An interactive guide to how premium tax credits work and what\'s at stake in 2026
', unsafe_allow_html=True)
-
- # Household selector
- st.markdown("### Select an Example Household")
-
- cols = st.columns(len(PRESET_HOUSEHOLDS))
- selected_household = st.session_state.get("selected_household", "tampa_family")
-
- for i, (key, household) in enumerate(PRESET_HOUSEHOLDS.items()):
- with cols[i]:
- is_selected = key == selected_household
- button_type = "primary" if is_selected else "secondary"
- if st.button(
- household["name"],
- key=f"btn_{key}",
- type=button_type,
- use_container_width=True,
- ):
- st.session_state.selected_household = key
- st.rerun()
-
- # Show household info
- household = PRESET_HOUSEHOLDS[selected_household]
- st.markdown(f"""
-
-
{household['name']}
-
{household['description']}
-
-
Key insight: {household['key_insight']}
-
-
- """, unsafe_allow_html=True)
-
- # Load precomputed data for selected household
- data = load_household_data(selected_household)
-
- if data is None:
- st.stop()
-
- # Two-column layout: scrollable text on right, sticky chart on left
- chart_col, text_col = st.columns([3, 2])
-
- # Track current section
- current_section = st.session_state.get("current_section", 0)
-
- with text_col:
- # Progress indicator
- progress_html = '
'
- for i in range(len(SCROLL_SECTIONS)):
- if i < current_section:
- progress_html += ''
- elif i == current_section:
- progress_html += ''
- else:
- progress_html += ''
- progress_html += '
'
- st.markdown(progress_html, unsafe_allow_html=True)
-
- # Navigation buttons
- nav_cols = st.columns([1, 3, 1])
- with nav_cols[0]:
- if current_section > 0:
- if st.button("← Back", use_container_width=True):
- st.session_state.current_section = current_section - 1
- st.rerun()
- with nav_cols[2]:
- if current_section < len(SCROLL_SECTIONS) - 1:
- if st.button("Next →", use_container_width=True, type="primary"):
- st.session_state.current_section = current_section + 1
- st.rerun()
-
- # Current section content
- section = SCROLL_SECTIONS[current_section]
- st.markdown(f"### {section['title']}")
- st.markdown(section['content'])
-
- # Link to calculator on last section
- if section['id'] == 'your_turn':
- st.markdown("---")
- if st.button("🧮 Open the Full Calculator", type="primary", use_container_width=True):
- st.switch_page("pages/calculator.py")
-
- with chart_col:
- # Create and display chart based on current section
- section = SCROLL_SECTIONS[current_section]
- fig = create_chart(data, section['chart_state'], section.get('highlight'))
- st.plotly_chart(fig, use_container_width=True, config={"displayModeBar": False})
-
- # Show key metrics below chart
- if section['chart_state'] in ['ira_reform', 'both_reforms', 'impact']:
- fpl = data['fpl']
-
- # Calculate key values at 400% FPL
- income_arr = np.array(data['income'])
- idx_400fpl = np.argmin(np.abs(income_arr - fpl * 4))
-
- ptc_baseline = data['ptc_baseline'][idx_400fpl]
- ptc_ira = data['ptc_ira'][idx_400fpl]
- ptc_700 = data['ptc_700fpl'][idx_400fpl] if data['ptc_700fpl'] else 0
-
- metric_cols = st.columns(3)
- with metric_cols[0]:
- st.metric(
- "At 400% FPL",
- f"${fpl * 4:,.0f}",
- help="Income at 400% of Federal Poverty Level"
- )
- with metric_cols[1]:
- st.metric(
- "Baseline PTC",
- f"${ptc_baseline:,.0f}",
- help="Premium tax credit under current law"
- )
- with metric_cols[2]:
- reform_value = ptc_ira if section['chart_state'] != 'both_reforms' else max(ptc_ira, ptc_700)
- gain = reform_value - ptc_baseline
- st.metric(
- "With Reform",
- f"${reform_value:,.0f}",
- f"+${gain:,.0f}" if gain > 0 else None,
- )
-
-
-if __name__ == "__main__":
- main()
diff --git a/app_backup.py b/app_backup.py
deleted file mode 100644
index b21bee1..0000000
--- a/app_backup.py
+++ /dev/null
@@ -1,1414 +0,0 @@
-"""
-ACA Premium Tax Credit Calculator
-==================================
-Explore how extending enhanced premium tax credits would affect your household.
-
-This app calculates ACA premium tax credits under two scenarios:
-1. Current law: Enhanced PTCs expire after 2025
-2. Extended: Enhanced PTCs extended to 2026
-
-Uses PolicyEngine US for accurate tax-benefit microsimulation.
-"""
-
-import streamlit as st
-
-try:
- import pandas as pd
- import numpy as np
- import json
- import gc
- from policyengine_us import Simulation
- import plotly.graph_objects as go
- import base64
-
- # Import calculation functions from package
- from aca_calc.calculations.ptc import calculate_ptc
- from aca_calc.calculations.household import build_household_situation
- from aca_calc.calculations.reforms import create_enhanced_ptc_reform, create_700fpl_reform
-
- # Try to import reform capability
- try:
- from policyengine_core.reforms import Reform
-
- REFORM_AVAILABLE = True
- except ImportError:
- REFORM_AVAILABLE = False
-
- st.set_page_config(
- page_title="Enhanced ACA Subsidies Calculator",
- layout="wide",
- initial_sidebar_state="expanded",
- )
-
-except Exception as e:
- st.error(f"Startup Error: {str(e)}")
- st.error("Please report this error with the details above.")
- import traceback
-
- st.code(traceback.format_exc())
- st.stop()
-
-
-# Load PolicyEngine logo
-def get_logo_base64():
- """Load PolicyEngine logo and convert to base64"""
- try:
- with open("blue.png", "rb") as f:
- return base64.b64encode(f.read()).decode()
- except:
- return None
-
-
-# Load counties from PolicyEngine data
-@st.cache_data
-def load_counties():
- try:
- with open("counties.json", "r") as f:
- return json.load(f)
- except:
- return None
-
-
-# PolicyEngine brand colors
-COLORS = {
- "primary": "#2C6496", # Blue for extension/reform
- "secondary": "#39C6C0",
- "green": "#28A745",
- "gray": "#BDBDBD", # Medium light gray for baseline (matches policyengine-app)
- "blue_gradient": ["#D1E5F0", "#92C5DE", "#2166AC", "#053061"],
-}
-
-
-def get_logo_base64():
- """Get base64 encoded PolicyEngine logo"""
- try:
- with open("blue.png", "rb") as f:
- return base64.b64encode(f.read()).decode()
- except:
- return None
-
-
-def add_logo_to_layout():
- """Add PolicyEngine logo to chart layout (matches policyengine-app positioning)"""
- logo_base64 = get_logo_base64()
- if logo_base64:
- return {
- "images": [
- {
- "source": f"data:image/png;base64,{logo_base64}",
- "xref": "paper",
- "yref": "paper",
- "x": 1.01,
- "y": -0.18,
- "sizex": 0.10,
- "sizey": 0.10,
- "xanchor": "right",
- "yanchor": "bottom",
- }
- ]
- }
- return {}
-
-
-def main():
- # Header with PolicyEngine branding
- st.markdown(
- f"""
-
- """,
- unsafe_allow_html=True,
- )
-
- st.title("How would extending enhanced subsidies affect you?")
