<_Geographic coverage_> [To what level is data significant] +<_Currency_> [Currency used for wages] + +----------------------------------------------------------------------- + +<_ICLS Version_> [Version of ICLS for Labor Questions] +<_ISCED Version_> [Version of ICLS for Labor Questions] +<_ISCO Version_> [Version of ICLS for Labor Questions] +<_OCCUP National_> [Version of ICLS for Labor Questions] +<_ISIC Version_> [Version of ICLS for Labor Questions] +<_INDUS National_> [Version of ICLS for Labor Questions] + +----------------------------------------------------------------------- +<_Version Control_> + +* Date: [YYYY-MM-DD] - [Description of changes] +* Date: [YYYY-MM-DD] - [Description of changes] + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +==============================================================================================%%*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m +set varabbrev off + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD-Harmonization/529026_MG/Countries" +local country "ARM" +local year "2010" +local survey "ILCS" +local vermast "V01" +local veralt "V01" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + +* Check whether there is a weight file +local has_wf = fileexists("`path_in_stata/weight.dta'") + +* Start with HH +use "`path_in_stata'/hh.dta" + +* If there is a weight file, merge it in +if `has_wf' { + merge 1:1 recno using "`path_in_stata/weight.dta'", assert(match) nogen +} + +* Add member roster +merge 1:m recno using "`path_in_stata'/mem.dta", assert(match) nogen + +* Add employment section +merge 1:1 recno memnum using "`path_in_stata'/d1", assert(match master) nogen + +* Add number labels +numlabel, add force + +/*%%============================================================================================= + 2: Survey & ID +==============================================================================================%%*/ + +{ + +*<_countrycode_> + gen str4 countrycode = "ARM" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname = "ILCS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey = "GLD" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v = "ICLS-13" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version = "" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version = "" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version = "isic_4" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year = 2010 + label var year "Year of survey" +* + + +*<_vermast_> + gen vermast = "`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen veralt = "`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization = "GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year= 2010 + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month = date + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> +/* <_hhid_note> + + Values are 1-5184 running. Would have preferred making it a string with 0001 to 5184, but leave as is since + GMD has it this way. For PID concatenate this with 01-12 but leave as is. + + */ + gen hhid = recno + label var hhid "Household ID" +* + + +*<_pid_> + gen pid = memnum + label var pid "Individual ID" +* + + +*<_weight_> + *gen weight = weight + label var weight "Survey sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + gen weight_q = . + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + gen psu = . + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu = . + label var ssu "Secondary sampling units" +* + + +*<_strata_> + gen strata = . + label var strata "Strata" +* + + +*<_wave_> + gen wave = . + label var wave "Survey wave" +* + + +*<_panel_> + gen panel = "" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no = . + label var visit_no "Visit number in panel" +* + +} + + +/*%%============================================================================================= + 3: Geography +==============================================================================================%%*/ + +{ + +*<_urban_> + * typev is 0 if Yerevan, 1 if urban (other), rural is 2 + gen byte urban = inrange(typev, 0,1) + replace urban = 0 if typev == 2 + label var urban "Location is urban" + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban +* + + + +*<_subnatid1_> +/* <_subnatid1_note> + + The variable is string and country-specific categorical. Numeric entries are coded in string format using the following naming convention: "1 – Hatay". That is, the variable itself is to be string, not a labelled numeric vector. + + Example of entries would be "1 - Alaska", "2 - Arkansas", ... + + */ + gen str subnatid1 = "" + replace subnatid1 = "1 - Yerevan" if marz == 1 + replace subnatid1 = "2 - Aragatsotn" if marz == 2 + replace subnatid1 = "3 - Ararat" if marz == 3 + replace subnatid1 = "4 - Armavir" if marz == 4 + replace subnatid1 = "5 - Gegharkunik" if marz == 5 + replace subnatid1 = "6 - Lori" if marz == 6 + replace subnatid1 = "7 - Kotayk" if marz == 7 + replace subnatid1 = "8 - Shirak" if marz == 8 + replace subnatid1 = "9 - Syunik" if marz == 9 + replace subnatid1 = "10 - Vayoc Dzor" if marz == 10 + replace subnatid1 = "11 - Tavush" if marz == 11 + label var subnatid1 "Subnational ID at First Administrative Level" +* + + +*<_subnatid2_> + gen str subnatid2 = "" + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen str subnatid3 = "" + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> +/* <_subnatidsurvey_note> + + Variable denoting lowest administrative info to which the survey is still significat. + See entry in GLD Guidelines (https://github.com/worldbank/gld/blob/main/Support/A%20-%20Guides%20and%20Documentation/GLD_1.0_Guidelines.docx) for more details + + */ + decode urban, generate(helper) + generate subnatidsurvey = string(urban) + " - " + helper + drop helper + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> +/* <_subnatid1_prev_note> + + subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + + */ + gen subnatid1_prev = . + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev = . + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev = . + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code = . + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code = . + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code = . + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + + +/*%%============================================================================================= + 4: Demography +==============================================================================================%%*/ + +{ + +*<_hsize_> + * If keep all + gen hsize = members + /* * If drop absentees + gen helper = 1 + egen hh_abs_no = total(helper), by(recno) + replace hsize = hsize - hh_abs_no + drop helper hh_abs_no + */ + label var hsize "Household size" +* + + +*<_age_> + * Already in there + *gen age = . + label var age "Individual age" +* + + +*<_male_> + gen male = a1_1 + recode male (2 = 0) + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + gen relationharm = a1_2 + recode relationharm (4 = 3) (6 = 4) (7 = 5) (8 = 6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +* + + +*<_relationcs_> + clonevar relationcs = a1_2 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen byte marital = a1_5 + recode marital (3 = 5) (5 = 3) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all" + label values eye_dsablty dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values hear_dsablty dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values walk_dsablty dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values conc_dsord dsablty + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values slfcre_dsablty dsablty + label var slfcre_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values comm_dsablty dsablty + label var comm_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +==============================================================================================%%*/ + + +{ + +* Migration is not done as it is much more narrowly defined as migrated and returned. Thus anyone who +* migrated from their home town to the capital city would not be included. + +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + label values migrated_binary lblmigrated_binary + label var migrated_binary "Individual has migrated" +* + + +*<_migrated_years_> + gen migrated_years = . + label var migrated_years "Years since latest migration" +* + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + label de lblmigrated_from_urban 0 "Rural" 1 "Urban" + label values migrated_from_urban lblmigrated_from_urban + label var migrated_from_urban "Migrated from area" +* + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + label de lblmigrated_from_cat 1 "From same admin3 area" 2 "From same admin2 area" 3 "From same admin1 area" 4 "From other admin1 area" 5 "From other country" + label values migrated_from_cat lblmigrated_from_cat + label var migrated_from_cat "Category of migration area" +* + + +*<_migrated_from_code_> + gen migrated_from_code = . + *label de lblmigrated_from_code + *label values migrated_from_code lblmigrated_from_code + label var migrated_from_code "Code of migration area as subnatid level of migrated_from_cat" +* + + +*<_migrated_from_country_> + gen migrated_from_country = . + label var migrated_from_country "Code of migration country (ISO 3 Letter Code)" +* + + +*<_migrated_reason_> + gen migrated_reason = . + label de lblmigrated_reason 1 "Family reasons" 2 "Educational reasons" 3 "Employment" 4 "Forced (political reasons, natural disaster, …)" 5 "Other reasons" + label values migrated_reason lblmigrated_reason + label var migrated_reason "Reason for migrating" +* + + +} + + +/*%%============================================================================================= + 6: Education +==============================================================================================%%*/ + + +{ + +*<_ed_mod_age_> + +/* <_ed_mod_age_note> + +Education module is only asked to those XX and older. + + */ + +gen byte ed_mod_age = 6 +label var ed_mod_age "Education module application age" + +* + + +*<_school_> + gen byte school = 0 + replace school = 1 if e2_7 == 1 + label var school "Attending school" + la de lblschool 0 "No" 1 "Yes" + label values school lblschool +* + + +*<_literacy_> + gen byte literacy = 1 + replace literacy = 0 if e2_2 == 0 + replace literacy = . if mi(e2_2) + label var literacy "Individual can read & write" + la de lblliteracy 0 "No" 1 "Yes" + label values literacy lblliteracy +* + + +*<_educy_> + * Number of years is a combination of level (e2_2) and years in that course (e2_3) + gen byte educy =. + replace educy = 0 if e2_2 == 0 + replace educy = e2_3 if e2_2 == 1 & inrange(e2_3,0,4) + replace educy = 4 + e2_3 if e2_2 == 2 & inrange(e2_3,0,5) + replace educy = 9 + e2_3 if e2_2 == 3 & inrange(e2_3,0,3) + replace educy = 9 + e2_3 if e2_2 == 4 & inrange(e2_3,0,2) + replace educy = 9 + e2_3 if e2_2 == 5 & inrange(e2_3,0,5) + replace educy = 12 + e2_3 if e2_2 == 6 & inrange(e2_3,0,7) + replace educy = 16 + e2_3 if e2_2 == 7 & inrange(e2_3,0,4) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7 =. + replace educat7 = 1 if e2_2 == 0 + replace educat7 = 2 if e2_2 == 1 & e2_3 < 4 + replace educat7 = 3 if e2_2 == 1 & e2_3 == 4 + replace educat7 = 4 if e2_2 == 2 + replace educat7 = 5 if inrange(e2_2, 3, 4) + replace educat7 = 6 if e2_2 == 5 + replace educat7 = 7 if inrange(e2_2, 6, 7) + label var educat7 "Level of education 1" + la de lbleducat7 1 "No education" 2 "Primary incomplete" 3 "Primary complete" 4 "Secondary incomplete" 5 "Secondary complete" 6 "Higher than secondary but not university" 7 "University incomplete or complete", replace + label values educat7 lbleducat7 +* + + +*<_educat5_> + gen byte educat5 = educat7 + recode educat5 4=3 5=4 6 7=5 + label var educat5 "Level of education 2" + la de lbleducat5 1 "No education" 2 "Primary incomplete" 3 "Primary complete but secondary incomplete" 4 "Secondary complete" 5 "Some tertiary/post-secondary" + label values educat5 lbleducat5 +* + + +*<_educat4_> + gen byte educat4 = educat7 + recode educat4 (2 3 4 = 2) (5=3) (6 7=4) + label var educat4 "Level of education 3" + la de lbleducat4 1 "No education" 2 "Primary" 3 "Secondary" 4 "Post-secondary" + label values educat4 lbleducat4 +* + + +*<_educat_orig_> + clonevar educat_orig = e2_2 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced = . + label var educat_isced "ISCED standardised level of education" +* + + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var "school literacy educy educat7 educat5 educat4 educat_orig educat_isced" + +foreach v of local ed_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < ed_mod_age & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < ed_mod_age & !missing(age) ) + } +} + + +* + + +} + + +/*%%============================================================================================= + 7: Training +==============================================================================================%%*/ + + +{ + +*<_vocational_> + gen vocational = . + label de lblvocational 0 "No" 1 "Yes" + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type = . + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l = . + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u = . + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen str vocational_field_orig = "" + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed = . + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + + +/*%%============================================================================================= + 8: Labour +==============================================================================================%%*/ + + +*<_minlaborage_> + gen byte minlaborage = 15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + * Logic is either have a job (yes to D1_1a) or returning (D1_2a) + * However the returning is subject to reasons (D1_3a) that are not + * a skip pattern but upon probing of the enumerator + * The below tab shows that some go to main job, others don't + * tab d1_3a d1_4a,m + gen byte lstatus = 1 if !mi(d1_4a) + + * For unemployed we need looking for a job (d2_5) and willing to accept (d2_10) + * Ensured all who looked answer the willing question + count if inrange(d2_5,1,2) & mi(d2_10) + assert `r(N)' == 0 + replace lstatus = 2 if lstatus == . & inrange(d2_5, 1, 2) & d2_10 == 1 + + * Normally, I would set all others to NLF, but given that we have the absentees, assign only to no in d2_5 + replace lstatus = 3 if lstatus == . & d2_5 == 3 + replace lstatus = 3 if lstatus == . & inrange(d2_5, 1, 2) & d2_10 == 2 + + replace lstatus = . if age < minlaborage + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + gen byte potential_lf = 0 + * Either not looking but would accept or looking but would not accept + replace potential_lf = 1 if (d2_5 == 3 & d2_10 == 1) | (inrange(d2_5,1,2) & d2_10 == 2) + replace potential_lf = . if age < minlaborage & age != . + replace potential_lf = . if lstatus != 3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment = 0 + replace underemployment = 1 if d1_23a == 7 + replace underemployment = . if age < minlaborage & age != . + replace underemployment = . if lstatus != 1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=. + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=. + replace unempldur_l = 0 if d2_9 == 1 + replace unempldur_l = 1 if d2_9 == 2 + replace unempldur_l = 4 if d2_9 == 3 + replace unempldur_l = 7 if d2_9 == 4 + replace unempldur_l = 13 if d2_9 == 5 + replace unempldur_l = 25 if d2_9 == 6 + replace unempldur_l = 49 if d2_9 == 7 + replace unempldur_l = . if lstatus != 2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=. + replace unempldur_u = 1 if d2_9 == 1 + replace unempldur_u = 3 if d2_9 == 2 + replace unempldur_u = 6 if d2_9 == 3 + replace unempldur_u = 12 if d2_9 == 4 + replace unempldur_u = 24 if d2_9 == 5 + replace unempldur_u = 48 if d2_9 == 6 + replace unempldur_u = 999 if d2_9 == 7 + replace unempldur_u = . if lstatus != 2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat = d1_7a + recode empstat (2 3 = 1) (4 = 3) (5 6 8 = 4) (7 = 2) + label var empstat "Employment status during past week primary job 7 day recall" + la de lblempstat 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat lblempstat +* + + +*<_ocusec_> + gen byte ocusec = d1_8a + recode ocusec (2 = 1) (3/5 = 2) + replace ocusec = . if lstatus != 1 + label var ocusec "Sector of activity primary job 7 day recall" + la de lblocusec 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec lblocusec +* + + +*<_industry_orig_> + decode d1_5a, gen(industry_orig) + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic = "" + replace industrycat_isic = "A" if d1_5a == 1 + replace industrycat_isic = "B" if d1_5a == 2 + replace industrycat_isic = "C" if d1_5a == 3 + replace industrycat_isic = "D" if d1_5a == 4 + replace