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Explore_RevGSP.Rmd
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Explore_RevGSP.Rmd
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---
title: "Exploring the relationship between GSP and government revenue"
output: html_notebook
editor_options:
chunk_output_type: inline
---
This script explore the relationship between GDP and gov revenue and does exploratory modeling
```{r Packages, message=FALSE, warning=FALSE, include=FALSE, paged.print=FALSE}
library(tidyverse)
library(broom)
library(readxl)
library(magrittr)
library(stringr)
library(forcats)
library(grid)
library(gridExtra)
library(scales)
library(knitr)
# packages for time series modeling
library(astsa) # companion package
library(TSA) # companion package; arimax: flexible transfer function model
library(tseries) #
library(forecast) # Arima
library(MSwM)
library(TTR)
#library(MSBVAR)
# packages for ts
library(zoo)
library(xts)
library(timetk)
library(tidyquant)
library(lubridate)
library(feather)
library(psych) # describe
# check tidyquant, timetk, sweep (broom ), tibbletime
# Intro to zoo cran.r-project.org/web/packages/zoo/vignettes/zoo-quickref.pdf
# sweep: http://www.business-science.io/code-tools/2017/07/09/sweep-0-1-0.html
```
```{r Global settings and tools, include=FALSE}
#**********************************************************************
# Global settings and tools ###
#**********************************************************************
dir_data_raw <- "data_raw/"
dir_data_out <- "data_out/"
# NBER recession periods, post-WWII
recessionPeriods <-
matrix(c(
1953+2/4, 1954+2/4,
1957+3/4, 1958+2/4,
1960+2/4, 1961+1/4,
1969+4/4, 1970+4/4,
1973+4/4, 1975+1/4,
1980+1/4, 1980+3/4,
1981+3/4, 1982+4/4,
1990+3/4, 1991+1/4,
2001+1/4, 2001+4/4,
2007+4/4, 2009+2/4
) , ncol = 2, byrow = T) %>%
as.data.frame() %>%
rename(peak = V1,
trough = V2) %>%
mutate(peak = peak - 1/4,
trough = trough - 1/4)
get_logReturn <- function(x){
if(any(x <= 0, na.rm = TRUE)) stop("Nagative value(s)")
log(x/lag(x))
}
```
```{r Loading data, include=FALSE}
#**********************************************************************
# Loading Data ###
#**********************************************************************
# Loading saved data
load(paste0(dir_data_out, "dataRaw_RevGSP.RData"))
```
# Creating variables
```{r}
df_
```