-
- counties = load_counties()
-
- # Sidebar for household configuration
- with st.sidebar:
- st.header("Reform scenarios")
- st.markdown("Select which reform(s) to compare against baseline:")
-
- show_ira = st.checkbox(
- "IRA Extension",
- value=True,
- help="Extends current enhanced subsidies indefinitely with 8.5% cap and no income limit above 400% FPL"
- )
-
- show_700fpl = st.checkbox(
- "700% FPL Extension (Bipartisan Bill)",
- value=False,
- help="Bipartisan Health Insurance Affordability Act: extends eligibility to 700% FPL with 9.25% cap"
- )
-
- if not show_ira and not show_700fpl:
- st.warning("Please select at least one reform to compare.")
-
- st.markdown("---")
-
- st.header("Household configuration")
-
- married = st.checkbox("Are you married?", value=False)
-
- age_head = st.number_input(
- "How old are you?", min_value=18, max_value=100, value=35
- )
-
- if married:
- age_spouse = st.number_input(
- "How old is your spouse?",
- min_value=18,
- max_value=100,
- value=35,
- )
- else:
- age_spouse = None
-
- num_dependents = st.number_input(
- "How many children or dependents do you have?",
- min_value=0,
- max_value=10,
- value=0,
- )
- dependent_ages = []
-
- if num_dependents > 0:
- st.write("What are their ages?")
- for i in range(num_dependents):
- age_dep = st.number_input(
- f"Child {i+1} age",
- min_value=0,
- max_value=25,
- value=10,
- key=f"dep_{i}",
- )
- dependent_ages.append(age_dep)
-
- states = [
- "AL",
- "AK",
- "AZ",
- "AR",
- "CA",
- "CO",
- "CT",
- "DE",
- "FL",
- "GA",
- "HI",
- "ID",
- "IL",
- "IN",
- "IA",
- "KS",
- "KY",
- "LA",
- "ME",
- "MD",
- "MA",
- "MI",
- "MN",
- "MS",
- "MO",
- "MT",
- "NE",
- "NV",
- "NH",
- "NJ",
- "NM",
- "NY",
- "NC",
- "ND",
- "OH",
- "OK",
- "OR",
- "PA",
- "RI",
- "SC",
- "SD",
- "TN",
- "TX",
- "UT",
- "VT",
- "VA",
- "WA",
- "WV",
- "WI",
- "WY",
- "DC",
- ]
-
- state = st.selectbox(
- "Which state do you live in?", states, index=0
- ) # Default to AL
-
- # County selection - auto-select first alphabetically
- county = None
- if counties and state in counties:
- sorted_counties = sorted(counties[state])
- county = st.selectbox(
- "Which county?",
- sorted_counties,
- index=0,
- help="County used for marketplace calculations",
- )
-
- # ZIP code input - required for LA County
- zip_code = None
- if state == "CA" and county == "Los Angeles County":
- zip_code = st.text_input(
- "What is your ZIP code?",
- max_chars=5,
- help="Los Angeles County has multiple rating areas. ZIP code is required for accurate premium calculations.",
- placeholder="90001",
- )
- if zip_code and (len(zip_code) != 5 or not zip_code.isdigit()):
- st.error("Please enter a valid 5-digit ZIP code")
- zip_code = None
-
- st.markdown("---")
-
- calculate_button = st.button(
- "Analyze premium subsidies",
- type="primary",
- use_container_width=True,
- )
-
- if calculate_button:
- st.session_state.calculate = True
- new_params = {
- "age_head": age_head,
- "age_spouse": age_spouse,
- "dependent_ages": dependent_ages,
- "state": state,
- "county": county,
- "married": married,
- "zip_code": zip_code,
- "show_ira": show_ira,
- "show_700fpl": show_700fpl,
- }
- # Clear cached charts if params changed
- if hasattr(st.session_state, "params") and st.session_state.params != new_params:
- st.session_state.income_range = None
- st.session_state.fig_net_income = None
- st.session_state.fig_mtr = None
- st.session_state.params = new_params
-
- # Main content area
- if not hasattr(st.session_state, "calculate") or not st.session_state.calculate:
- # Show instructional text when first loading
- st.markdown(
- """
- ### Get started
-
- Enter your household information in the sidebar, then click **"Analyze premium subsidies"** to see:
-
- - How premium tax credits vary across income levels for your household
- - The income range where extending enhanced subsidies would benefit you
- - Your specific impact at any income level you choose
-
- **Available reform scenarios:**
- - **IRA Extension**: Continues current enhanced subsidies with 8.5% cap and no income limit
- - **700% FPL Extension**: [Bipartisan Health Insurance Affordability Act](https://punchbowl.news/wp-content/uploads/Bipartisan-Health-Insurance-Affordability-Act-Section-by-Section-copy.pdf) extending eligibility to 700% FPL with 9.25% cap
-
- Select one or both reforms in the sidebar to compare against baseline (current law after IRA expiration).
- """
- )
- else:
- params = st.session_state.params
-
- # Generate charts only if not already in session state (avoid recalculation)
- if not hasattr(st.session_state, "income_range") or st.session_state.income_range is None:
- with st.spinner("Generating analysis..."):
- county_name = params["county"] if params["county"] else None
- zip_code = params.get("zip_code")
-
- (
- fig_comparison,
- fig_delta,
- benefit_info,
- income_range,
- ptc_baseline_range,
- ptc_reform_range,
- ptc_700fpl_range,
- slcsp_2026,
- fpl,
- x_axis_max,
- ) = create_chart(
- params["age_head"],
- params["age_spouse"],
- tuple(params["dependent_ages"]),
- params["state"],
- county_name,
- zip_code,
- show_ira=params.get("show_ira", True),
- show_700fpl=params.get("show_700fpl", False),
- )
-
- # Store arrays and charts in session state for later use
- if income_range is not None:
- st.session_state.income_range = income_range
- st.session_state.ptc_baseline_range = ptc_baseline_range
- st.session_state.ptc_reform_range = ptc_reform_range
- st.session_state.ptc_700fpl_range = ptc_700fpl_range
- st.session_state.slcsp_2026 = slcsp_2026
- st.session_state.fpl = fpl
- st.session_state.benefit_info = benefit_info
- st.session_state.fig_comparison = fig_comparison
- st.session_state.fig_delta = fig_delta
- st.session_state.x_axis_max = x_axis_max
-
- # Show tabs using cached charts
- if hasattr(st.session_state, "fig_delta") and st.session_state.fig_delta is not None:
- tab1, tab2, tab3, tab4, tab5 = st.tabs([
- "Gain from extension",
- "Baseline vs. extension",
- "Net income",
- "Marginal tax rates",
- "Your impact"
- ])
-
- with tab1:
- st.plotly_chart(
- st.session_state.fig_delta,
- use_container_width=True,
- config={"displayModeBar": False},
- key="gain_chart",
- )
-
- with tab2:
- st.plotly_chart(
- st.session_state.fig_comparison,
- use_container_width=True,
- config={"displayModeBar": False},
- key="comparison_chart",
- )
-
- with tab3:
- # Auto-generate net income chart if not cached
- if not hasattr(st.session_state, "fig_net_income") or st.session_state.fig_net_income is None:
- with st.spinner("Calculating net income (this may take a few seconds)..."):
- x_axis_max = st.session_state.get("x_axis_max", 200000)
- (
- fig_net_income,
- fig_mtr,
- net_income_range,
- net_income_baseline,
- net_income_reform,
- ) = create_net_income_and_mtr_charts(
- params["age_head"],
- params["age_spouse"],
- tuple(params["dependent_ages"]),
- params["state"],
- params.get("county"),
- params.get("zip_code"),
- x_axis_max,
- show_ira=params.get("show_ira", True),
- show_700fpl=params.get("show_700fpl", False),
- )
-
- # Store in session state
- if fig_net_income is not None:
- st.session_state.fig_net_income = fig_net_income
- st.session_state.fig_mtr = fig_mtr
-
- # Display cached chart
- if hasattr(st.session_state, "fig_net_income") and st.session_state.fig_net_income is not None:
- st.plotly_chart(
- st.session_state.fig_net_income,
- use_container_width=True,
- config={"displayModeBar": False},
- key="net_income_chart",
- )
-
- with tab4:
- # Check if chart needs to be generated
- if not hasattr(st.session_state, "fig_mtr") or st.session_state.fig_mtr is None:
- with st.spinner("Calculating marginal tax rates (this may take a few seconds)..."):
- x_axis_max = st.session_state.get("x_axis_max", 200000)
- (
- fig_net_income,
- fig_mtr,
- net_income_range,
- net_income_baseline,
- net_income_reform,
- ) = create_net_income_and_mtr_charts(
- params["age_head"],
- params["age_spouse"],
- tuple(params["dependent_ages"]),
- params["state"],
- params.get("county"),
- params.get("zip_code"),
- x_axis_max,
- show_ira=params.get("show_ira", True),
- show_700fpl=params.get("show_700fpl", False),
- )
-
- # Store in session state
- if fig_mtr is not None:
- st.session_state.fig_net_income = fig_net_income
- st.session_state.fig_mtr = fig_mtr
-
- # Display chart
- if hasattr(st.session_state, "fig_mtr") and st.session_state.fig_mtr is not None:
- st.plotly_chart(
- st.session_state.fig_mtr,
- use_container_width=True,
- config={"displayModeBar": False},
- key="mtr_chart",
- )
-
- with tab5:
- st.markdown("Enter your annual household income to see your specific impact.")