industrycat_isic = "E" if d1_5a == 5 + replace industrycat_isic = "F" if d1_5a == 6 + replace industrycat_isic = "G" if d1_5a == 7 + replace industrycat_isic = "H" if d1_5a == 8 + replace industrycat_isic = "I" if d1_5a == 9 + replace industrycat_isic = "J" if d1_5a == 10 + replace industrycat_isic = "K" if d1_5a == 11 + replace industrycat_isic = "L" if d1_5a == 12 + replace industrycat_isic = "M" if d1_5a == 13 + replace industrycat_isic = "N" if d1_5a == 14 + replace industrycat_isic = "O" if d1_5a == 15 + replace industrycat_isic = "P" if d1_5a == 16 + replace industrycat_isic = "Q" if d1_5a == 17 + replace industrycat_isic = "R" if d1_5a == 18 + replace industrycat_isic = "S" if d1_5a == 19 + replace industrycat_isic = "T" if d1_5a == 20 + replace industrycat_isic = "U" if d1_5a == 21 + + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen byte industrycat10 = . + replace industrycat10 = 1 if d1_5a == 1 + replace industrycat10 = 2 if d1_5a == 2 + replace industrycat10 = 3 if d1_5a == 3 + replace industrycat10 = 4 if inrange(d1_5a,4,5) + replace industrycat10 = 5 if d1_5a == 6 + replace industrycat10 = 6 if inlist(d1_5a, 7, 9) + replace industrycat10 = 7 if inlist(d1_5a, 8, 10) + replace industrycat10 = 8 if inrange(d1_5a, 11, 14) + replace industrycat10 = 9 if d1_5a == 15 + replace industrycat10 = 10 if inrange(d1_5a, 16, 21) + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4 = industrycat10 + recode industrycat4 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4 "Broad Economic Activities classification, primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig = . + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco) + *int_classif_universe, var(occup_isco) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_> + gen byte occup = . + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_occup_skill_> + gen occup_skill = . + replace occup_skill = 3 if inrange(occup, 1, 3) + replace occup_skill = 2 if inrange(occup, 4, 8) + replace occup_skill = 1 if occup == 9 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_wage_no_compen_> + egen double wage_no_compen = rowtotal(d1_13a d1_15a), missing + replace wage_no_compen = . if lstatus != 1 | empstat == 2 | wage_no_compen == 0 + label var wage_no_compen "Last wage payment primary job 7 day recall" +* + + +*<_unitwage_> + gen byte unitwage = 5 + replace unitwage = . if mi(wage_no_compen) + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours = d1_21a + replace whours = . if whours == 0 | lstatus != 1 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths = . + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> +/* <_wage_total_note> + + Use gross wages when available and net wages only when gross wages are not available. + This is done to make it easy to compare earnings in formal and informal sectors. + + */ + gen wage_total = . + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + gen byte contract = 0 + replace contract = 1 if d1_7a == 1 | d1_7a == 2 + replace contract = . if lstatus != 1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins = . + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec = . + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union = . + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen firmsize_l = . + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen firmsize_u= . + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + + +{ +*<_empstat_2_> + gen byte empstat_2 = d1_7b + recode empstat_2 (2 3 = 1) (4 = 3) (5 6 8 = 4) (7 = 2) + label var empstat_2 "Employment status during past week secondary job 7 day recall" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2 = d1_8b + recode ocusec_2 (2 = 1) (3/5 = 2) (0 = .) + replace ocusec_2 = . if mi(empstat_2) + label var ocusec_2 "Sector of activity secondary job 7 day recall" + label values ocusec_2 lblocusec +* + + +*<_industry_orig_2_> + decode d1_5b, gen(industry_orig_2) + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2 = "" + replace industrycat_isic_2 = "A" if d1_5b == 1 + replace industrycat_isic_2 = "B" if d1_5b == 2 + replace industrycat_isic_2 = "C" if d1_5b == 3 + replace industrycat_isic_2 = "D" if d1_5b == 4 + replace industrycat_isic_2 = "E" if d1_5b == 5 + replace industrycat_isic_2 = "F" if d1_5b == 6 + replace industrycat_isic_2 = "G" if d1_5b == 7 + replace industrycat_isic_2 = "H" if d1_5b == 8 + replace industrycat_isic_2 = "I" if d1_5b == 9 + replace industrycat_isic_2 = "J" if d1_5b == 10 + replace industrycat_isic_2 = "K" if d1_5b == 11 + replace industrycat_isic_2 = "L" if d1_5b == 12 + replace industrycat_isic_2 = "M" if d1_5b == 13 + replace industrycat_isic_2 = "N" if d1_5b == 14 + replace industrycat_isic_2 = "O" if d1_5b == 15 + replace industrycat_isic_2 = "P" if d1_5b == 16 + replace industrycat_isic_2 = "Q" if d1_5b == 17 + replace industrycat_isic_2 = "R" if d1_5b == 18 + replace industrycat_isic_2 = "S" if d1_5b == 19 + replace industrycat_isic_2 = "T" if d1_5b == 20 + replace industrycat_isic_2 = "U" if d1_5b == 21 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen byte industrycat10_2 = . + replace industrycat10_2 = 1 if d1_5b == 1 + replace industrycat10_2 = 2 if d1_5b == 2 + replace industrycat10_2 = 3 if d1_5b == 3 + replace industrycat10_2 = 4 if inrange(d1_5b,4,5) + replace industrycat10_2 = 5 if d1_5b == 6 + replace industrycat10_2 = 6 if inlist(d1_5b, 7, 9) + replace industrycat10_2 = 7 if inlist(d1_5b, 8, 10) + replace industrycat10_2 = 8 if inrange(d1_5b, 11, 14) + replace industrycat10_2 = 9 if d1_5b == 15 + replace industrycat10_2 = 10 if inrange(d1_5b, 16, 21) + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2 = industrycat10_2 + recode industrycat4_2 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2 "Broad Economic Activities classification, secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2 = . + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2 = "" + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_2_> + gen byte occup_2 = . + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_occup_skill_2_> + gen occup_skill_2 = . + replace occup_skill_2 = 3 if inrange(occup_2, 1, 3) + replace occup_skill_2 = 2 if inrange(occup_2, 4, 8) + replace occup_skill_2 = 1 if occup_2 == 9 + la de lblskill2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2 lblskill2 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_wage_no_compen_2_> + egen double wage_no_compen_2 = rowtotal(d1_13b d1_15b), missing + replace wage_no_compen_2 = . if mi(empstat_2) | empstat_2 == 2 | wage_no_compen_2 == 0 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2 = 5 + replace unitwage_2 = . if mi(wage_no_compen_2) + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2 = d1_21b + replace whours_2 = . if whours_2 == 0 | mi(empstat_2) + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2 = . + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2 = . + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen firmsize_l_2 = . + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen firmsize_u_2 = . + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others = . + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others = . + label var t_wage_nocompen_others "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others = . + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total = . + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total = . + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total = . + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ + +*<_lstatus_year_> + gen byte lstatus_year = . + replace lstatus_year=. if age < minlaborage & age != . + label var lstatus_year "Labor status during last year" + la de lbllstatus_year 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus_year lbllstatus_year +* + +*<_potential_lf_year_> + gen byte potential_lf_year = . + replace potential_lf_year=. if age < minlaborage & age != . + replace potential_lf_year = . if lstatus_year != 3 + label var potential_lf_year "Potential labour force status" + la de lblpotential_lf_year 0 "No" 1 "Yes" + label values potential_lf_year lblpotential_lf_year +* + + +*<_underemployment_year_> + gen byte underemployment_year = . + replace underemployment_year = . if age < minlaborage & age != . + replace underemployment_year = . if lstatus_year == 1 + label var underemployment_year "Underemployment status" + la de lblunderemployment_year 0 "No" 1 "Yes" + label values underemployment_year lblunderemployment_year +* + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ + +*<_empstat_year_> + gen byte empstat_year = . + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + +*<_ocusec_year_> + gen byte ocusec_year = . + label var ocusec_year "Sector of activity primary job 12 month recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + +*<_industry_orig_year_> + gen industry_orig_year = . + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year = . + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(industrycat_isic_year) + *int_classif_universe, var(industrycat_isic_year) universe(ISIC) + count + *list + *assert `r(N)' == 0 + restore + + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + +*<_industrycat10_year_> + gen byte industrycat10_year = . + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "Broad Economic Activities classification, primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year = . + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen occup_isco_year = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco_year) + *int_classif_universe, var(occup_isco_year) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year = . + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_occup_skill_year_> + gen occup_skill_year = . + replace occup_skill_year = 3 if inrange(occup_year, 1, 3) + replace occup_skill_year = 2 if inrange(occup_year, 4, 8) + replace occup_skill_year = 1 if occup_year == 9 + la de lblskillyear 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_year lblskillyear + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_wage_no_compen_year_> --- this var has the same name as other and when quoted in the keep and order codes is repeated. + gen double wage_no_compen_year = . + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year = . + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year = . + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year = . + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year = . + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year = . + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year = . + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year = . + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year = . + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen firmsize_l_year = . + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen firmsize_u_year = . + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year = . + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year = . + label var ocusec_2_year "Sector of activity secondary job 12 month recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year = . + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year = . + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year = . + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "Broad Economic Activities classification, secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year = . + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year = "" + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year = . + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year = . + replace occup_skill_2_year = 3 if inrange(occup_2_year, 1, 3) + replace occup_skill_2_year = 2 if inrange(occup_2_year, 4, 8) + replace occup_skill_2_year = 1 if occup_2_year == 9 + la de lblskilly2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2_year lblskilly2 + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year = . + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year = . + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year = . + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year = . + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year = . + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + +*<_firmsize_l_2_year_> + gen firmsize_l_2_year = . + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen firmsize_u_2_year = . + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year = . + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year = . + label var t_wage_nocompen_others_year "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 12 month recall" +* + +*<_t_wage_others_year_> + gen t_wage_others_year = . + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year = . + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year = . + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year = . + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs = . + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual = . + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc = . + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome = t_wage_total_year + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`out_file'", replace + +* diff --git a/GLD/ARM/ARM_2011_ILCS/ARM_2011_ILCS_V01_M_V01_A_GLD/Programs/ARM_2011_ILCS_V01_M_V01_A_GLD_ALL.do b/GLD/ARM/ARM_2011_ILCS/ARM_2011_ILCS_V01_M_V01_A_GLD/Programs/ARM_2011_ILCS_V01_M_V01_A_GLD_ALL.do new file mode 100644 index 000000000..9ea07ab49 --- /dev/null +++ b/GLD/ARM/ARM_2011_ILCS/ARM_2011_ILCS_V01_M_V01_A_GLD/Programs/ARM_2011_ILCS_V01_M_V01_A_GLD_ALL.do @@ -0,0 +1,1782 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +==============================================================================================%%*/ + +/* ----------------------------------------------------------------------- + +<_Program name_> ARM_2011_ILCS_V01_M_V01_A_GLD_ALL.do +<_Application_> Stata 18 <_Application_> +<_Author(s)_> World Bank Jobs Group (gld@worldbank.org) +<_Date created_> 2024-09-11 + +------------------------------------------------------------------------- + +<_Country_> Armenia +<_Survey Title_> Integrated Living Conditions Survey +<_Survey Year_> 2011 +<_Study ID_> https://microdatalib.worldbank.org/index.php/catalog/2615 +<_Data collection from_> [MM/YYYY] +<_Data collection to_> [MM/YYYY] +<_Source of dataset_> [Source of data, e.g. NSO] +<_Sample size (HH)_> [#] +<_Sample size (IND)_> [#] +<_Sampling method_> [Brief description] +<_Geographic coverage_> [To what level is data significant] +<_Currency_> [Currency used for wages] + +----------------------------------------------------------------------- + +<_ICLS Version_> [Version of ICLS for Labor Questions] +<_ISCED Version_> [Version of ICLS for Labor Questions] +<_ISCO Version_> [Version of ICLS for Labor Questions] +<_OCCUP National_> [Version of ICLS for Labor Questions] +<_ISIC Version_> [Version of ICLS for Labor Questions] +<_INDUS National_> [Version of ICLS for Labor Questions] + +----------------------------------------------------------------------- +<_Version Control_> + +* Date: [YYYY-MM-DD] - [Description of changes] +* Date: [YYYY-MM-DD] - [Description of changes] + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +==============================================================================================%%*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m +set varabbrev off + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD-Harmonization/529026_MG/Countries" +local country "ARM" +local year "2011" +local survey "ILCS" +local vermast "V01" +local veralt "V01" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + +* Check whether there is a weight file +local has_wf = fileexists("`path_in_stata'/Weight.dta") + +* Start with HH +use "`path_in_stata'/hh.dta" + +* If there is a weight file, merge it in +if `has_wf' { + merge 1:1 recno using "`path_in_stata'/Weight.dta", assert(match) nogen +} + +* Add member roster +merge 1:m recno using "`path_in_stata'/mem.dta", assert(match) nogen + +* Add employment section +merge 1:1 recno memnum using "`path_in_stata'/d1", assert(match master) nogen + +* Add number labels +numlabel, add force + +/*%%============================================================================================= + 2: Survey & ID +==============================================================================================%%*/ + +{ + +*<_countrycode_> + gen str4 countrycode = "ARM" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname = "ILCS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey = "GLD" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v = "ICLS-13" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version = "" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version = "" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version = "isic_4" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year = 2011 + label var year "Year of survey" +* + + +*<_vermast_> + gen vermast = "`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen veralt = "`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization = "GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year= 2011 + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month = date + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> +/* <_hhid_note> + + Values are 1-5184 running. Would have preferred making it a string with 0001 to 5184, but leave as is since + GMD has it this way. For PID concatenate this with 01-12 but leave as is. + + */ + gen hhid = recno + label var hhid "Household ID" +* + + +*<_pid_> + gen pid = memnum + label var pid "Individual ID" +* + + +*<_weight_> + * Weight already exists + *gen weight = . + label var weight "Survey sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + gen weight_q = . + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + gen psu = . + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu = . + label var ssu "Secondary sampling units" +* + + +*<_strata_> + gen strata = . + label var strata "Strata" +* + + +*<_wave_> + gen wave = . + label var wave "Survey wave" +* + + +*<_panel_> + gen panel = "" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no = . + label var visit_no "Visit number in panel" +* + +} + + +/*%%============================================================================================= + 3: Geography +==============================================================================================%%*/ + +{ + +*<_urban_> + * typev is 0 if YErevan, 1 if urban (other), rural is 2 + gen byte urban = inrange(typev, 0,1) + replace urban = 0 if typev == 2 + label var urban "Location is urban" + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban +* + + +*<_subnatid1_> +/* <_subnatid1_note> + + The variable is string and country-specific categorical. Numeric entries are coded in string format using the following naming convention: "1 – Hatay". That is, the variable itself is to be string, not a labelled numeric vector. + + Example of entries would be "1 - Alaska", "2 - Arkansas", ... + + */ + gen str subnatid1 = "" + replace subnatid1 = "1 - Yerevan" if marz == 1 + replace subnatid1 = "2 - Aragatsotn" if marz == 2 + replace subnatid1 = "3 - Ararat" if marz == 3 + replace subnatid1 = "4 - Armavir" if marz == 4 + replace subnatid1 = "5 - Gegharkunik" if marz == 5 + replace subnatid1 = "6 - Lori" if marz == 6 + replace subnatid1 = "7 - Kotayk" if marz == 7 + replace subnatid1 = "8 - Shirak" if marz == 8 + replace subnatid1 = "9 - Syunik" if marz == 9 + replace subnatid1 = "10 - Vayoc Dzor" if marz == 10 + replace subnatid1 = "11 - Tavush" if marz == 11 +* + + +*<_subnatid2_> + gen str subnatid2 = "" + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen str subnatid3 = "" + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> +/* <_subnatidsurvey_note> + + Variable denoting lowest administrative info to which the survey is still significat. + See entry in GLD Guidelines (https://github.com/worldbank/gld/blob/main/Support/A%20-%20Guides%20and%20Documentation/GLD_1.0_Guidelines.docx) for more details + + */ + decode urban, generate(helper) + generate subnatidsurvey = string(urban) + " - " + helper + drop helper + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> +/* <_subnatid1_prev_note> + + subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + + */ + gen subnatid1_prev = . + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev = . + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev = . + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code = . + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code = . + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code = . + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + + +/*%%============================================================================================= + 4: Demography +==============================================================================================%%*/ + +{ + +*<_hsize_> + * If keep all + gen hsize = members + /* * If drop absentees + gen helper = 1 + egen hh_abs_no = total(helper), by(recno) + replace hsize = hsize - hh_abs_no + drop helper hh_abs_no + */ + label var hsize "Household size" +* + + +*<_age_> + * Already in there + *gen age = . + label var age "Individual age" +* + + +*<_male_> + gen male = a1_1 + recode male (2 = 0) + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + gen relationharm = a1_2 + recode relationharm (4 = 3) (6 = 4) (7 = 5) (8 = 6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +* + + +*<_relationcs_> + clonevar relationcs = a1_2 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen byte marital = a1_5 + recode marital (3 = 5) (5 = 3) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all" + label values eye_dsablty dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values hear_dsablty dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values walk_dsablty dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values conc_dsord dsablty + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values slfcre_dsablty dsablty + label var slfcre_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values comm_dsablty dsablty + label var comm_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +==============================================================================================%%*/ + + +{ + +* Migration is not done as it is much more narrowly defined as migrated and returned. Thus anyone who +* migrated from their home town to the capital city would not be included. + +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + label values migrated_binary lblmigrated_binary + label var migrated_binary "Individual has migrated" +* + + +*<_migrated_years_> + gen migrated_years = . + label var migrated_years "Years since latest migration" +* + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + label de lblmigrated_from_urban 0 "Rural" 1 "Urban" + label values migrated_from_urban lblmigrated_from_urban + label var migrated_from_urban "Migrated from area" +* + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + label de lblmigrated_from_cat 1 "From same admin3 area" 2 "From same admin2 area" 3 "From same admin1 area" 4 "From other admin1 area" 5 "From other country" + label values migrated_from_cat lblmigrated_from_cat + label var migrated_from_cat "Category of migration area" +* + + +*<_migrated_from_code_> + gen migrated_from_code = . + *label de lblmigrated_from_code + *label values migrated_from_code lblmigrated_from_code + label var migrated_from_code "Code of migration area as subnatid level of migrated_from_cat" +* + + +*<_migrated_from_country_> + gen migrated_from_country = . + label var migrated_from_country "Code of migration country (ISO 3 Letter Code)" +* + + +*<_migrated_reason_> + gen migrated_reason = . + label de lblmigrated_reason 1 "Family reasons" 2 "Educational reasons" 3 "Employment" 4 "Forced (political reasons, natural disaster, …)" 5 "Other reasons" + label values migrated_reason lblmigrated_reason + label var migrated_reason "Reason for migrating" +* + + +} + + +/*%%============================================================================================= + 6: Education +==============================================================================================%%*/ + + +{ + +*<_ed_mod_age_> + +/* <_ed_mod_age_note> + +Education module is only asked to those 6 and older. + + */ + +gen byte ed_mod_age = 6 +label var ed_mod_age "Education module application age" + +* + +*<_school_> + gen byte school = 0 + replace school = 1 if e2_7 == 1 + label var school "Attending school" + la de lblschool 0 "No" 1 "Yes" + label values school lblschool +* + + +*<_literacy_> + gen byte literacy = 1 + replace literacy = 0 if e2_2 == 0 + replace literacy = . if mi(e2_2) + label var literacy "Individual can read & write" + la de lblliteracy 0 "No" 1 "Yes" + label values literacy lblliteracy +* + + +*<_educy_> + * Number of years is a combination of level (e2_2) and years in that course (e2_3) + gen byte educy =. + replace educy = 0 if e2_2 == 0 + replace educy = e2_3 if e2_2 == 1 & inrange(e2_3,0,4) + replace educy = 4 + e2_3 if e2_2 == 2 & inrange(e2_3,0,5) + replace educy = 9 + e2_3 if e2_2 == 3 & inrange(e2_3,0,3) + replace educy = 9 + e2_3 if e2_2 == 4 & inrange(e2_3,0,2) + replace educy = 9 + e2_3 if e2_2 == 5 & inrange(e2_3,0,5) + replace educy = 12 + e2_3 if e2_2 == 6 & inrange(e2_3,0,7) + replace educy = 16 + e2_3 if e2_2 == 7 & inrange(e2_3,0,4) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7 =. + replace educat7 = 1 if e2_2 == 0 + replace educat7 = 2 if e2_2 == 1 & e2_3 < 4 + replace educat7 = 3 if e2_2 == 1 & e2_3 == 4 + replace educat7 = 4 if e2_2 == 2 + replace educat7 = 5 if inrange(e2_2, 3, 4) + replace educat7 = 6 if e2_2 == 5 + replace educat7 = 7 if inrange(e2_2, 6, 7) + label var educat7 "Level of education 1" + la de lbleducat7 1 "No education" 2 "Primary incomplete" 3 "Primary complete" 4 "Secondary incomplete" 5 "Secondary complete" 6 "Higher than secondary but not university" 7 "University incomplete or complete", replace + label values educat7 lbleducat7 +* + + +*<_educat5_> + gen byte educat5 = educat7 + recode educat5 4=3 5=4 6 7=5 + label var educat5 "Level of education 2" + la de lbleducat5 1 "No education" 2 "Primary incomplete" 3 "Primary complete but secondary incomplete" 4 "Secondary complete" 5 "Some tertiary/post-secondary" + label values educat5 lbleducat5 +* + + +*<_educat4_> + gen byte educat4 = educat7 + recode educat4 (2 3 4 = 2) (5=3) (6 7=4) + label var educat4 "Level of education 3" + la de lbleducat4 1 "No education" 2 "Primary" 3 "Secondary" 4 "Post-secondary" + label values educat4 lbleducat4 +* + + +*<_educat_orig_> + clonevar educat_orig = e2_2 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced = . + label var educat_isced "ISCED standardised level of education" +* + + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var "school literacy educy educat7 educat5 educat4 educat_orig educat_isced" + +foreach v of local ed_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < ed_mod_age & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < ed_mod_age & !missing(age) ) + } +} + + +* + + +} + + +/*%%============================================================================================= + 7: Training +==============================================================================================%%*/ + + +{ + +*<_vocational_> + gen vocational = . + label de lblvocational 0 "No" 1 "Yes" + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type = . + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l = . + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u = . + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen str vocational_field_orig = "" + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed = . + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + + +/*%%============================================================================================= + 8: Labour +==============================================================================================%%*/ + + +*<_minlaborage_> + gen byte minlaborage = 15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + * Logic is either have a job (yes to D1_1a) or returning (D1_2a) + * However the returning is subject to reasons (D1_3a) that are not + * a skip pattern but upon probing of the enumerator + * The below tab shows that some go to main job, others don't + * tab d1_3a d1_4a,m + gen byte lstatus = 1 if !mi(d1_4a) + + * For unemployed we need looking for a job (d2_5) and willing to accept (d2_10) + * Ensured all who looked answer the willing question + count if inrange(d2_5,1,2) & mi(d2_10) + assert `r(N)' == 0 + replace lstatus = 2 if lstatus == . & inrange(d2_5, 1, 2) & d2_10 == 1 + + * Normally, I would set all others to NLF, but given that we have the absentees, assign only to no in d2_5 + replace lstatus = 3 if lstatus == . & d2_5 == 3 + replace lstatus = 3 if lstatus == . & inrange(d2_5, 1, 2) & d2_10 == 2 + + replace lstatus = . if age < minlaborage + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + gen byte potential_lf = 0 + * Either not looking but would accept or looking but would not accept + replace potential_lf = 1 if (d2_5 == 3 & d2_10 == 1) | (inrange(d2_5,1,2) & d2_10 == 2) + replace potential_lf = . if age < minlaborage & age != . + replace potential_lf = . if lstatus != 3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment = 0 + replace underemployment = 1 if d1_24a == 7 + replace underemployment = . if age < minlaborage & age != . + replace underemployment = . if lstatus != 1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=. + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=. + replace unempldur_l = 0 if d2_9 == 1 + replace unempldur_l = 1 if d2_9 == 2 + replace unempldur_l = 4 if d2_9 == 3 + replace unempldur_l = 7 if d2_9 == 4 + replace unempldur_l = 13 if d2_9 == 5 + replace unempldur_l = 25 if d2_9 == 6 + replace unempldur_l = 49 if d2_9 == 7 + replace unempldur_l = . if lstatus != 2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=. + replace unempldur_u = 1 if d2_9 == 1 + replace unempldur_u = 3 if d2_9 == 2 + replace unempldur_u = 6 if d2_9 == 3 + replace unempldur_u = 12 if d2_9 == 4 + replace unempldur_u = 24 if d2_9 == 5 + replace unempldur_u = 48 if d2_9 == 6 + replace unempldur_u = 999 if d2_9 == 7 + replace unempldur_u = . if lstatus != 2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat = d1_7a + recode empstat (2 3 = 1) (4 = 3) (5 6 8 = 4) (7 = 2) + label var empstat "Employment status during past week primary job 7 day recall" + la de lblempstat 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat lblempstat +* + + +*<_ocusec_> + gen byte ocusec = d1_9a + recode ocusec (2 = 1) (3/5 = 2) + replace ocusec = . if lstatus != 1 + label var ocusec "Sector of activity primary job 7 day recall" + la de lblocusec 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec lblocusec +* + + +*<_industry_orig_> + gen industry_orig = string(d1_5a, "%02.0f") + replace industry_orig = "" if industry_orig == "." + replace industry_orig = "" if lstatus != 1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic = industry_orig + "00" if !mi(industry_orig) + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + drop if missing(industrycat_isic) + int_classif_universe, var(industrycat_isic) universe(ISIC) + count + list + *assert `r(N)' == 0 + restore + + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen byte industrycat10 = . + replace industrycat10 = 1 if inrange(industry_orig, "01", "03") + replace industrycat10 = 2 if inrange(industry_orig, "05", "09") + replace industrycat10 = 3 if inrange(industry_orig, "10", "33") + replace industrycat10 = 4 if inrange(industry_orig, "35", "39") + replace industrycat10 = 5 if inrange(industry_orig, "41", "43") + replace industrycat10 = 6 if inrange(industry_orig, "45", "47") | inrange(industry_orig, "55", "56") + replace industrycat10 = 7 if inrange(industry_orig, "49", "53") | inrange(industry_orig, "58", "63") + replace industrycat10 = 8 if inrange(industry_orig, "64", "82") + replace industrycat10 = 9 if inrange(industry_orig, "84", "84") + replace industrycat10 = 10 if inrange(industry_orig, "85", "99") + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4 = industrycat10 + recode industrycat4 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4 "Broad Economic Activities classification, primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig = . + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco) + *int_classif_universe, var(occup_isco) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_> + gen byte occup = . + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_occup_skill_> + gen occup_skill = . + replace occup_skill = 3 if inrange(occup, 1, 3) + replace occup_skill = 2 if inrange(occup, 4, 8) + replace occup_skill = 1 if occup == 9 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_wage_no_compen_> + egen double wage_no_compen = rowtotal(d1_14a d1_16a), missing + replace wage_no_compen = . if lstatus != 1 | empstat == 2 | wage_no_compen == 0 + label var wage_no_compen "Last wage payment primary job 7 day recall" +* + + +*<_unitwage_> + gen byte unitwage = 5 + replace unitwage = . if mi(wage_no_compen) + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours = d1_22a + replace whours = . if whours == 0 | lstatus != 1 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths = . + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> +/* <_wage_total_note> + + Use gross wages when available and net wages only when gross wages are not available. + This is done to make it easy to compare earnings in formal and informal sectors. + + */ + gen wage_total = . + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + gen byte contract = 0 + replace contract = 1 if d1_7a == 1 | d1_7a == 2 + replace contract = . if lstatus != 1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins = . + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec = . + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union = . + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen firmsize_l = . + replace firmsize_l = 1 if d1_11a == 1 + replace firmsize_l = 6 if d1_11a == 2 + replace firmsize_l = 16 if d1_11a == 3 + replace firmsize_l = 31 if d1_11a == 4 + replace firmsize_l = 50 if d1_11a == 5 + replace firmsize_l = 100 if d1_11a == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_l = 100 if ocusec == 1 & mi(firmsize_l) + + replace firmsize_l = . if lstatus != 1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen firmsize_u= . + replace firmsize_u = 5 if d1_11a == 1 + replace firmsize_u = 15 if d1_11a == 2 + replace firmsize_u = 30 if d1_11a == 3 + replace firmsize_u = 49 if d1_11a == 4 + replace firmsize_u = 99 if d1_11a == 5 + replace firmsize_u = 9999 if d1_11a == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_u = 9999 if ocusec == 1 & mi(firmsize_u) + + replace firmsize_u = . if lstatus != 1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + + +{ +*<_empstat_2_> + gen byte empstat_2 = d1_7b + recode empstat_2 (2 3 = 1) (4 = 3) (5 6 8 = 4) (7 = 2) + label var empstat_2 "Employment status during past week secondary job 7 day recall" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2 = d1_9b + recode ocusec_2 (2 = 1) (3/5 = 2) (0 = .) + replace ocusec_2 = . if mi(empstat_2) + label var ocusec_2 "Sector of activity secondary job 7 day recall" + label values ocusec_2 lblocusec +* + + +*<_industry_orig_2_> + gen industry_orig_2 = string(d1_5b, "%02.0f") + replace industry_orig_2 = "" if industry_orig_2 == "." + replace industry_orig_2 = "" if industry_orig_2 == "00" + replace industry_orig_2 = "" if mi(empstat_2) + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2 = industry_orig_2 + "00" if !mi(industry_orig_2) + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen byte industrycat10_2 = . + replace industrycat10_2 = 1 if inrange(industry_orig_2, "01", "03") + replace industrycat10_2 = 2 if inrange(industry_orig_2, "05", "09") + replace industrycat10_2 = 3 if inrange(industry_orig_2, "10", "33") + replace industrycat10_2 = 4 if inrange(industry_orig_2, "35", "39") + replace industrycat10_2 = 5 if inrange(industry_orig_2, "41", "43") + replace industrycat10_2 = 6 if inrange(industry_orig_2, "45", "47") | inrange(industry_orig_2, "55", "56") + replace industrycat10_2 = 7 if inrange(industry_orig_2, "49", "53") | inrange(industry_orig_2, "58", "63") + replace industrycat10_2 = 8 if inrange(industry_orig_2, "64", "82") + replace industrycat10_2 = 9 if inrange(industry_orig_2, "84", "84") + replace industrycat10_2 = 10 if inrange(industry_orig_2, "85", "99") + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2 = industrycat10_2 + recode industrycat4_2 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2 "Broad Economic Activities classification, secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2 = . + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2 = "" + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_2_> + gen byte occup_2 = . + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_occup_skill_2_> + gen occup_skill_2 = . + replace occup_skill_2 = 3 if inrange(occup_2, 1, 3) + replace occup_skill_2 = 2 if inrange(occup_2, 4, 8) + replace occup_skill_2 = 1 if occup_2 == 9 + la de lblskill2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2 lblskill2 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_wage_no_compen_2_> + egen double wage_no_compen_2 = rowtotal(d1_14b d1_16b), missing + replace wage_no_compen_2 = . if mi(empstat_2) | empstat_2 == 2 | wage_no_compen_2 == 0 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2 = 5 + replace unitwage_2 = . if mi(wage_no_compen_2) + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2 = d1_22b + replace whours_2 = . if whours_2 == 0 | mi(empstat_2) + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2 = . + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2 = . + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen firmsize_l_2 = . + replace firmsize_l_2 = 1 if d1_11b == 1 + replace firmsize_l_2 = 6 if d1_11b == 2 + replace firmsize_l_2 = 16 if d1_11b == 3 + replace firmsize_l_2 = 31 if d1_11b == 4 + replace firmsize_l_2 = 50 if d1_11b == 5 + replace firmsize_l_2 = 100 if d1_11b == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_l_2 = 100 if ocusec_2 == 1 & mi(firmsize_l_2) + + replace firmsize_l_2 = . if mi(empstat_2) + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen firmsize_u_2 = . + replace firmsize_u_2 = 5 if d1_11b == 1 + replace firmsize_u_2 = 15 if d1_11b == 2 + replace firmsize_u_2 = 30 if d1_11b == 3 + replace firmsize_u_2 = 49 if d1_11b == 4 + replace firmsize_u_2 = 99 if d1_11b == 5 + replace firmsize_u_2 = 9999 if d1_11b == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_u_2 = 9999 if ocusec_2 == 1 & mi(firmsize_u_2) + + replace firmsize_u_2 = . if mi(empstat_2) + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others = . + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others = . + label var t_wage_nocompen_others "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others = . + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total = . + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total = . + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total = . + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ + +*<_lstatus_year_> + gen byte lstatus_year = . + replace lstatus_year=. if age < minlaborage & age != . + label var lstatus_year "Labor status during last year" + la de lbllstatus_year 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus_year lbllstatus_year +* + +*<_potential_lf_year_> + gen byte potential_lf_year = . + replace potential_lf_year=. if age < minlaborage & age != . + replace potential_lf_year = . if lstatus_year != 3 + label var potential_lf_year "Potential labour force status" + la de lblpotential_lf_year 0 "No" 1 "Yes" + label values potential_lf_year lblpotential_lf_year +* + + +*<_underemployment_year_> + gen byte underemployment_year = . + replace underemployment_year = . if age < minlaborage & age != . + replace underemployment_year = . if lstatus_year == 1 + label var underemployment_year "Underemployment status" + la de lblunderemployment_year 0 "No" 1 "Yes" + label values underemployment_year lblunderemployment_year +* + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ + +*<_empstat_year_> + gen byte empstat_year = . + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + +*<_ocusec_year_> + gen byte ocusec_year = . + label var ocusec_year "Sector of activity primary job 12 month recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + +*<_industry_orig_year_> + gen industry_orig_year = . + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year = . + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(industrycat_isic_year) + *int_classif_universe, var(industrycat_isic_year) universe(ISIC) + count + *list + *assert `r(N)' == 0 + restore + + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + +*<_industrycat10_year_> + gen byte industrycat10_year = . + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "Broad Economic Activities classification, primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year = . + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen occup_isco_year = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco_year) + *int_classif_universe, var(occup_isco_year) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year = . + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_occup_skill_year_> + gen occup_skill_year = . + replace occup_skill_year = 3 if inrange(occup_year, 1, 3) + replace occup_skill_year = 2 if inrange(occup_year, 4, 8) + replace occup_skill_year = 1 if occup_year == 9 + la de lblskillyear 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_year lblskillyear + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_wage_no_compen_year_> --- this var has the same name as other and when quoted in the keep and order codes is repeated. + gen double wage_no_compen_year = . + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year = . + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year = . + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year = . + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year = . + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year = . + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year = . + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year = . + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year = . + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen firmsize_l_year = . + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen firmsize_u_year = . + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year = . + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year = . + label var ocusec_2_year "Sector of activity secondary job 12 month recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year = . + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year = . + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year = . + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "Broad Economic Activities classification, secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year = . + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year = "" + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year = . + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year = . + replace occup_skill_2_year = 3 if inrange(occup_2_year, 1, 3) + replace occup_skill_2_year = 2 if inrange(occup_2_year, 4, 8) + replace occup_skill_2_year = 1 if occup_2_year == 9 + la de lblskilly2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2_year lblskilly2 + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year = . + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year = . + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year = . + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year = . + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year = . + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + +*<_firmsize_l_2_year_> + gen firmsize_l_2_year = . + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen firmsize_u_2_year = . + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year = . + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year = . + label var t_wage_nocompen_others_year "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 12 month recall" +* + +*<_t_wage_others_year_> + gen t_wage_others_year = . + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year = . + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year = . + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year = . + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs = . + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual = . + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc = . + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome = t_wage_total_year + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`out_file'", replace + +* diff --git a/GLD/ARM/ARM_2012_ILCS/ARM_2012_ILCS_V01_M_V01_A_GLD/Programs/ARM_2012_ILCS_V01_M_V01_A_GLD_ALL.do b/GLD/ARM/ARM_2012_ILCS/ARM_2012_ILCS_V01_M_V01_A_GLD/Programs/ARM_2012_ILCS_V01_M_V01_A_GLD_ALL.do new file mode 100644 index 000000000..368a0bdbc --- /dev/null +++ b/GLD/ARM/ARM_2012_ILCS/ARM_2012_ILCS_V01_M_V01_A_GLD/Programs/ARM_2012_ILCS_V01_M_V01_A_GLD_ALL.do @@ -0,0 +1,1818 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +==============================================================================================%%*/ + +/* ----------------------------------------------------------------------- + +<_Program name_> ARM_2012_ILCS_V01_M_V01_A_GLD_ALL.do +<_Application_> Stata 18 <_Application_> +<_Author(s)_> World Bank Jobs Group (gld@worldbank.org) +<_Date created_> 2024-09-11 + +------------------------------------------------------------------------- + +<_Country_> Armenia +<_Survey Title_> Integrated Living Conditions Survey +<_Survey Year_> 2012 +<_Study ID_> https://microdatalib.worldbank.org/index.php/catalog/2615 +<_Data collection from_> [MM/YYYY] +<_Data collection to_> [MM/YYYY] +<_Source of dataset_> [Source of data, e.g. NSO] +<_Sample size (HH)_> [#] +<_Sample size (IND)_> [#] +<_Sampling method_> [Brief description] +<_Geographic coverage_> [To what level is data significant] +<_Currency_> [Currency used for wages] + +----------------------------------------------------------------------- + +<_ICLS Version_> [Version of ICLS for Labor Questions] +<_ISCED Version_> [Version of ICLS for Labor Questions] +<_ISCO Version_> [Version of ICLS for Labor Questions] +<_OCCUP National_> [Version of ICLS for Labor Questions] +<_ISIC Version_> [Version of ICLS for Labor Questions] +<_INDUS National_> [Version of ICLS for Labor Questions] + +----------------------------------------------------------------------- +<_Version Control_> + +* Date: [YYYY-MM-DD] - [Description of changes] +* Date: [YYYY-MM-DD] - [Description of changes] + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +==============================================================================================%%*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m +set varabbrev off + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD-Harmonization/529026_MG/Countries" +local country "ARM" +local year "2012" +local survey "ILCS" +local vermast "V01" +local veralt "V01" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + +* Check whether there is a weight file +local has_wf = fileexists("`path_in_stata/weight.dta'") + +* Start with HH +use "`path_in_stata'/hh.dta" + +* If there is a weight file, merge it in +if `has_wf' { + merge 1:1 recno using "`path_in_stata/weight.dta'", assert(match) nogen +} + +* Add member roster +merge 1:m recno using "`path_in_stata'/mem.dta", assert(match) nogen + +* Add employment section +merge 1:1 recno memnum using "`path_in_stata'/d1", assert(match master) nogen + +* Add number labels +numlabel, add force + +/*%%============================================================================================= + 2: Survey & ID +==============================================================================================%%*/ + +{ + +*<_countrycode_> + gen str4 countrycode = "ARM" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname = "ILCS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey = "GLD" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v = "ICLS-13" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version = "" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version = "" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version = "isic_4" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year = 2012 + label var year "Year of survey" +* + + +*<_vermast_> + gen vermast = "`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen veralt = "`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization = "GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year= 2012 + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month = date + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> +/* <_hhid_note> + + Values are 1-5184 running. Would have preferred making it a string with 0001 to 5184, but leave as is since + GMD has it this way. For PID concatenate this with 01-12 but leave as is. + + */ + gen hhid = recno + label var hhid "Household ID" +* + + +*<_pid_> + gen pid = memnum + label var pid "Individual ID" +* + + +*<_weight_> + *gen weight = . + label var weight "Survey sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + gen weight_q = . + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + +/* <_psu_note> + + We have (at the moment) no documentation on 2012. The variable PSU only has 9 distinct values, roughtly equal + (each number is ~2,200). If you look at the start (list in 1/20) you can see it aligns with the households + (where recno's 1 to 9 are equal to psu, then with recno's 10-18 it is 1-9 again and so forth). It further + aligns with the weights (that is, a block of PSUs has a different weight). It thus seems that PSU does not + directly denote the PSU but rather the numbering of the HHs within the PSU (where 9 HHs are interviewed per + PSU). In 2009, when we do have an accurate PSU (and a methodology text to confirm this) they had always 8 HHs + per PSU. It seems most plausible that this is the case. hence we use the ordering to create a PSU + + */ + + * Sort by recno and memnum (as data is in file already, just in case) to have the order of 9 households/block + rename psu PSU + sort recno memnum + + * Generate a new