-
- user_income = st.number_input(
- "Annual household income:",
- min_value=0,
- value=0,
- step=1000,
- help="Modified Adjusted Gross Income (MAGI) as defined in 26 USC § 36B(d)(2). Includes: wages, self-employment income, capital gains, interest, dividends, pensions, Social Security, unemployment, rental income, and other income sources. Also includes tax-exempt interest and tax-exempt Social Security.",
- format="%d",
- )
-
- # Interpolate values at user's income (only if income > 0)
- if (
- hasattr(st.session_state, "income_range")
- and user_income is not None
- and user_income > 0
- ):
- ptc_2026_baseline = np.interp(
- user_income,
- st.session_state.income_range,
- st.session_state.ptc_baseline_range,
- )
- ptc_2026_with_ira = np.interp(
- user_income,
- st.session_state.income_range,
- st.session_state.ptc_reform_range,
- )
- difference = ptc_2026_with_ira - ptc_2026_baseline
- slcsp_2026 = st.session_state.slcsp_2026
- fpl = st.session_state.fpl
-
- # Calculate FPL percentage
- household_size = (
- 1
- + (1 if params["age_spouse"] else 0)
- + len(params["dependent_ages"])
- )
- fpl_pct = (user_income / fpl * 100) if fpl > 0 else 0
-
- # Display metrics with custom CSS to prevent truncation
- st.markdown(
- """
-
- """,
- unsafe_allow_html=True,
- )
-
- col_baseline, col_with_ira, col_diff = st.columns(3)
-
- with col_baseline:
- st.metric(
- "Current law",
- f"${ptc_2026_baseline:,.0f} per year",
- help="Your credits under current law (enhanced PTCs expire)",
- )
-
- with col_with_ira:
- st.metric(
- "Enhanced PTCs extended",
- f"${ptc_2026_with_ira:,.0f} per year",
- help="Your credits if enhanced subsidies were extended",
- )
-
- with col_diff:
- if difference > 0:
- st.metric(
- "You gain",
- f"${difference:,.0f} per year",
- f"+${difference/12:,.0f} per month",
- delta_color="normal",
- )
- else:
- st.metric("No change", "$0")
-
- # Details
- with st.expander("See calculation details"):
- st.write(
- f"""
- ### Your household
- - **Size:** {household_size} people
- - **Income:** ${user_income:,} ({fpl_pct:.0f}% of FPL)
- - **2026 Federal Poverty Guideline:** ${fpl:,.0f}
- - **Location:** {params['county'] + ', ' if params['county'] else ''}{params['state']}
- - **Second Lowest Cost Silver Plan:** ${slcsp_2026:,.0f} per year (${slcsp_2026/12:,.0f} per month)
-
- ### How premium tax credits work
-
- **Formula:** PTC = Benchmark Plan Cost - Your Required Contribution
-
- **Your Required Contribution** is a percentage of your income:
- - Lower percentages with IRA extension (2026): 0-8.5% based on income
- - Higher percentages without IRA (2026): 2-9.5% based on income
- - No credits at all above 400% FPL without IRA extension
-
- If the benchmark plan costs less than your required contribution, you get no credit.
- """
- )
-
- # Move "About this calculator" below the tabs
- with st.expander("About this calculator"):
- try:
- from importlib.metadata import version
- pe_version = version("policyengine-us")
- except Exception:
- pe_version = "development"
-
- st.markdown(
- f"""
- The Inflation Reduction Act enhanced ACA subsidies through 2025. This calculator shows how extending these enhancements to 2026 would affect your household's premium tax credits.
-
- This calculator uses [PolicyEngine's open-source tax-benefit microsimulation model](https://github.com/PolicyEngine/policyengine-us) (version {pe_version}).
-
- **2026 premium projections:** This calculator projects Second Lowest Cost Silver Plan (SLCSP) premiums for 2026 by applying a 4.19% increase to actual 2025 benchmark premiums from KFF, based on 2024-25 growth patterns. Actual premiums may rise faster, and we will update the calculator when CMS releases official data in October 2025.
-
- 📖 [Learn more about enhanced premium tax credits](https://policyengine.org/us/research/enhanced-premium-tax-credits-extension)
-
- **Reform scenarios:**
-
- *IRA Extension:*
- - No income cap - households above 400% FPL can still receive credits
- - Lower premium contribution percentages (0-8.5% of income)
- - More generous subsidies at all income levels
-
- *700% FPL Extension ([Bipartisan Health Insurance Affordability Act](https://punchbowl.news/wp-content/uploads/Bipartisan-Health-Insurance-Affordability-Act-Section-by-Section-copy.pdf)):*
- - Eligibility extends to 700% FPL (vs no limit under IRA extension)
- - Contribution percentages: 2-9.25% of income
- - Different phase-out schedule than IRA extension
-
- **Current law (baseline - enhanced PTCs expire):**
- - Hard cap at 400% FPL - no credits above this level (the "subsidy cliff")
- - Higher contribution percentages (2.1-9.96% of income, per IRS Revenue Procedure 2025-25)
- - Less generous subsidies, especially for middle incomes
-
- **Key assumptions:**
- - Households have no employer-sponsored insurance (ESI), making them eligible for Medicaid, CHIP, and premium tax credits
- - Net income and MTR calculations assume standard deduction (set as input to avoid expensive itemization branching)
-
- **Technical note on MTR chart:** The IRS requires MAGI/FPL ratios to be truncated to whole percentages per [Form 8962 instructions](https://www.irs.gov/pub/irs-pdf/i8962.pdf#page=8). This creates ~$10 jumps in PTCs approximately every $100-200 income. The MTR chart applies a $1,000 moving average to smooth over these artifacts while preserving major cliffs (like PTC eligibility thresholds).
- """
- )
-
-
-def create_chart(
- age_head,
- age_spouse,
- dependent_ages,
- state,
- county=None,
- zip_code=None,
- income=None,
- show_ira=True,
- show_700fpl=False,
-):
- """Create income curve charts showing PTC across income range
-
- Args:
- zip_code: 5-digit ZIP code string (required for LA County)
- income: Optional income to mark on chart. If None, no marker shown.