variable to identify PSUs + gen psu = . + + * Initialize the block counter + local psu_counter = 0 + + * Loop through the data to identify the start of each block + forvalues i = 1/`=_N' { + if PSU[`i'] == 1 & (PSU[`i'-1] != 1 | `i' == 1) { + local psu_counter = `psu_counter' + 1 + } + quietly : replace psu = `psu_counter' if _n == `i' + } + + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu = . + label var ssu "Secondary sampling units" +* + + +*<_strata_> + gen strata = recno + label var strata "Strata" +* + + +*<_wave_> + gen wave = . + label var wave "Survey wave" +* + + +*<_panel_> + gen panel = "" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no = . + label var visit_no "Visit number in panel" +* + +} + + +/*%%============================================================================================= + 3: Geography +==============================================================================================%%*/ + +{ + +*<_urban_> + * typev is 0 if Yerevan, 1 if urban (other), rural is 2 + gen byte urban = inrange(typev, 0,1) + replace urban = 0 if typev == 2 + label var urban "Location is urban" + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban +* + + +*<_subnatid1_> +/* <_subnatid1_note> + + The variable is string and country-specific categorical. Numeric entries are coded in string format using the following naming convention: "1 – Hatay". That is, the variable itself is to be string, not a labelled numeric vector. + + Example of entries would be "1 - Alaska", "2 - Arkansas", ... + + */ + gen str subnatid1 = "" + replace subnatid1 = "1 - Yerevan" if marz == 1 + replace subnatid1 = "2 - Aragatsotn" if marz == 2 + replace subnatid1 = "3 - Ararat" if marz == 3 + replace subnatid1 = "4 - Armavir" if marz == 4 + replace subnatid1 = "5 - Gegharkunik" if marz == 5 + replace subnatid1 = "6 - Lori" if marz == 6 + replace subnatid1 = "7 - Kotayk" if marz == 7 + replace subnatid1 = "8 - Shirak" if marz == 8 + replace subnatid1 = "9 - Syunik" if marz == 9 + replace subnatid1 = "10 - Vayoc Dzor" if marz == 10 + replace subnatid1 = "11 - Tavush" if marz == 11 +* + + +*<_subnatid2_> + gen str subnatid2 = "" + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen str subnatid3 = "" + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> +/* <_subnatidsurvey_note> + + Variable denoting lowest administrative info to which the survey is still significat. + See entry in GLD Guidelines (https://github.com/worldbank/gld/blob/main/Support/A%20-%20Guides%20and%20Documentation/GLD_1.0_Guidelines.docx) for more details + + */ + decode urban, generate(helper) + generate subnatidsurvey = string(urban) + " - " + helper + drop helper + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> +/* <_subnatid1_prev_note> + + subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + + */ + gen subnatid1_prev = . + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev = . + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev = . + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code = . + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code = . + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code = . + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + + +/*%%============================================================================================= + 4: Demography +==============================================================================================%%*/ + +{ + +*<_hsize_> + * If keep all + gen hsize = members + /* * If drop absentees + gen helper = 1 + egen hh_abs_no = total(helper), by(recno) + replace hsize = hsize - hh_abs_no + drop helper hh_abs_no + */ + label var hsize "Household size" +* + + + +*<_age_> + * Already in there + *gen age = . + label var age "Individual age" +* + + +*<_male_> + gen male = a1_1 + recode male (2 = 0) + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + gen relationharm = a1_2 + recode relationharm (4 = 3) (6 = 4) (7 = 5) (8 = 6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +* + + +*<_relationcs_> + clonevar relationcs = a1_2 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen byte marital = a1_5 + recode marital (3 = 5) (5 = 3) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all" + label values eye_dsablty dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values hear_dsablty dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values walk_dsablty dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values conc_dsord dsablty + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values slfcre_dsablty dsablty + label var slfcre_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values comm_dsablty dsablty + label var comm_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +==============================================================================================%%*/ + + +{ + +* Migration is not done as it is much more narrowly defined as migrated and returned. Thus anyone who +* migrated from their home town to the capital city would not be included. + + +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + label values migrated_binary lblmigrated_binary + label var migrated_binary "Individual has migrated" +* + + +*<_migrated_years_> + gen migrated_years = . + label var migrated_years "Years since latest migration" +* + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + label de lblmigrated_from_urban 0 "Rural" 1 "Urban" + label values migrated_from_urban lblmigrated_from_urban + label var migrated_from_urban "Migrated from area" +* + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + label de lblmigrated_from_cat 1 "From same admin3 area" 2 "From same admin2 area" 3 "From same admin1 area" 4 "From other admin1 area" 5 "From other country" + label values migrated_from_cat lblmigrated_from_cat + label var migrated_from_cat "Category of migration area" +* + + +*<_migrated_from_code_> + gen migrated_from_code = . + *label de lblmigrated_from_code + *label values migrated_from_code lblmigrated_from_code + label var migrated_from_code "Code of migration area as subnatid level of migrated_from_cat" +* + + +*<_migrated_from_country_> + gen migrated_from_country = . + label var migrated_from_country "Code of migration country (ISO 3 Letter Code)" +* + + +*<_migrated_reason_> + gen migrated_reason = . + label de lblmigrated_reason 1 "Family reasons" 2 "Educational reasons" 3 "Employment" 4 "Forced (political reasons, natural disaster, …)" 5 "Other reasons" + label values migrated_reason lblmigrated_reason + label var migrated_reason "Reason for migrating" +* + + +} + + +/*%%============================================================================================= + 6: Education +==============================================================================================%%*/ + + +{ + +*<_ed_mod_age_> + +/* <_ed_mod_age_note> + +Education module is only asked to those XX and older. + + */ + +gen byte ed_mod_age = 6 +label var ed_mod_age "Education module application age" + +* + +*<_school_> + gen byte school = 0 + replace school = 1 if e2_7 == 1 + label var school "Attending school" + la de lblschool 0 "No" 1 "Yes" + label values school lblschool +* + + +*<_literacy_> + gen byte literacy = 1 + replace literacy = 0 if e2_2 == 0 + replace literacy = . if mi(e2_2) + label var literacy "Individual can read & write" + la de lblliteracy 0 "No" 1 "Yes" + label values literacy lblliteracy +* + + +*<_educy_> + * Number of years is a combination of level (e2_2) and years in that course (e2_3) + gen byte educy =. + replace educy = 0 if e2_2 == 0 + replace educy = e2_3 if e2_2 == 1 & inrange(e2_3,0,4) + replace educy = 4 + e2_3 if e2_2 == 2 & inrange(e2_3,0,5) + replace educy = 9 + e2_3 if e2_2 == 3 & inrange(e2_3,0,3) + replace educy = 9 + e2_3 if e2_2 == 4 & inrange(e2_3,0,2) + replace educy = 9 + e2_3 if e2_2 == 5 & inrange(e2_3,0,5) + replace educy = 12 + e2_3 if e2_2 == 6 & inrange(e2_3,0,7) + replace educy = 16 + e2_3 if e2_2 == 7 & inrange(e2_3,0,4) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7 =. + replace educat7 = 1 if e2_2 == 0 + replace educat7 = 2 if e2_2 == 1 & e2_3 < 4 + replace educat7 = 3 if e2_2 == 1 & e2_3 == 4 + replace educat7 = 4 if e2_2 == 2 + replace educat7 = 5 if inrange(e2_2, 3, 4) + replace educat7 = 6 if e2_2 == 5 + replace educat7 = 7 if inrange(e2_2, 6, 7) + label var educat7 "Level of education 1" + la de lbleducat7 1 "No education" 2 "Primary incomplete" 3 "Primary complete" 4 "Secondary incomplete" 5 "Secondary complete" 6 "Higher than secondary but not university" 7 "University incomplete or complete", replace + label values educat7 lbleducat7 +* + + +*<_educat5_> + gen byte educat5 = educat7 + recode educat5 4=3 5=4 6 7=5 + label var educat5 "Level of education 2" + la de lbleducat5 1 "No education" 2 "Primary incomplete" 3 "Primary complete but secondary incomplete" 4 "Secondary complete" 5 "Some tertiary/post-secondary" + label values educat5 lbleducat5 +* + + +*<_educat4_> + gen byte educat4 = educat7 + recode educat4 (2 3 4 = 2) (5=3) (6 7=4) + label var educat4 "Level of education 3" + la de lbleducat4 1 "No education" 2 "Primary" 3 "Secondary" 4 "Post-secondary" + label values educat4 lbleducat4 +* + + +*<_educat_orig_> + clonevar educat_orig = e2_2 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced = . + label var educat_isced "ISCED standardised level of education" +* + + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var "school literacy educy educat7 educat5 educat4 educat_orig educat_isced" + +foreach v of local ed_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < ed_mod_age & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < ed_mod_age & !missing(age) ) + } +} + + +* + + +} + + +/*%%============================================================================================= + 7: Training +==============================================================================================%%*/ + + +{ + +*<_vocational_> + gen vocational = . + label de lblvocational 0 "No" 1 "Yes" + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type = . + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l = . + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u = . + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen str vocational_field_orig = "" + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed = . + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + + +/*%%============================================================================================= + 8: Labour +==============================================================================================%%*/ + + +*<_minlaborage_> + gen byte minlaborage = 15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ + +*<_lstatus_> + + * Logic is either have a job (yes to D1_1a) or returning (D1_2a) + * However the returning is subject to reasons (D1_3a) that are not + * a skip pattern but upon probing of the enumerator + * The below tab shows that some go to main job, others don't + * tab d1_3a d1_4a,m + gen byte lstatus = 1 if !mi(d1_4a) + + * For unemployed we need looking for a job (d2_5) and willing to accept (d2_10) + * Ensured all who looked answer the willing question + count if inrange(d2_5,1,2) & mi(d2_10) + assert `r(N)' == 0 + replace lstatus = 2 if lstatus == . & inrange(d2_5, 1, 2) & d2_10 == 1 + + * Normally, I would set all others to NLF, but given that we have the absentees, assign only to no in d2_5 + replace lstatus = 3 if lstatus == . & d2_5 == 3 + replace lstatus = 3 if lstatus == . & inrange(d2_5, 1, 2) & d2_10 == 2 + + replace lstatus = . if age < minlaborage + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + gen byte potential_lf = 0 + * Either not looking but would accept or looking but would not accept + replace potential_lf = 1 if (d2_5 == 3 & d2_10 == 1) | (inrange(d2_5,1,2) & d2_10 == 2) + replace potential_lf = . if age < minlaborage & age != . + replace potential_lf = . if lstatus != 3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment = 0 + replace underemployment = 1 if d1_24a == 7 + replace underemployment = . if age < minlaborage & age != . + replace underemployment = . if lstatus != 1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=. + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=. + replace unempldur_l = 0 if d2_9 == 1 + replace unempldur_l = 1 if d2_9 == 2 + replace unempldur_l = 4 if d2_9 == 3 + replace unempldur_l = 7 if d2_9 == 4 + replace unempldur_l = 13 if d2_9 == 5 + replace unempldur_l = 25 if d2_9 == 6 + replace unempldur_l = 49 if d2_9 == 7 + replace unempldur_l = . if lstatus != 2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=. + replace unempldur_u = 1 if d2_9 == 1 + replace unempldur_u = 3 if d2_9 == 2 + replace unempldur_u = 6 if d2_9 == 3 + replace unempldur_u = 12 if d2_9 == 4 + replace unempldur_u = 24 if d2_9 == 5 + replace unempldur_u = 48 if d2_9 == 6 + replace unempldur_u = 999 if d2_9 == 7 + replace unempldur_u = . if lstatus != 2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat = d1_7a + recode empstat (2 3 = 1) (4 = 3) (5 6 8 = 4) (7 = 2) + replace empstat = . if lstatus != 1 + label var empstat "Employment status during past week primary job 7 day recall" + la de lblempstat 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat lblempstat +* + + +*<_ocusec_> + gen byte ocusec = d1_9a + recode ocusec (2 = 1) (3/5 = 2) + replace ocusec = . if lstatus != 1 + label var ocusec "Sector of activity primary job 7 day recall" + la de lblocusec 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec lblocusec +* + + +*<_industry_orig_> + gen industry_orig = string(d1_5a, "%02.0f") + replace industry_orig = "" if industry_orig == "." + replace industry_orig = "" if lstatus != 1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic = industry_orig + "00" if !mi(industry_orig) + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + drop if missing(industrycat_isic) + int_classif_universe, var(industrycat_isic) universe(ISIC) + count + list + *assert `r(N)' == 0 + restore + + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen byte industrycat10 = . + replace industrycat10 = 1 if inrange(industry_orig, "01", "03") + replace industrycat10 = 2 if inrange(industry_orig, "05", "09") + replace industrycat10 = 3 if inrange(industry_orig, "10", "33") + replace industrycat10 = 4 if inrange(industry_orig, "35", "39") + replace industrycat10 = 5 if inrange(industry_orig, "41", "43") + replace industrycat10 = 6 if inrange(industry_orig, "45", "47") | inrange(industry_orig, "55", "56") + replace industrycat10 = 7 if inrange(industry_orig, "49", "53") | inrange(industry_orig, "58", "63") + replace industrycat10 = 8 if inrange(industry_orig, "64", "82") + replace industrycat10 = 9 if inrange(industry_orig, "84", "84") + replace industrycat10 = 10 if inrange(industry_orig, "85", "99") + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4 = industrycat10 + recode industrycat4 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4 "Broad Economic Activities classification, primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig = . + label var occup_orig "Original occupation record primary job 7 day recall" +* + + + +*<_occup_isco_> + gen occup_isco = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco) + *int_classif_universe, var(occup_isco) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_> + gen byte occup = . + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_occup_skill_> + gen occup_skill = . + replace occup_skill = 3 if inrange(occup, 1, 3) + replace occup_skill = 2 if inrange(occup, 4, 8) + replace occup_skill = 1 if occup == 9 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_wage_no_compen_> + egen double wage_no_compen = rowtotal(d1_14a d1_16a), missing + replace wage_no_compen = . if lstatus != 1 | empstat == 2 | wage_no_compen == 0 + label var wage_no_compen "Last wage payment primary job 7 day recall" +* + + +*<_unitwage_> + gen byte unitwage = 5 + replace unitwage = . if mi(wage_no_compen) + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours = d1_22a + replace whours = . if whours == 0 | lstatus != 1 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths = . + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> +/* <_wage_total_note> + + Use gross wages when available and net wages only when gross wages are not available. + This is done to make it easy to compare earnings in formal and informal sectors. + + */ + gen wage_total = . + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + gen byte contract = 0 + replace contract = 1 if d1_7a == 1 | d1_7a == 2 + replace contract = . if lstatus != 1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins = . + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec = . + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union = . + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen firmsize_l = . + replace firmsize_l = 1 if d1_11a == 1 + replace firmsize_l = 6 if d1_11a == 2 + replace firmsize_l = 16 if d1_11a == 3 + replace firmsize_l = 31 if d1_11a == 4 + replace firmsize_l = 50 if d1_11a == 5 + replace firmsize_l = 100 if d1_11a == 6 + + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_l = 100 if ocusec == 1 & mi(firmsize_l) + + replace firmsize_l = . if lstatus != 1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen firmsize_u= . + replace firmsize_u = 5 if d1_11a == 1 + replace firmsize_u = 15 if d1_11a == 2 + replace firmsize_u = 30 if d1_11a == 3 + replace firmsize_u = 49 if d1_11a == 4 + replace firmsize_u = 99 if d1_11a == 5 + replace firmsize_u = 9999 if d1_11a == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_u = 9999 if ocusec == 1 & mi(firmsize_u) + + replace firmsize_u = . if lstatus != 1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + + +{ +*<_empstat_2_> + gen byte empstat_2 = d1_7b + recode empstat_2 (2 3 = 1) (4 = 3) (5 6 8 = 4) (7 = 2) (0 = .) + label var empstat_2 "Employment status during past week secondary job 7 day recall" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2 = d1_9b + recode ocusec_2 (2 = 1) (3/5 = 2) (0 = .) + replace ocusec_2 = . if mi(empstat_2) + label var ocusec_2 "Sector of activity secondary job 7 day recall" + label values ocusec_2 lblocusec +* + + +*<_industry_orig_2_> + gen industry_orig_2 = string(d1_5b, "%02.0f") + replace industry_orig_2 = "" if industry_orig_2 == "." + replace industry_orig_2 = "" if industry_orig_2 == "00" + replace industry_orig_2 = "" if mi(empstat_2) + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2 = industry_orig_2 + "00" if !mi(industry_orig_2) + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen byte industrycat10_2 = . + replace industrycat10_2 = 1 if inrange(industry_orig_2, "01", "03") + replace industrycat10_2 = 2 if inrange(industry_orig_2, "05", "09") + replace industrycat10_2 = 3 if inrange(industry_orig_2, "10", "33") + replace industrycat10_2 = 4 if inrange(industry_orig_2, "35", "39") + replace industrycat10_2 = 5 if inrange(industry_orig_2, "41", "43") + replace industrycat10_2 = 6 if inrange(industry_orig_2, "45", "47") | inrange(industry_orig_2, "55", "56") + replace industrycat10_2 = 7 if inrange(industry_orig_2, "49", "53") | inrange(industry_orig_2, "58", "63") + replace industrycat10_2 = 8 if inrange(industry_orig_2, "64", "82") + replace industrycat10_2 = 9 if inrange(industry_orig_2, "84", "84") + replace industrycat10_2 = 10 if inrange(industry_orig_2, "85", "99") + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2 = industrycat10_2 + recode industrycat4_2 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2 "Broad Economic Activities classification, secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2 = . + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2 = "" + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_2_> + gen byte occup_2 = . + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_occup_skill_2_> + gen occup_skill_2 = . + replace occup_skill_2 = 3 if inrange(occup_2, 1, 3) + replace occup_skill_2 = 2 if inrange(occup_2, 4, 8) + replace occup_skill_2 = 1 if occup_2 == 9 + la de lblskill2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2 lblskill2 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_wage_no_compen_2_> + egen double wage_no_compen_2 = rowtotal(d1_14b d1_16b), missing + replace wage_no_compen_2 = . if mi(empstat_2) | empstat_2 == 2 | wage_no_compen_2 == 0 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2 = 5 + replace unitwage_2 = . if mi(wage_no_compen_2) + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2 = d1_22b + replace whours_2 = . if whours_2 == 0 | mi(empstat_2) + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2 = . + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2 = . + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen firmsize_l_2 = . + replace firmsize_l_2 = 1 if d1_11b == 1 + replace firmsize_l_2 = 6 if d1_11b == 2 + replace firmsize_l_2 = 16 if d1_11b == 3 + replace firmsize_l_2 = 31 if d1_11b == 4 + replace firmsize_l_2 = 50 if d1_11b == 5 + replace firmsize_l_2 = 100 if d1_11b == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_l_2 = 100 if ocusec_2 == 1 & mi(firmsize_l_2) + + replace firmsize_l_2 = . if mi(empstat_2) + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen firmsize_u_2 = . + replace firmsize_u_2 = 5 if d1_11b == 1 + replace firmsize_u_2 = 15 if d1_11b == 2 + replace firmsize_u_2 = 30 if d1_11b == 3 + replace firmsize_u_2 = 49 if d1_11b == 4 + replace firmsize_u_2 = 99 if d1_11b == 5 + replace firmsize_u_2 = 9999 if d1_11b == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_u_2 = 9999 if ocusec_2 == 1 & mi(firmsize_u_2) + + replace firmsize_u_2 = . if mi(empstat_2) + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others = . + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others = . + label var t_wage_nocompen_others "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others = . + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total = . + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total = . + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total = . + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ + +*<_lstatus_year_> + gen byte lstatus_year = . + replace lstatus_year=. if age < minlaborage & age != . + label var lstatus_year "Labor status during last year" + la de lbllstatus_year 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus_year lbllstatus_year +* + +*<_potential_lf_year_> + gen byte potential_lf_year = . + replace potential_lf_year=. if age < minlaborage & age != . + replace potential_lf_year = . if lstatus_year != 3 + label var potential_lf_year "Potential labour force status" + la de lblpotential_lf_year 0 "No" 1 "Yes" + label values potential_lf_year lblpotential_lf_year +* + + +*<_underemployment_year_> + gen byte underemployment_year = . + replace underemployment_year = . if age < minlaborage & age != . + replace underemployment_year = . if lstatus_year == 1 + label var underemployment_year "Underemployment status" + la de lblunderemployment_year 0 "No" 1 "Yes" + label values underemployment_year lblunderemployment_year +* + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ + +*<_empstat_year_> + gen byte empstat_year = . + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + +*<_ocusec_year_> + gen byte ocusec_year = . + label var ocusec_year "Sector of activity primary job 12 month recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + +*<_industry_orig_year_> + gen industry_orig_year = . + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year = . + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(industrycat_isic_year) + *int_classif_universe, var(industrycat_isic_year) universe(ISIC) + count + *list + *assert `r(N)' == 0 + restore + + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + +*<_industrycat10_year_> + gen byte industrycat10_year = . + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "Broad Economic Activities classification, primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year = . + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen occup_isco_year = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco_year) + *int_classif_universe, var(occup_isco_year) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year = . + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_occup_skill_year_> + gen occup_skill_year = . + replace occup_skill_year = 3 if inrange(occup_year, 1, 3) + replace occup_skill_year = 2 if inrange(occup_year, 4, 8) + replace occup_skill_year = 1 if occup_year == 9 + la de lblskillyear 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_year lblskillyear + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_wage_no_compen_year_> --- this var has the same name as other and when quoted in the keep and order codes is repeated. + gen double wage_no_compen_year = . + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year = . + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year = . + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year = . + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year = . + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year = . + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year = . + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year = . + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year = . + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen firmsize_l_year = . + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen firmsize_u_year = . + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year = . + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year = . + label var ocusec_2_year "Sector of activity secondary job 12 month recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year = . + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year = . + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year = . + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "Broad Economic Activities classification, secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year = . + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year = "" + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year = . + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year = . + replace occup_skill_2_year = 3 if inrange(occup_2_year, 1, 3) + replace occup_skill_2_year = 2 if inrange(occup_2_year, 4, 8) + replace occup_skill_2_year = 1 if occup_2_year == 9 + la de lblskilly2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2_year lblskilly2 + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year = . + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year = . + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year = . + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year = . + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year = . + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + +*<_firmsize_l_2_year_> + gen firmsize_l_2_year = . + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen firmsize_u_2_year = . + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year = . + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year = . + label var t_wage_nocompen_others_year "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 12 month recall" +* + +*<_t_wage_others_year_> + gen t_wage_others_year = . + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year = . + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year = . + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year = . + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs = . + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual = . + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc = . + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome = t_wage_total_year + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`out_file'", replace + +* diff --git a/GLD/ARM/ARM_2013_ILCS/ARM_2013_ILCS_V01_M_V01_A_GLD/Programs/ARM_2013_ILCS_V01_M_V01_A_GLD_ALL.do b/GLD/ARM/ARM_2013_ILCS/ARM_2013_ILCS_V01_M_V01_A_GLD/Programs/ARM_2013_ILCS_V01_M_V01_A_GLD_ALL.do new file mode 100644 index 000000000..152cbc836 --- /dev/null +++ b/GLD/ARM/ARM_2013_ILCS/ARM_2013_ILCS_V01_M_V01_A_GLD/Programs/ARM_2013_ILCS_V01_M_V01_A_GLD_ALL.do @@ -0,0 +1,1904 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +==============================================================================================%%*/ + +/* ----------------------------------------------------------------------- + +<_Program name_> ARM_2013_ILCS_V01_M_V01_A_GLD_ALL.do +<_Application_> Stata 18 <_Application_> +<_Author(s)_> World Bank Jobs Group (gld@worldbank.org) +<_Date created_> 2024-09-11 + +------------------------------------------------------------------------- + +<_Country_> Armenia +<_Survey Title_> Integrated Living Conditions Survey +<_Survey Year_> 2013 +<_Study ID_> https://microdatalib.worldbank.org/index.php/catalog/2615 +<_Data collection from_> [MM/YYYY] +<_Data collection to_> [MM/YYYY] +<_Source of dataset_> [Source of data, e.g. NSO] +<_Sample size (HH)_> [#] +<_Sample size (IND)_> [#] +<_Sampling method_> [Brief description] +<_Geographic coverage_> [To what level is data significant] +<_Currency_> [Currency used for wages] + +----------------------------------------------------------------------- + +<_ICLS Version_> [Version of ICLS for Labor Questions] +<_ISCED Version_> [Version of ICLS for Labor Questions] +<_ISCO Version_> [Version of ICLS for Labor Questions] +<_OCCUP National_> [Version of ICLS for Labor Questions] +<_ISIC Version_> [Version of ICLS for Labor Questions] +<_INDUS National_> [Version of ICLS for Labor Questions] + +----------------------------------------------------------------------- +<_Version Control_> + +* Date: [YYYY-MM-DD] - [Description of changes] +* Date: [YYYY-MM-DD] - [Description of changes] + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +==============================================================================================%%*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m +set varabbrev off + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD-Harmonization/529026_MG/Countries" +local country "ARM" +local year "2013" +local survey "ILCS" +local vermast "V01" +local veralt "V01" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + +* Check whether there is a weight file +local has_wf = fileexists("`path_in_stata/weight.dta'") + +* Start with HH +use "`path_in_stata'/hh.dta" + +* If there is a weight file, merge it in +if `has_wf' { + merge 1:1 recno using "`path_in_stata/weight.dta'", assert(match) nogen +} + +* Add member roster +merge 1:m recno using "`path_in_stata'/mem.dta", assert(match) nogen + +* Add employment section +merge 1:1 recno memnum using "`path_in_stata'/d1", assert(match master) nogen + +* Add number labels +numlabel, add force + +/* + +There is an issue with the data. When merging, there are 1,329 individuals who should have answers to +section d1 (employment section for those aged 15 to 75 - inclusive) but do not merge + +gen miss_emp = inrange(age,15,75) & mi(d1_1a) + +Additionally, there are 229 individuals who answer no to the first question but then have the follow up missing. + +gen wrong_emp = inrange(age,15,75) & mi(d1_2a) & d1_1a == 2 + +Note that these all respond to the unemployment question (d2_1) with "Compulsory military" + +If we make a variable that contains either case + +gen either = miss_emp | wrong_emp + +and compare this to the people who state that they have been missing from the household (a1_7) we get the following + + . tab either a1_7 if inrange(age,15,75),m + + | If during the whole survey month + | some members of the household + | are absent, then + either | 1. .up to 2. 3 mont . | Total + -----------+---------------------------------+---------- + 0 | 1 0 13,500 | 13,501 + 1 | 299 1,252 7 | 1,558 + -----------+---------------------------------+---------- + Total | 300 1,252 13,507 | 15,059 + + . + . + . tab either a1_7 if inrange(age,15,75),m col nofreq + + | If during the whole survey month + | some members of the household + | are absent, then + either | 1. .up to 2. 