- show_ira: Whether to show IRA extension reform
- show_700fpl: Whether to show 700% FPL extension reform
-
- Returns tuple of (comparison_fig, delta_fig, benefit_info, income_range, ptc_baseline_range, ptc_reform_range, ptc_700fpl_range, slcsp, fpl, x_axis_max)
- Arrays are returned for interpolation
-
- Note: Caching removed to prevent signature mismatch issues on Streamlit Cloud
- """
-
- # Create base household structure for income sweep
- base_household = build_household_situation(
- age_head=age_head,
- age_spouse=age_spouse,
- dependent_ages=list(dependent_ages) if dependent_ages else [],
- state=state,
- county=county,
- zip_code=zip_code,
- year=2026,
- with_axes=True,
- )
-
- # Color for 700% FPL reform
- PURPLE = "#9467BD"
-
- try:
- # Create reforms for chart calculation
- reform_ira = create_enhanced_ptc_reform()
- reform_700fpl = create_700fpl_reform()
-
- # Calculate baseline
- sim_baseline = Simulation(situation=base_household)
-
- income_range = sim_baseline.calculate(
- "employment_income", map_to="household", period=2026
- )
- ptc_range_baseline = sim_baseline.calculate(
- "aca_ptc", map_to="household", period=2026
- )
-
- # Calculate IRA reform if selected
- ptc_range_reform = None
- if show_ira:
- sim_ira = Simulation(situation=base_household, reform=reform_ira)
- ptc_range_reform = sim_ira.calculate(
- "aca_ptc", map_to="household", period=2026
- )
-
- # Calculate 700% FPL reform if selected
- ptc_range_700fpl = None
- if show_700fpl and reform_700fpl is not None:
- sim_700fpl = Simulation(situation=base_household, reform=reform_700fpl)
- ptc_range_700fpl = sim_700fpl.calculate(
- "aca_ptc", map_to="household", period=2026
- )
-
- # Calculate Medicaid and CHIP values
- medicaid_range = sim_baseline.calculate(
- "medicaid_cost", map_to="household", period=2026
- )
- chip_range = sim_baseline.calculate(
- "per_capita_chip", map_to="household", period=2026
- )
-
- # Find where PTC goes to zero for dynamic x-axis range
- max_income_with_ptc = 200000 # Default fallback
- # Check all active reform PTCs
- ptc_arrays_to_check = [ptc_range_baseline]
- if ptc_range_reform is not None:
- ptc_arrays_to_check.append(ptc_range_reform)
- if ptc_range_700fpl is not None:
- ptc_arrays_to_check.append(ptc_range_700fpl)
-
- for ptc_arr in ptc_arrays_to_check:
- for i in range(len(ptc_arr) - 1, -1, -1):
- if ptc_arr[i] > 0:
- max_income_with_ptc = max(max_income_with_ptc, income_range[i])
- break
-
- # Add 10% padding to the range
- x_axis_max = min(1000000, max_income_with_ptc * 1.1)
-
- # Calculate delta (use IRA if available, otherwise 700% FPL)
- if ptc_range_reform is not None:
- delta_range = ptc_range_reform - ptc_range_baseline
- elif ptc_range_700fpl is not None:
- delta_range = ptc_range_700fpl - ptc_range_baseline
- else:
- delta_range = np.zeros_like(ptc_range_baseline)
-
- # Create hover text based on program eligibility
- import numpy as np
-
- hover_text = []
- for i in range(len(income_range)):
- inc = income_range[i]
- ptc_base = ptc_range_baseline[i]
- ptc_ira = ptc_range_reform[i] if ptc_range_reform is not None else 0
- ptc_700 = ptc_range_700fpl[i] if ptc_range_700fpl is not None else 0
- medicaid = medicaid_range[i]
- chip = chip_range[i]
-
- text = f"Income: ${inc:,.0f}
"
-
- # Show all applicable benefits (not mutually exclusive)
- if medicaid > 0:
- text += f"Medicaid: ${medicaid:,.0f}/year "
- if chip > 0:
- text += f"CHIP: ${chip:,.0f}/year "
-
- # Always show PTC information if present
- if ptc_base > 0 or ptc_ira > 0 or ptc_700 > 0:
- text += f"PTC (baseline): ${ptc_base:,.0f}/year "
- if show_ira and ptc_range_reform is not None:
- text += f"PTC (IRA extension): ${ptc_ira:,.0f}/year "
- if show_700fpl and ptc_range_700fpl is not None:
- text += f"PTC (700% FPL): ${ptc_700:,.0f}/year "
-
- hover_text.append(text)
-
- # Create the plot
- fig = go.Figure()
-
- # Build list of arrays to find max for hover trace
- arrays_for_max = [medicaid_range, chip_range, ptc_range_baseline]
- if ptc_range_reform is not None:
- arrays_for_max.append(ptc_range_reform)
- if ptc_range_700fpl is not None:
- arrays_for_max.append(ptc_range_700fpl)
-
- # Add invisible hover trace with unified information
- fig.add_trace(
- go.Scatter(
- x=income_range,
- y=np.maximum.reduce(arrays_for_max),
- mode="lines",
- line=dict(width=0),
- hovertext=hover_text,
- hoverinfo="text",
- showlegend=False,
- name="",
- )
- )
-
- # Add Medicaid line (always show in legend, hidden by default)
- fig.add_trace(
- go.Scatter(
- x=income_range,
- y=medicaid_range,
- mode="lines",
- name="Medicaid",
- line=dict(color=COLORS["green"], width=3),
- hoverinfo="skip",
- visible="legendonly",
- )
- )
-
- # Add CHIP line only if any household member is eligible
- if np.any(chip_range > 0):
- fig.add_trace(
- go.Scatter(
- x=income_range,
- y=chip_range,
- mode="lines",
- name="Children's Health Insurance Program (CHIP)",
- line=dict(color=COLORS["secondary"], width=3),
- hoverinfo="skip",
- visible="legendonly",
- )
- )
-
- # Add baseline line (current law) - show first in legend
- fig.add_trace(
- go.Scatter(
- x=income_range,
- y=ptc_range_baseline,
- mode="lines",
- name="PTC (baseline)",
- line=dict(color=COLORS["gray"], width=3),
- hoverinfo="skip",
- )
- )
-
- # Add IRA extension line if selected
- if show_ira and ptc_range_reform is not None:
- fig.add_trace(
- go.Scatter(
- x=income_range,
- y=ptc_range_reform,
- mode="lines",
- name="PTC (IRA extension)",
- line=dict(color=COLORS["primary"], width=3),
- hoverinfo="skip",
- )
- )
-
- # Add 700% FPL extension line if selected
- if show_700fpl and ptc_range_700fpl is not None:
- fig.add_trace(
- go.Scatter(
- x=income_range,
- y=ptc_range_700fpl,
- mode="lines",
- name="PTC (700% FPL extension)",
- line=dict(color=PURPLE, width=3),
- hoverinfo="skip",
- )
- )
-
- # Add user's position markers (only if income is provided)
- if income is not None and income > 10000:
- # Interpolate PTC values at user's income
- ptc_baseline_user = np.interp(
- income, income_range, ptc_range_baseline
- )
-
- # Add baseline marker
- fig.add_annotation(
- x=income,
- y=ptc_baseline_user,
- text=f"Baseline: ${ptc_baseline_user:,.0f}",
- showarrow=True,
- arrowhead=2,
- arrowsize=1,
- arrowwidth=2,
- arrowcolor=COLORS["gray"],
- ax=60,
- ay=40,
- bgcolor="white",
- bordercolor=COLORS["gray"],
- borderwidth=2,
- )
-
- if show_ira and ptc_range_reform is not None:
- ptc_ira_user = np.interp(income, income_range, ptc_range_reform)
- fig.add_annotation(
- x=income,
- y=ptc_ira_user,
- text=f"IRA: ${ptc_ira_user:,.0f}",
- showarrow=True,
- arrowhead=2,
- arrowsize=1,
- arrowwidth=2,
- arrowcolor=COLORS["primary"],
- ax=60,
- ay=-40,
- bgcolor="white",
- bordercolor=COLORS["primary"],
- borderwidth=2,
- )
-
- if show_700fpl and ptc_range_700fpl is not None:
- ptc_700_user = np.interp(income, income_range, ptc_range_700fpl)
- fig.add_annotation(
- x=income,
- y=ptc_700_user,
- text=f"700% FPL: ${ptc_700_user:,.0f}",
- showarrow=True,
- arrowhead=2,
- arrowsize=1,
- arrowwidth=2,
- arrowcolor=PURPLE,
- ax=-60,
- ay=-40,
- bgcolor="white",
- bordercolor=PURPLE,
- borderwidth=2,
- )
-
- # Update layout for comparison chart
- fig.update_layout(
- title={
- "text": "Healthcare assistance by household income (2026)",
- "font": {"size": 20, "color": COLORS["primary"]},
- },
- xaxis_title="Annual household income",
- yaxis_title="Annual healthcare assistance value",
- height=400,
- xaxis=dict(
- tickformat="$,.0f", range=[0, x_axis_max], automargin=True
- ),
- yaxis=dict(
- tickformat="$,.0f", rangemode="tozero", automargin=True
- ),
- plot_bgcolor="white",
- paper_bgcolor="white",
- font=dict(family="Roboto, sans-serif"),
- legend=dict(
- orientation="h", yanchor="bottom", y=0.98, xanchor="right", x=1
- ),
- margin=dict(l=80, r=40, t=60, b=80),
- **add_logo_to_layout(),
- )
-
- # Create delta chart
- fig_delta = go.Figure()
-
- # Create hover text for delta chart
- delta_hover_text = []
- for i in range(len(income_range)):
- inc = income_range[i]
- delta = delta_range[i]
- ptc_base = ptc_range_baseline[i]
- ptc_ira = ptc_range_reform[i] if ptc_range_reform is not None else 0
- ptc_700 = ptc_range_700fpl[i] if ptc_range_700fpl is not None else 0
- medicaid = medicaid_range[i]
- chip = chip_range[i]
-
- text = f"Income: ${inc:,.0f}
"
-
- # Show all applicable benefits
- if medicaid > 0:
- text += f"Medicaid: ${medicaid:,.0f}/year "
- if chip > 0:
- text += f"CHIP: ${chip:,.0f}/year "
-
- # Show PTC amounts
- text += f"PTC (baseline): ${ptc_base:,.0f}/year "
- if show_ira and ptc_range_reform is not None:
- text += f"PTC (IRA extension): ${ptc_ira:,.0f}/year "
- if show_700fpl and ptc_range_700fpl is not None:
- text += f"PTC (700% FPL): ${ptc_700:,.0f}/year "
-
- delta_hover_text.append(text)
-
- # Add delta lines for each selected reform
- if show_ira and ptc_range_reform is not None:
- delta_ira = ptc_range_reform - ptc_range_baseline
- fig_delta.add_trace(
- go.Scatter(
- x=income_range,
- y=delta_ira,
- mode="lines",
- name="IRA extension gain",
- line=dict(color=COLORS["primary"], width=3),
- fill="tozeroy",
- fillcolor="rgba(44, 100, 150, 0.2)",
- hovertext=delta_hover_text,
- hoverinfo="text",
- )
- )
-
- if show_700fpl and ptc_range_700fpl is not None:
- delta_700 = ptc_range_700fpl - ptc_range_baseline
- fig_delta.add_trace(
- go.Scatter(
- x=income_range,
- y=delta_700,
- mode="lines",
- name="700% FPL extension gain",
- line=dict(color=PURPLE, width=3),
- fill="tozeroy" if not show_ira else None,
- fillcolor="rgba(148, 103, 189, 0.2)" if not show_ira else None,
- hovertext=delta_hover_text,
- hoverinfo="text",
- )
- )
-
- fig_delta.update_layout(
- title={
- "text": "PTC gain from extending enhanced subsidies (2026)",
- "font": {"size": 20, "color": COLORS["primary"]},
- },
- xaxis_title="Annual household income",
- yaxis_title="Annual PTC gain (extended - current law)",
- height=400,
- xaxis=dict(
- tickformat="$,.0f", range=[0, x_axis_max], automargin=True
- ),
- yaxis=dict(
- tickformat="$,.0f", rangemode="tozero", automargin=True
- ),
- plot_bgcolor="white",
- paper_bgcolor="white",
- font=dict(family="Roboto, sans-serif"),
- showlegend=False,
- margin=dict(l=80, r=40, t=60, b=80),
- **add_logo_to_layout(),
- )
-
- # Calculate benefit range information
- benefit_indices = np.where(delta_range > 0)[0]
- if len(benefit_indices) > 0:
- min_benefit_income = income_range[benefit_indices[0]]
- max_benefit_income = income_range[benefit_indices[-1]]
- max_benefit = np.max(delta_range[benefit_indices])
- peak_benefit_index = benefit_indices[np.argmax(delta_range[benefit_indices])]
- peak_benefit_income = income_range[peak_benefit_index]
-
- benefit_info = {
- "min_income": float(min_benefit_income),
- "max_income": float(max_benefit_income),
- "max_benefit": float(max_benefit),
- "peak_income": float(peak_benefit_income),
- }
-
- # Add annotations to delta chart for min/max/peak
- # Min income annotation
- fig_delta.add_annotation(
- x=min_benefit_income,
- y=delta_range[benefit_indices[0]],
- text=f"Benefit starts ${min_benefit_income:,.0f}",
- showarrow=True,
- arrowhead=2,
- arrowsize=1,
- arrowwidth=2,
- arrowcolor=COLORS["primary"],
- ax=-50,
- ay=-50,
- bgcolor=COLORS["primary"],
- bordercolor=COLORS["primary"],
- borderwidth=0,
- borderpad=8,
- font=dict(size=11, color="white"),
- )
-
- # Peak benefit annotation
- fig_delta.add_annotation(
- x=peak_benefit_income,
- y=max_benefit,
- text=f"Max benefit: ${max_benefit:,.0f} at ${peak_benefit_income:,.0f}",
- showarrow=True,
- arrowhead=2,
- arrowsize=1,
- arrowwidth=2,
- arrowcolor=COLORS["primary"],
- ax=0,
- ay=50,
- bgcolor=COLORS["primary"],
- bordercolor=COLORS["primary"],
- borderwidth=0,
- borderpad=8,
- font=dict(size=12, color="white"),
- )
-
- # Max income annotation
- fig_delta.add_annotation(
- x=max_benefit_income,
- y=delta_range[benefit_indices[-1]],
- text=f"Benefit ends ${max_benefit_income:,.0f}",
- showarrow=True,
- arrowhead=2,
- arrowsize=1,
- arrowwidth=2,
- arrowcolor=COLORS["primary"],
- ax=50,
- ay=-50,
- bgcolor=COLORS["primary"],
- bordercolor=COLORS["primary"],
- borderwidth=0,
- borderpad=8,
- font=dict(size=11, color="white"),
- )
- else:
- benefit_info = None
-
- # Get SLCSP and FPL for display
- # SLCSP and FPL don't vary with income, but get from middle of array to avoid edge cases
- slcsp_array = sim_baseline.calculate("slcsp", map_to="household", period=2026)
- fpl_array = sim_baseline.calculate("tax_unit_fpg", period=2026)
-
- # Use max value for SLCSP (should be constant, but this handles any edge cases)
- slcsp = float(np.max(slcsp_array))
- fpl = float(fpl_array[len(fpl_array) // 2]) # Use middle value
-
- return (
- fig,
- fig_delta,
- benefit_info,
- income_range,
- ptc_range_baseline,
- ptc_range_reform,
- ptc_range_700fpl,
- slcsp,
- fpl,
- x_axis_max,