3 mont . | Total + -----------+---------------------------------+---------- + 0 | 0.33 0.00 99.95 | 89.65 + 1 | 99.67 100.00 0.05 | 10.35 + -----------+---------------------------------+---------- + Total | 100.00 100.00 100.00 | 100.00 + +As can be seen, nearly all cases where employment is missing are the cases where people are declared absent. + +The full dataset contains 19,831 individuals. If the people absent are dropped we get to 18,200. The ILO dataset states +has 18,196 rows (https://webapps.ilo.org/surveyLib/index.php/catalog/6540/data-dictionary/FA_ARM_HILCS_2013_FULL?file_name=ARM_HILCS_2013_FULL - they call is "cases") + +Hence it would seem that they have trimmed these cases. + +However, the population numbers do not align. + +Total population for the full 19,831 is 3,127,434 +Total population accroding to WB Data is 2,901,385 (https://data.worldbank.org/indicator/SP.POP.TOTL?locations=AM) +Total + +ILOSTAT has working age pop 15+ + +The full dataset for 15+ gives us 2,560,389 +The reduced (not absent) 15+ is 2,336,590 +ILOSTAT has (same source claimed) 2,155,400 (https://rshiny.ilo.org/dataexplorer56/?lang=en&id=POP_XWAP_SEX_AGE_GEO_NB_A) + +So despite being very close in the number of observations between non-absent and ILO, the weighted numbers are different. + +The data from the ARMStat site (https://armstat.am/en/?nid=965) is for the LFS series. +A bit confusing but the data from 2008 to 2013 is actually from ILCS so we may compare it + +There they use the concept of "permanent/resident" population which excludes the absentees. +Without them the numbers agree (exxcept for small disagreements between unemployed and NLF) + +Hence drop absentees from data +*/ +*drop if !mi(a1_7) + + +/*%%============================================================================================= + 2: Survey & ID +==============================================================================================%%*/ + +{ + +*<_countrycode_> + gen str4 countrycode = "ARM" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname = "ILCS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey = "GLD" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v = "ICLS-13" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version = "" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version = "" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version = "isic_4" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year = 2013 + label var year "Year of survey" +* + + +*<_vermast_> + gen vermast = "`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen veralt = "`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization = "GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year= 2013 + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month = date + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> +/* <_hhid_note> + + Values are 1-5184 running. Would have preferred making it a string with 0001 to 5184, but leave as is since + GMD has it this way. For PID concatenate this with 01-12 but leave as is. + + */ + gen hhid = recno + label var hhid "Household ID" +* + + +*<_pid_> + gen pid = memnum + label var pid "Individual ID" +* + + +*<_weight_> + *gen weight = weight + label var weight "Survey sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + gen weight_q = . + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + +/* <_psu_note> + + We have (at the moment) no documentation on 2013. The variable PSU only has 9 distinct values, roughtly equal + (each number is ~2,200). If you look at the start (list in 1/20) you can see it aligns with the households + (where recno's 1 to 9 are equal to psu, then with recno's 10-18 it is 1-9 again and so forth). It further + aligns with the weights (that is, a block of PSUs has a different weight). It thus seems that PSU does not + directly denote the PSU but rather the numbering of the HHs within the PSU (where 9 HHs are interviewed per + PSU). In 2009, when we do have an accurate PSU (and a methodology text to confirm this) they had always 8 HHs + per PSU. It seems most plausible that this is the case. hence we use the ordering to create a PSU + + */ + + * Sort by recno and memnum (as data is in file already, just in case) to have the order of 9 households/block + sort recno memnum + + * Generate a new variable to identify PSUs + gen psu = . + + * Initialize the block counter + local psu_counter = 0 + + * Loop through the data to identify the start of each block + forvalues i = 1/`=_N' { + if PSU[`i'] == 1 & (PSU[`i'-1] != 1 | `i' == 1) { + local psu_counter = `psu_counter' + 1 + } + quietly : replace psu = `psu_counter' if _n == `i' + } + + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu = recno + label var ssu "Secondary sampling units" +* + + +*<_strata_> + gen strata = . + label var strata "Strata" +* + + +*<_wave_> + gen wave = . + label var wave "Survey wave" +* + + +*<_panel_> + gen panel = "" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + +* There seems to be visit no info in the questionnaire, but nothing in the data, cannot confirm, leave missing + gen visit_no = . + label var visit_no "Visit number in panel" +* + +} + + +/*%%============================================================================================= + 3: Geography +==============================================================================================%%*/ + +{ + +*<_urban_> + * typev is 0 if Yerevan, 1 if urban (other), rural is 2 + gen byte urban = inrange(typev, 0,1) + replace urban = 0 if typev == 2 + label var urban "Location is urban" + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban +* + + +*<_subnatid1_> +/* <_subnatid1_note> + + The variable is string and country-specific categorical. Numeric entries are coded in string format using the following naming convention: "1 – Hatay". That is, the variable itself is to be string, not a labelled numeric vector. + + Example of entries would be "1 - Alaska", "2 - Arkansas", ... + + */ + gen str subnatid1 = "" + replace subnatid1 = "1 - Yerevan" if marz == 1 + replace subnatid1 = "2 - Aragatsotn" if marz == 2 + replace subnatid1 = "3 - Ararat" if marz == 3 + replace subnatid1 = "4 - Armavir" if marz == 4 + replace subnatid1 = "5 - Gegharkunik" if marz == 5 + replace subnatid1 = "6 - Lori" if marz == 6 + replace subnatid1 = "7 - Kotayk" if marz == 7 + replace subnatid1 = "8 - Shirak" if marz == 8 + replace subnatid1 = "9 - Syunik" if marz == 9 + replace subnatid1 = "10 - Vayoc Dzor" if marz == 10 + replace subnatid1 = "11 - Tavush" if marz == 11 +* + + +*<_subnatid2_> + gen str subnatid2 = "" + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen str subnatid3 = "" + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> +/* <_subnatidsurvey_note> + + Variable denoting lowest administrative info to which the survey is still significat. + See entry in GLD Guidelines (https://github.com/worldbank/gld/blob/main/Support/A%20-%20Guides%20and%20Documentation/GLD_1.0_Guidelines.docx) for more details + + */ + decode urban, generate(helper) + generate subnatidsurvey = string(urban) + " - " + helper + drop helper + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> +/* <_subnatid1_prev_note> + + subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + + */ + gen subnatid1_prev = . + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev = . + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev = . + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code = . + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code = . + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code = . + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + + +/*%%============================================================================================= + 4: Demography +==============================================================================================%%*/ + +{ + +*<_hsize_> + * If keep all + gen hsize = members + /* * If drop absentees + gen helper = 1 + egen hh_abs_no = total(helper), by(recno) + replace hsize = hsize - hh_abs_no + drop helper hh_abs_no + */ + label var hsize "Household size" +* + + +*<_age_> + * Already in there + *gen age = . + label var age "Individual age" +* + + +*<_male_> + gen male = a1_1 + recode male (2 = 0) + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + gen relationharm = a1_2 + recode relationharm (4 = 3) (6 = 4) (7 = 5) (8 = 6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +* + + +*<_relationcs_> + clonevar relationcs = a1_2 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen byte marital = a1_5 + recode marital (3 = 5) (5 = 3) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all" + label values eye_dsablty dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values hear_dsablty dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values walk_dsablty dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values conc_dsord dsablty + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values slfcre_dsablty dsablty + label var slfcre_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty = . + label define dsablty 1 "No – no difficulty" 2 "Yes – some difficulty" 3 "Yes – a lot of difficulty" 4 "Cannot do at all", replace + label values comm_dsablty dsablty + label var comm_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +==============================================================================================%%*/ + + +{ + +* Migration is not done as it is much more narrowly defined as migrated and returned. Thus anyone who +* migrated from their home town to the capital city would not be included. For example, while 31% of the +* population is in Yerevan, only 22% of migrants are. + +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + label values migrated_binary lblmigrated_binary + label var migrated_binary "Individual has migrated" +* + + +*<_migrated_years_> + gen migrated_years = . + label var migrated_years "Years since latest migration" +* + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + label de lblmigrated_from_urban 0 "Rural" 1 "Urban" + label values migrated_from_urban lblmigrated_from_urban + label var migrated_from_urban "Migrated from area" +* + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + label de lblmigrated_from_cat 1 "From same admin3 area" 2 "From same admin2 area" 3 "From same admin1 area" 4 "From other admin1 area" 5 "From other country" + label values migrated_from_cat lblmigrated_from_cat + label var migrated_from_cat "Category of migration area" +* + + +*<_migrated_from_code_> + gen migrated_from_code = . + *label de lblmigrated_from_code + *label values migrated_from_code lblmigrated_from_code + label var migrated_from_code "Code of migration area as subnatid level of migrated_from_cat" +* + + +*<_migrated_from_country_> + gen migrated_from_country = . + label var migrated_from_country "Code of migration country (ISO 3 Letter Code)" +* + + +*<_migrated_reason_> + gen migrated_reason = . + label de lblmigrated_reason 1 "Family reasons" 2 "Educational reasons" 3 "Employment" 4 "Forced (political reasons, natural disaster, …)" 5 "Other reasons" + label values migrated_reason lblmigrated_reason + label var migrated_reason "Reason for migrating" +* + + +} + + +/*%%============================================================================================= + 6: Education +==============================================================================================%%*/ + +* Education looks tricky. There are responses in the HH roster section (a1_9) +* and in a separate education section (e2). They do not agree 100% - odd +* Information about the education system to confirm the data is from +* https://www.aacrao.org/edge/country/armenia and +* https://www.unicef.org/armenia/media/15496/file/Education%20Sector%20Analysis%20for%20Armenia.pdf +* visited in September 2024 + +{ + +*<_ed_mod_age_> + +/* <_ed_mod_age_note> + +Education module is only asked to those XX and older. + + */ + +gen byte ed_mod_age = 6 +label var ed_mod_age "Education module application age" + +* + +*<_school_> + gen byte school = 0 + replace school = 1 if e2_7 == 1 + label var school "Attending school" + la de lblschool 0 "No" 1 "Yes" + label values school lblschool +* + + +*<_literacy_> + gen byte literacy = 1 + replace literacy = 0 if e2_2 == 0 + replace literacy = . if mi(e2_2) + label var literacy "Individual can read & write" + la de lblliteracy 0 "No" 1 "Yes" + label values literacy lblliteracy +* + + +*<_educy_> + * Number of years is a combination of level (e2_2) and years in that course (e2_3) + gen byte educy =. + replace educy = 0 if e2_2 == 0 + replace educy = e2_3 if e2_2 == 1 & inrange(e2_3,0,4) + replace educy = 4 + e2_3 if e2_2 == 2 & inrange(e2_3,0,5) + replace educy = 9 + e2_3 if e2_2 == 3 & inrange(e2_3,0,3) + replace educy = 9 + e2_3 if e2_2 == 4 & inrange(e2_3,0,2) + replace educy = 9 + e2_3 if e2_2 == 5 & inrange(e2_3,0,5) + replace educy = 12 + e2_3 if e2_2 == 6 & inrange(e2_3,0,7) + replace educy = 16 + e2_3 if e2_2 == 7 & inrange(e2_3,0,4) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7 =. + replace educat7 = 1 if e2_2 == 0 + replace educat7 = 2 if e2_2 == 1 & e2_3 < 4 + replace educat7 = 3 if e2_2 == 1 & e2_3 == 4 + replace educat7 = 4 if e2_2 == 2 + replace educat7 = 5 if inrange(e2_2, 3, 4) + replace educat7 = 6 if e2_2 == 5 + replace educat7 = 7 if inrange(e2_2, 6, 7) + label var educat7 "Level of education 1" + la de lbleducat7 1 "No education" 2 "Primary incomplete" 3 "Primary complete" 4 "Secondary incomplete" 5 "Secondary complete" 6 "Higher than secondary but not university" 7 "University incomplete or complete", replace + label values educat7 lbleducat7 +* + + +*<_educat5_> + gen byte educat5 = educat7 + recode educat5 4=3 5=4 6 7=5 + label var educat5 "Level of education 2" + la de lbleducat5 1 "No education" 2 "Primary incomplete" 3 "Primary complete but secondary incomplete" 4 "Secondary complete" 5 "Some tertiary/post-secondary" + label values educat5 lbleducat5 +* + + +*<_educat4_> + gen byte educat4 = educat7 + recode educat4 (2 3 4 = 2) (5=3) (6 7=4) + label var educat4 "Level of education 3" + la de lbleducat4 1 "No education" 2 "Primary" 3 "Secondary" 4 "Post-secondary" + label values educat4 lbleducat4 +* + + +*<_educat_orig_> + clonevar educat_orig = e2_2 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced = . + label var educat_isced "ISCED standardised level of education" +* + + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var "school literacy educy educat7 educat5 educat4 educat_orig educat_isced" + +foreach v of local ed_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < ed_mod_age & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < ed_mod_age & !missing(age) ) + } +} + + +* + + +} + + +/*%%============================================================================================= + 7: Training +==============================================================================================%%*/ + + +{ + +*<_vocational_> + gen vocational = . + label de lblvocational 0 "No" 1 "Yes" + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type = . + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l = . + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u = . + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen str vocational_field_orig = "" + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed = . + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + + +/*%%============================================================================================= + 8: Labour +==============================================================================================%%*/ + + +*<_minlaborage_> + gen byte minlaborage = 15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + + * Logic is either have a job (yes to D1_1a) or returning (D1_2a) + * However the returning is subject to reasons (D1_3a) that are not + * a skip pattern but upon probing of the enumerator + * The below tab shows that some go to main job, others don't + * tab d1_3a d1_4a,m + gen byte lstatus = 1 if !mi(d1_4a) + + * For unemployed we need looking for a job (d2_5) and willing to accept (d2_9) + * Ensured all who looked answer the willing question + count if inrange(d2_5,1,2) & mi(d2_9) + assert `r(N)' == 0 + replace lstatus = 2 if lstatus == . & inrange(d2_5, 1, 2) & d2_9 == 1 + + * Normally, I would set all others to NLF, but given that we have the absentees, assign only to no in d2_5 + replace lstatus = 3 if lstatus == . & d2_5 == 3 + replace lstatus = 3 if lstatus == . & inrange(d2_5, 1, 2) & d2_9 == 2 + + replace lstatus = . if age < minlaborage + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + gen byte potential_lf = 0 + * Either not looking but would accept or looking but would not accept + replace potential_lf = 1 if (d2_5 == 3 & d2_9 == 1) | (inrange(d2_5,1,2) & d2_9 == 2) + replace potential_lf = . if age < minlaborage & age != . + replace potential_lf = . if lstatus != 3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment = 0 + replace underemployment = 1 if d1_24a == 7 + replace underemployment = . if age < minlaborage & age != . + replace underemployment = . if lstatus != 1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason = . + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l = . + replace unempldur_l = 0 if d2_8 == 1 + replace unempldur_l = 3 if d2_8 == 2 + replace unempldur_l = 12 if d2_8 == 3 + replace unempldur_l = 24 if d2_8 == 4 + replace unempldur_l = 48 if d2_8 == 5 + replace unempldur_l = . if lstatus != 2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=. + replace unempldur_u = 3 if d2_8 == 1 + replace unempldur_u = 12 if d2_8 == 2 + replace unempldur_u = 24 if d2_8 == 3 + replace unempldur_u = 48 if d2_8 == 4 + replace unempldur_u = 9999 if d2_8 == 5 + replace unempldur_u = . if lstatus != 2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat = d1_7a + recode empstat (2 = 1) (5 = 4) (6 = 2) + replace empstat = . if lstatus != 1 + label var empstat "Employment status during past week primary job 7 day recall" + la de lblempstat 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat lblempstat +* + + +*<_ocusec_> + gen byte ocusec = d1_9a + recode ocusec (2 = 1) (3/5 = 2) + replace ocusec = . if lstatus != 1 + label var ocusec "Sector of activity primary job 7 day recall" + la de lblocusec 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec lblocusec +* + + +*<_industry_orig_> + gen industry_orig = string(d1_5a, "%02.0f") + replace industry_orig = "" if industry_orig == "." + replace industry_orig = "" if lstatus != 1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic = industry_orig + "00" if !mi(industry_orig) + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + drop if missing(industrycat_isic) + int_classif_universe, var(industrycat_isic) universe(ISIC) + count + list + *assert `r(N)' == 0 + restore + + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen byte industrycat10 = . + replace industrycat10 = 1 if inrange(industry_orig, "01", "03") + replace industrycat10 = 2 if inrange(industry_orig, "05", "09") + replace industrycat10 = 3 if inrange(industry_orig, "10", "33") + replace industrycat10 = 4 if inrange(industry_orig, "35", "39") + replace industrycat10 = 5 if inrange(industry_orig, "41", "43") + replace industrycat10 = 6 if inrange(industry_orig, "45", "47") | inrange(industry_orig, "55", "56") + replace industrycat10 = 7 if inrange(industry_orig, "49", "53") | inrange(industry_orig, "58", "63") + replace industrycat10 = 8 if inrange(industry_orig, "64", "82") + replace industrycat10 = 9 if inrange(industry_orig, "84", "84") + replace industrycat10 = 10 if inrange(industry_orig, "85", "99") + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4 = industrycat10 + recode industrycat4 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4 "Broad Economic Activities classification, primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig = d1_6a + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco) + *int_classif_universe, var(occup_isco) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_> + gen byte occup = d1_6a + recode occup (51 52 = 5) (99 = 10) + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_occup_skill_> + gen occup_skill = . + replace occup_skill = 3 if inrange(occup, 1, 3) + replace occup_skill = 2 if inrange(occup, 4, 8) + replace occup_skill = 1 if occup == 9 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_wage_no_compen_> + egen double wage_no_compen = rowtotal(d1_14a d1_16a), missing + replace wage_no_compen = . if lstatus != 1 | empstat == 2 | wage_no_compen == 0 + label var wage_no_compen "Last wage payment primary job 7 day recall" +* + + +*<_unitwage_> + +/* <_unitwage_note> + Unitwage refers to the unit used to record wage_no_compen, *not* the unit of + general wage payent. For example, PHL LFS asks about wage periodicity, then + asks for basic daily pay. The value of that pay would be wage_no_compen, + while unitwage is code 1 ("Daily") for all, regardless of the periodicity. + */ + + gen byte unitwage = 5 + replace unitwage = . if mi(wage_no_compen) + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours = d1_22a + replace whours = . if whours == 0 | lstatus != 1 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths = . + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> +/* <_wage_total_note> + + Use gross wages when available and net wages only when gross wages are not available. + This is done to make it easy to compare earnings in formal and informal sectors. + + */ + gen wage_total = . + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + gen byte contract = 0 + replace contract = 1 if d1_7a == 1 + replace contract = . if lstatus != 1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins = . + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec = . + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union = . + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen firmsize_l = . + replace firmsize_l = 1 if d1_11a == 1 + replace firmsize_l = 6 if d1_11a == 2 + replace firmsize_l = 16 if d1_11a == 3 + replace firmsize_l = 31 if d1_11a == 4 + replace firmsize_l = 50 if d1_11a == 5 + replace firmsize_l = 100 if d1_11a == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_l = 100 if ocusec == 1 & mi(firmsize_l) + + replace firmsize_l = . if lstatus != 1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen firmsize_u= . + replace firmsize_u = 5 if d1_11a == 1 + replace firmsize_u = 15 if d1_11a == 2 + replace firmsize_u = 30 if d1_11a == 3 + replace firmsize_u = 49 if d1_11a == 4 + replace firmsize_u = 99 if d1_11a == 5 + replace firmsize_u = 9999 if d1_11a == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_u = 9999 if ocusec == 1 & mi(firmsize_u) + + replace firmsize_u = . if lstatus != 1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + + +{ +*<_empstat_2_> + gen byte empstat_2 = d1_7b + recode empstat_2 (2 = 1) (5 = 4) (6 = 2) + label var empstat_2 "Employment status during past week secondary job 7 day recall" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2 = d1_9b + recode ocusec_2 (2 = 1) (3/5 = 2) + replace ocusec_2 = . if mi(empstat_2) + label var ocusec_2 "Sector of activity secondary job 7 day recall" + label values ocusec_2 lblocusec +* + + +*<_industry_orig_2_> + gen industry_orig_2 = string(d1_5b, "%02.0f") + replace industry_orig_2 = "" if industry_orig_2 == "." + replace industry_orig_2 = "" if mi(empstat_2) + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2 = industry_orig_2 + "00" if !mi(industry_orig_2) + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen byte industrycat10_2 = . + replace industrycat10_2 = 1 if inrange(industry_orig_2, "01", "03") + replace industrycat10_2 = 2 if inrange(industry_orig_2, "05", "09") + replace industrycat10_2 = 3 if inrange(industry_orig_2, "10", "33") + replace industrycat10_2 = 4 if inrange(industry_orig_2, "35", "39") + replace industrycat10_2 = 5 if inrange(industry_orig_2, "41", "43") + replace industrycat10_2 = 6 if inrange(industry_orig_2, "45", "47") | inrange(industry_orig_2, "55", "56") + replace industrycat10_2 = 7 if inrange(industry_orig_2, "49", "53") | inrange(industry_orig_2, "58", "63") + replace industrycat10_2 = 8 if inrange(industry_orig_2, "64", "82") + replace industrycat10_2 = 9 if inrange(industry_orig_2, "84", "84") + replace industrycat10_2 = 10 if inrange(industry_orig_2, "85", "99") + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2 = industrycat10_2 + recode industrycat4_2 (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2 "Broad Economic Activities classification, secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2 = d1_6b + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2 = "" + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_2_> + gen byte occup_2 = d1_6b + recode occup_2 (51 52 = 5) (99 = 10) + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_occup_skill_2_> + gen occup_skill_2 = . + replace occup_skill_2 = 3 if inrange(occup_2, 1, 3) + replace occup_skill_2 = 2 if inrange(occup_2, 4, 8) + replace occup_skill_2 = 1 if occup_2 == 9 + la de lblskill2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2 lblskill2 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_wage_no_compen_2_> + egen double wage_no_compen_2 = rowtotal(d1_14b d1_16b), missing + replace wage_no_compen_2 = . if mi(empstat_2) | empstat_2 == 2 | wage_no_compen_2 == 0 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2 = 5 + replace unitwage_2 = . if mi(wage_no_compen_2) + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2 = d1_22b + replace whours_2 = . if whours_2 == 0 | mi(empstat_2) + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2 = . + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2 = . + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen firmsize_l_2 = . + replace firmsize_l_2 = 1 if d1_11b == 1 + replace firmsize_l_2 = 6 if d1_11b == 2 + replace firmsize_l_2 = 16 if d1_11b == 3 + replace firmsize_l_2 = 31 if d1_11b == 4 + replace firmsize_l_2 = 50 if d1_11b == 5 + replace firmsize_l_2 = 100 if d1_11b == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_l_2 = 100 if ocusec_2 == 1 & mi(firmsize_l_2) + + replace firmsize_l_2 = . if mi(empstat_2) + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen firmsize_u_2 = . + replace firmsize_u_2 = 5 if d1_11b == 1 + replace firmsize_u_2 = 15 if d1_11b == 2 + replace firmsize_u_2 = 30 if d1_11b == 3 + replace firmsize_u_2 = 49 if d1_11b == 4 + replace firmsize_u_2 = 99 if d1_11b == 5 + replace firmsize_u_2 = 9999 if d1_11b == 6 + + * Add in public sector workers (skip firm size as largest bracket) + replace firmsize_u_2 = 9999 if ocusec_2 == 1 & mi(firmsize_u_2) + + replace firmsize_u_2 = . if mi(empstat_2) + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others = . + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others = . + label var t_wage_nocompen_others "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others = . + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total = . + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total = . + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total = . + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ + +*<_lstatus_year_> + gen byte lstatus_year = . + replace lstatus_year=. if age < minlaborage & age != . + label var lstatus_year "Labor status during last year" + la de lbllstatus_year 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus_year lbllstatus_year +* + +*<_potential_lf_year_> + gen byte potential_lf_year = . + replace potential_lf_year=. if age < minlaborage & age != . + replace potential_lf_year = . if lstatus_year != 3 + label var potential_lf_year "Potential labour force status" + la de lblpotential_lf_year 0 "No" 1 "Yes" + label values potential_lf_year lblpotential_lf_year +* + + +*<_underemployment_year_> + gen byte underemployment_year = . + replace underemployment_year = . if age < minlaborage & age != . + replace underemployment_year = . if lstatus_year == 1 + label var underemployment_year "Underemployment status" + la de lblunderemployment_year 0 "No" 1 "Yes" + label values underemployment_year lblunderemployment_year +* + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ + +*<_empstat_year_> + gen byte empstat_year = . + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + +*<_ocusec_year_> + gen byte ocusec_year = . + label var ocusec_year "Sector of activity primary job 12 month recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + +*<_industry_orig_year_> + gen industry_orig_year = . + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year = . + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(industrycat_isic_year) + *int_classif_universe, var(industrycat_isic_year) universe(ISIC) + count + *list + *assert `r(N)' == 0 + restore + + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + +*<_industrycat10_year_> + gen byte industrycat10_year = . + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "Broad Economic Activities classification, primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year = . + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen occup_isco_year = "" + + * Check that no errors --> using our universe check function, count should be 0 (no obs wrong) + * https://github.com/worldbank/gld/tree/main/Support/Z%20-%20GLD%20Ecosystem%20Tools/ISIC%20ISCO%20universe%20check + preserve + *drop if missing(occup_isco_year) + *int_classif_universe, var(occup_isco_year) universe(ISCO) + count + *list + *assert `r(N)' == 0 + restore + + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year = . + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_occup_skill_year_> + gen occup_skill_year = . + replace occup_skill_year = 3 if inrange(occup_year, 1, 3) + replace occup_skill_year = 2 if inrange(occup_year, 4, 8) + replace occup_skill_year = 1 if occup_year == 9 + la de lblskillyear 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_year lblskillyear + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_wage_no_compen_year_> --- this var has the same name as other and when quoted in the keep and order codes is repeated. + gen double wage_no_compen_year = . + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year = . + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year = . + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year = . + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year = . + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year = . + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year = . + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year = . + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year = . + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen firmsize_l_year = . + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen firmsize_u_year = . + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year = . + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year = . + label var ocusec_2_year "Sector of activity secondary job 12 month recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year = . + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year = . + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year = . + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "Broad Economic Activities classification, secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year = . + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year = "" + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year = . + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year = . + replace occup_skill_2_year = 3 if inrange(occup_2_year, 1, 3) + replace occup_skill_2_year = 2 if inrange(occup_2_year, 4, 8) + replace occup_skill_2_year = 1 if occup_2_year == 9 + la de lblskilly2 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill_2_year lblskilly2 + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year = . + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year = . + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year = . + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year = . + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year = . + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + +*<_firmsize_l_2_year_> + gen firmsize_l_2_year = . + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen firmsize_u_2_year = . + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year = . + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year = . + label var t_wage_nocompen_others_year "Annualized wage in all but 1st & 2nd jobs excl. bonuses, etc. 12 month recall" +* + +*<_t_wage_others_year_> + gen t_wage_others_year = . + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year = . + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year = . + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year = . + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs = . + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual = . + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc = . + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome = t_wage_total_year + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`out_file'", replace + +* diff --git a/Support/B - Country Survey Details/ARM/ILCS/1. Introduction to ARM ILCS.md b/Support/B - Country Survey Details/ARM/ILCS/1. Introduction to ARM ILCS.md index fb9c9b366..189117005 100644 --- a/Support/B - Country Survey Details/ARM/ILCS/1. Introduction to ARM ILCS.md +++ b/Support/B - Country Survey Details/ARM/ILCS/1. Introduction to ARM ILCS.md @@ -87,4 +87,28 @@ The only exception are 228 individuals in 2013 who are coded as absent but answe ### Coding of education variables -Text \ No newline at end of file +The Armenian education system has a 4 + 5 + 3 structure where the first four years represent primary, the middle five years general secondary, and the latter three upper secondary. + +Specific to Armenia are the different paths and academic levels of vocational training, some requiring upper secondary education, others available to graduates of general education. + +[This UNESCO website](https://unevoc.unesco.org/home/Dynamic+TVET+Country+Profiles/country=ARM) summarises the (current) education situation in Armenia, including tertiary education. + +The Armenian ICLS questionnaire asks household members in the roster module about education and in the specific education module for people aged 6 and above. The GLD harmonization uses the latter, with the screenshot below showing the relevant questionnaire section. +

+ +![education questions](utilities/education_vars.png) + +The coding of the GLD variable `educat7` uses the following coding logic: + + +| Q2 - Ed level | Q3 - Ed year | GLD Educat 7 | +|-------------------------------------|------------------|---------------------------------------------| +| 0. Illiterate | Any value | 1. No education | +| 1. Primary (1-4 forms) | Under four years | 2. Primary incomplete | +| 1. Primary (1-4 forms) | If four years | 3. Primary complete | +| 2. Basic secondary (5-9 forms) | Any value | 4. Secondary incomplete | +| 3. Advanced secondary (10-12 forms) | Any value | 5. Secondary complete | +| 4. Secondary vocation | Any value | 5. Secondary complete | +| 5. College (vocational) | Any value | 6. Higher than secondary but not university | +| 6. Higher | Any value | 7. University incomplete or complete | +| 7. Post-graduate | Any value | 7. 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