- )
-
- except Exception as e:
- # If chart generation fails, return None for everything
- st.error(f"Error generating charts: {str(e)}")
- import traceback
-
- st.error(traceback.format_exc())
- return None, None, None, None, None, None, None, 0, 0, 200000
-
-
-def create_net_income_and_mtr_charts(
- age_head,
- age_spouse,
- dependent_ages,
- state,
- county=None,
- zip_code=None,
- x_axis_max=200000,
- show_ira=True,
- show_700fpl=False,
-):
- """Create net income and MTR charts including health benefits
-
- Args:
- x_axis_max: Maximum income for x-axis (from PTC charts)
- show_ira: Whether to show IRA extension reform
- show_700fpl: Whether to show 700% FPL extension reform
-
- Returns tuple of (net_income_fig, mtr_fig, income_range, net_income_baseline, net_income_reform)
- """
-
- # Color for 700% FPL reform
- PURPLE = "#9467BD"
-
- # Create base household structure for income sweep
- base_household = build_household_situation(
- age_head=age_head,
- age_spouse=age_spouse,
- dependent_ages=list(dependent_ages) if dependent_ages else [],
- state=state,
- county=county,
- zip_code=zip_code,
- year=2026,
- with_axes=True,
- )
-
- # Set tax_unit_itemizes=False to avoid expensive itemization branching
- # This is an input variable, not a reform, so it doesn't slow down baseline
- base_household["tax_units"]["your tax unit"]["tax_unit_itemizes"] = {2026: False}
-
- try:
- # Create reforms
- reform_ira = create_enhanced_ptc_reform()
- reform_700fpl = create_700fpl_reform()
-
- # Run simulations (itemization already set to False via input)
- sim_baseline = Simulation(situation=base_household)
-
- sim_ira = None
- if show_ira:
- sim_ira = Simulation(situation=base_household, reform=reform_ira)
-
- sim_700fpl = None
- if show_700fpl and reform_700fpl is not None:
- sim_700fpl = Simulation(situation=base_household, reform=reform_700fpl)
-
- income_range = sim_baseline.calculate(
- "employment_income", map_to="household", period=2026
- )
-
- # Calculate net income including health benefits
- net_income_baseline = sim_baseline.calculate(
- "household_net_income_including_health_benefits", map_to="household", period=2026
- )
-
- net_income_ira = None
- if sim_ira is not None:
- net_income_ira = sim_ira.calculate(
- "household_net_income_including_health_benefits", map_to="household", period=2026
- )
-
- net_income_700fpl = None
- if sim_700fpl is not None:
- net_income_700fpl = sim_700fpl.calculate(
- "household_net_income_including_health_benefits", map_to="household", period=2026
- )
-
- # Apply 10-step ($1k) moving average to smooth IRS truncation artifacts
- window = 10
- def moving_average(arr, window_size):
- """Apply simple moving average smoothing."""
- result = np.copy(arr)
- for i in range(len(arr)):
- start = max(0, i - window_size // 2)
- end = min(len(arr), i + window_size // 2 + 1)
- result[i] = np.mean(arr[start:end])
- return result
-
- def calc_mtr(net_income_arr):
- """Calculate MTR from net income array."""
- mtr_raw = np.zeros_like(income_range)
- for i in range(len(income_range) - 1):
- d_income = income_range[i+1] - income_range[i]
- d_net = net_income_arr[i+1] - net_income_arr[i]
- mtr_raw[i] = 1 - d_net / d_income
- mtr_raw[-1] = mtr_raw[-2] if len(income_range) > 1 else 0
- mtr_viz = moving_average(mtr_raw, window)
- return np.clip(mtr_viz, -1.0, 1.5)
-
- mtr_baseline_viz = calc_mtr(net_income_baseline)
- mtr_ira_viz = calc_mtr(net_income_ira) if net_income_ira is not None else None
- mtr_700fpl_viz = calc_mtr(net_income_700fpl) if net_income_700fpl is not None else None
-
- # Create hover text for net income chart
- net_income_hover = []
- for i in range(len(income_range)):
- text = f"Income: ${income_range[i]:,.0f}
"
- text += f"Net income (baseline): ${net_income_baseline[i]:,.0f} "
- if net_income_ira is not None:
- text += f"Net income (IRA extension): ${net_income_ira[i]:,.0f} "
- if net_income_700fpl is not None:
- text += f"Net income (700% FPL): ${net_income_700fpl[i]:,.0f} "
- net_income_hover.append(text)
-
- # Create MTR hover text
- mtr_hover = []
- for i in range(len(income_range)):
- text = f"Income: ${income_range[i]:,.0f}
"
- text += f"MTR (baseline): {mtr_baseline_viz[i]*100:.1f}% "
- if mtr_ira_viz is not None:
- text += f"MTR (IRA extension): {mtr_ira_viz[i]*100:.1f}% "
- if mtr_700fpl_viz is not None:
- text += f"MTR (700% FPL): {mtr_700fpl_viz[i]*100:.1f}% "
- mtr_hover.append(text)
-
- # Create net income chart
- fig_net_income = go.Figure()
-
- fig_net_income.add_trace(
- go.Scatter(
- x=income_range,
- y=net_income_baseline,
- mode="lines",
- name="Baseline",
- line=dict(color=COLORS["gray"], width=3),
- hovertext=net_income_hover,
- hoverinfo="text",
- )
- )
-
- if net_income_ira is not None:
- fig_net_income.add_trace(
- go.Scatter(
- x=income_range,
- y=net_income_ira,
- mode="lines",
- name="IRA extension",
- line=dict(color=COLORS["primary"], width=3),
- hovertext=net_income_hover,
- hoverinfo="text",
- )
- )
-
- if net_income_700fpl is not None:
- fig_net_income.add_trace(
- go.Scatter(
- x=income_range,
- y=net_income_700fpl,
- mode="lines",
- name="700% FPL extension",
- line=dict(color=PURPLE, width=3),
- hovertext=net_income_hover,
- hoverinfo="text",
- )
- )
-
- # Set y-axis range to 1.2x the max value within visible x range
- # Find indices within x_axis_max
- visible_indices = income_range <= x_axis_max
- net_income_arrays = [net_income_baseline[visible_indices]]
- if net_income_ira is not None:
- net_income_arrays.append(net_income_ira[visible_indices])
- if net_income_700fpl is not None:
- net_income_arrays.append(net_income_700fpl[visible_indices])
- net_income_max = max(np.max(arr) for arr in net_income_arrays)
- net_income_y_max = net_income_max * 1.2
-
- fig_net_income.update_layout(
- title={
- "text": "Net income (2026)",
- "font": {"size": 20, "color": COLORS["primary"]},
- },
- xaxis_title="Annual household income",
- yaxis_title="Net income",
- height=400,
- xaxis=dict(
- tickformat="$,.0f", range=[0, x_axis_max], automargin=True
- ),
- yaxis=dict(
- tickformat="$,.0f", range=[0, net_income_y_max], automargin=True
- ),
- plot_bgcolor="white",
- paper_bgcolor="white",
- font=dict(family="Roboto, sans-serif"),
- legend=dict(
- orientation="h", yanchor="bottom", y=0.98, xanchor="right", x=1
- ),
- margin=dict(l=80, r=40, t=60, b=80),
- **add_logo_to_layout(),
- )
-
- # Create MTR chart
- fig_mtr = go.Figure()
-
- fig_mtr.add_trace(
- go.Scatter(
- x=income_range,
- y=mtr_baseline_viz,
- mode="lines",
- name="Baseline",
- line=dict(color=COLORS["gray"], width=3),
- hovertext=mtr_hover,
- hoverinfo="text",
- )
- )
-
- if mtr_ira_viz is not None:
- fig_mtr.add_trace(
- go.Scatter(
- x=income_range,
- y=mtr_ira_viz,
- mode="lines",
- name="IRA extension",
- line=dict(color=COLORS["primary"], width=3),
- hovertext=mtr_hover,
- hoverinfo="text",
- )
- )
-
- if mtr_700fpl_viz is not None:
- fig_mtr.add_trace(
- go.Scatter(
- x=income_range,
- y=mtr_700fpl_viz,
- mode="lines",
- name="700% FPL extension",
- line=dict(color=PURPLE, width=3),
- hovertext=mtr_hover,
- hoverinfo="text",
- )
- )
-
- fig_mtr.update_layout(
- title={
- "text": "Marginal tax rate (2026)",
- "font": {"size": 20, "color": COLORS["primary"]},
- },
- xaxis_title="Annual household income",
- yaxis_title="Marginal tax rate",
- height=400,
- xaxis=dict(
- tickformat="$,.0f", range=[0, x_axis_max], automargin=True
- ),
- yaxis=dict(
- tickformat=".0%", range=[-0.1, 1.0], automargin=True, zeroline=True, zerolinecolor="black", zerolinewidth=2
- ),
- plot_bgcolor="white",
- paper_bgcolor="white",
- font=dict(family="Roboto, sans-serif"),
- legend=dict(
- orientation="h", yanchor="bottom", y=0.98, xanchor="right", x=1
- ),
- margin=dict(l=80, r=40, t=60, b=80),
- **add_logo_to_layout(),
- )
-
- # Clean up memory before returning
- gc.collect()
-
- return (
- fig_net_income,
- fig_mtr,
- income_range,
- net_income_baseline,
- net_income_ira,
- )
-
- except Exception as e:
- st.error(f"Error generating net income/MTR charts: {str(e)}")
- import traceback
- st.error(traceback.format_exc())
- return None, None, None, None, None
-
-
-if __name__ == "__main__":
- main()
diff --git a/eslint.config.mjs b/eslint.config.mjs
index b3456f9..d8b8c7e 100644
--- a/eslint.config.mjs
+++ b/eslint.config.mjs
@@ -26,6 +26,8 @@ export default defineConfig([
},
globalIgnores([
'.next/**',
+ '.venv/**',
+ 'venv/**',
'out/**',
'build/**',
'coverage/**',
diff --git a/package.json b/package.json
index ed87d2b..cee23cb 100644
--- a/package.json
+++ b/package.json
@@ -4,7 +4,7 @@
"version": "0.0.1",
"scripts": {
"dev": "next dev",
- "build": "next build",
+ "build": "next build --webpack",
"start": "next start",
"lint": "eslint ."
},
diff --git a/pages/calculator.py b/pages/calculator.py
deleted file mode 100644
index 1b97d94..0000000
--- a/pages/calculator.py
+++ /dev/null
@@ -1,623 +0,0 @@
-"""
-ACA Premium Tax Credit Calculator Page
-======================================
-Full calculator for exploring ACA premium tax credits.
-"""
-
-import streamlit as st
-import sys
-import os
-
-# Add parent directory to path to import from aca_calc
-sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-
-try:
- import pandas as pd
- import numpy as np
- import json
- import gc
- from policyengine_us import Simulation
- import plotly.graph_objects as go
- import base64
-
- # Import calculation functions from package
- from aca_calc.calculations.ptc import calculate_ptc
- from aca_calc.calculations.household import build_household_situation
- from aca_calc.calculations.reforms import create_enhanced_ptc_reform, create_700fpl_reform
-
- # Try to import reform capability
- try:
- from policyengine_core.reforms import Reform
- REFORM_AVAILABLE = True
- except ImportError:
- REFORM_AVAILABLE = False
-
- st.set_page_config(
- page_title="ACA Calculator",
- page_icon="🧮",
- layout="wide",
- initial_sidebar_state="expanded",
- )
-
-except Exception as e:
- st.error(f"Startup Error: {str(e)}")
- st.error("Please report this error with the details above.")
- import traceback
- st.code(traceback.format_exc())
- st.stop()
-
-
-# PolicyEngine brand colors (app-v2 style)
-COLORS = {
- "primary": "#319795", # Teal
- "secondary": "#2C6496", # Blue for IRA reform
- "purple": "#9467BD", # Purple for 700% FPL
- "gray": "#9CA3AF", # Gray for baseline
- "green": "#22C55E",
-}
-
-
-def get_logo_base64():
- """Get base64 encoded PolicyEngine logo"""
- try:
- logo_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), "blue.png")
- with open(logo_path, "rb") as f:
- return base64.b64encode(f.read()).decode()
- except:
- return None
-
-
-def add_logo_to_layout():
- """Add PolicyEngine logo to chart layout"""
- logo_base64 = get_logo_base64()
- if logo_base64:
- return {
- "images": [
- {
- "source": f"data:image/png;base64,{logo_base64}",
- "xref": "paper",
- "yref": "paper",
- "x": 1.01,
- "y": -0.18,
- "sizex": 0.10,
- "sizey": 0.10,
- "xanchor": "right",
- "yanchor": "bottom",
- }
- ]
- }
- return {}
-
-
-# Load counties
-@st.cache_data
-def load_counties():
- try:
- counties_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), "counties.json")
- with open(counties_path, "r") as f:
- return json.load(f)
- except:
- return None
-
-
-def main():
- # Header styling
- st.markdown(
- f"""
-
- """,
- unsafe_allow_html=True,
- )
-
- st.title("🧮 ACA Premium Tax Credit Calculator")
- st.markdown("Explore how extending enhanced premium tax credits would affect your household.")
-
- # Link back to interactive story
- st.markdown("← [Back to Interactive Guide](/)")
-
- counties = load_counties()
-
- # Sidebar for household configuration
- with st.sidebar:
- st.header("Reform scenarios")
- st.markdown("Select which reform(s) to compare against baseline:")
-
- show_ira = st.checkbox(
- "IRA Extension",
- value=True,
- help="Extends current enhanced subsidies indefinitely with 8.5% cap and no income limit above 400% FPL"
- )
-
- show_700fpl = st.checkbox(
- "700% FPL Extension (Bipartisan Bill)",
- value=False,
- help="Bipartisan Health Insurance Affordability Act: extends eligibility to 700% FPL with 9.25% cap"
- )
-
- if not show_ira and not show_700fpl:
- st.warning("Please select at least one reform to compare.")
-
- st.markdown("---")
-
- st.header("Household configuration")
-
- married = st.checkbox("Are you married?", value=False)
-
- age_head = st.number_input(
- "How old are you?", min_value=18, max_value=100, value=35
- )
-
- if married:
- age_spouse = st.number_input(
- "How old is your spouse?",
- min_value=18,
- max_value=100,
- value=35,
- )
- else:
- age_spouse = None
-
- num_dependents = st.number_input(
- "How many children or dependents do you have?",
- min_value=0,
- max_value=10,
- value=0,
- )
- dependent_ages = []
-
- if num_dependents > 0:
- st.write("What are their ages?")
- for i in range(num_dependents):
- age_dep = st.number_input(
- f"Child {i+1} age",
- min_value=0,
- max_value=25,
- value=10,
- key=f"dep_{i}",
- )
- dependent_ages.append(age_dep)
-
- states = [
- "AL", "AK", "AZ", "AR", "CA", "CO", "CT", "DE", "FL", "GA",
- "HI", "ID", "IL", "IN", "IA", "KS", "KY", "LA", "ME", "MD",
- "MA", "MI", "MN", "MS", "MO", "MT", "NE", "NV", "NH", "NJ",
- "NM", "NY", "NC", "ND", "OH", "OK", "OR", "PA", "RI", "SC",
- "SD", "TN", "TX", "UT", "VT", "VA", "WA", "WV", "WI", "WY", "DC",
- ]
-
- state = st.selectbox("Which state do you live in?", states, index=0)
-
- # County selection
- county = None
- if counties and state in counties:
- sorted_counties = sorted(counties[state])
- county = st.selectbox(
- "Which county?",
- sorted_counties,
- index=0,
- help="County used for marketplace calculations",
- )
-
- # ZIP code for LA County
- zip_code = None
- if state == "CA" and county == "Los Angeles County":
- zip_code = st.text_input(
- "What is your ZIP code?",
- max_chars=5,
- help="Los Angeles County has multiple rating areas.",
- placeholder="90001",
- )
- if zip_code and (len(zip_code) != 5 or not zip_code.isdigit()):
- st.error("Please enter a valid 5-digit ZIP code")
- zip_code = None
-
- st.markdown("---")
-
- calculate_button = st.button(
- "Analyze premium subsidies",
- type="primary",
- use_container_width=True,
- )
-
- if calculate_button:
- st.session_state.calculate = True
- new_params = {
- "age_head": age_head,
- "age_spouse": age_spouse,
- "dependent_ages": dependent_ages,
- "state": state,
- "county": county,
- "married": married,
- "zip_code": zip_code,
- "show_ira": show_ira,
- "show_700fpl": show_700fpl,
- }
- # Clear cached charts if params changed
- if hasattr(st.session_state, "params") and st.session_state.params != new_params:
- st.session_state.income_range = None
- st.session_state.fig_net_income = None
- st.session_state.fig_mtr = None
- st.session_state.params = new_params
-
- # Main content area
- if not hasattr(st.session_state, "calculate") or not st.session_state.calculate:
- st.markdown(
- """
- ### Get started
-
- Enter your household information in the sidebar, then click **"Analyze premium subsidies"** to see:
-
- - How premium tax credits vary across income levels for your household
- - The income range where extending enhanced subsidies would benefit you
- - Your specific impact at any income level you choose
-
- **Available reform scenarios:**
- - **IRA Extension**: Continues current enhanced subsidies with 8.5% cap and no income limit
- - **700% FPL Extension**: [Bipartisan Health Insurance Affordability Act](https://punchbowl.news/wp-content/uploads/Bipartisan-Health-Insurance-Affordability-Act-Section-by-Section-copy.pdf) extending eligibility to 700% FPL with 9.25% cap
-
- Select one or both reforms in the sidebar to compare against baseline (current law after IRA expiration).
- """
- )
- else:
- params = st.session_state.params
-
- # Generate charts
- if not hasattr(st.session_state, "income_range") or st.session_state.income_range is None:
- with st.spinner("Generating analysis..."):
- county_name = params["county"] if params["county"] else None
- zip_code = params.get("zip_code")
-
- (
- fig_comparison,
- fig_delta,
- benefit_info,
- income_range,
- ptc_baseline_range,
- ptc_reform_range,
- ptc_700fpl_range,
- slcsp_2026,
- fpl,
- x_axis_max,
- ) = create_chart(
- params["age_head"],
- params["age_spouse"],
- tuple(params["dependent_ages"]),
- params["state"],
- county_name,
- zip_code,
- show_ira=params.get("show_ira", True),
- show_700fpl=params.get("show_700fpl", False),
- )
-
- if income_range is not None:
- st.session_state.income_range = income_range
- st.session_state.ptc_baseline_range = ptc_baseline_range
- st.session_state.ptc_reform_range = ptc_reform_range
- st.session_state.ptc_700fpl_range = ptc_700fpl_range
- st.session_state.slcsp_2026 = slcsp_2026
- st.session_state.fpl = fpl
- st.session_state.benefit_info = benefit_info
- st.session_state.fig_comparison = fig_comparison
- st.session_state.fig_delta = fig_delta
- st.session_state.x_axis_max = x_axis_max
-
- # Show tabs
- if hasattr(st.session_state, "fig_delta") and st.session_state.fig_delta is not None:
- tab1, tab2, tab3 = st.tabs([
- "Gain from extension",
- "Baseline vs. extension",
- "Your impact"
- ])
-
- with tab1:
- st.plotly_chart(
- st.session_state.fig_delta,
- use_container_width=True,
- config={"displayModeBar": False},
- key="gain_chart",
- )
-
- with tab2:
- st.plotly_chart(
- st.session_state.fig_comparison,
- use_container_width=True,
- config={"displayModeBar": False},
- key="comparison_chart",
- )
-
- with tab3:
- st.markdown("Enter your annual household income to see your specific impact.")
-
- user_income = st.number_input(
- "Annual household income:",
- min_value=0,
- value=0,
- step=1000,
- help="Modified Adjusted Gross Income (MAGI)",
- format="%d",
- )
-
- if (
- hasattr(st.session_state, "income_range")
- and user_income is not None
- and user_income > 0
- ):
- ptc_2026_baseline = np.interp(
- user_income,
- st.session_state.income_range,
- st.session_state.ptc_baseline_range,
- )
- ptc_2026_with_ira = np.interp(
- user_income,
- st.session_state.income_range,
- st.session_state.ptc_reform_range,
- )
- difference = ptc_2026_with_ira - ptc_2026_baseline
- fpl = st.session_state.fpl
-
- # Calculate FPL percentage
- household_size = (
- 1
- + (1 if params["age_spouse"] else 0)
- + len(params["dependent_ages"])
- )
- fpl_pct = (user_income / fpl * 100) if fpl > 0 else 0
-
- col_baseline, col_with_ira, col_diff = st.columns(3)
-
- with col_baseline:
- st.metric(
- "Current law",
- f"${ptc_2026_baseline:,.0f}/year",
- )
-
- with col_with_ira:
- st.metric(
- "With reform",
- f"${ptc_2026_with_ira:,.0f}/year",
- )
-
- with col_diff:
- if difference > 0:
- st.metric(
- "You gain",
- f"${difference:,.0f}/year",
- f"+${difference/12:,.0f}/month",
- )
- else:
- st.metric("No change", "$0")
-
-
-def create_chart(
- age_head,
- age_spouse,
- dependent_ages,
- state,
- county=None,
- zip_code=None,
- income=None,
- show_ira=True,
- show_700fpl=False,
-):
- """Create income curve charts showing PTC across income range"""
-
- base_household = build_household_situation(
- age_head=age_head,
- age_spouse=age_spouse,
- dependent_ages=list(dependent_ages) if dependent_ages else [],
- state=state,
- county=county,
- zip_code=zip_code,
- year=2026,
- with_axes=True,
- )
-
- PURPLE = "#9467BD"
-
- try:
- reform_ira = create_enhanced_ptc_reform()
- reform_700fpl = create_700fpl_reform()
-
- sim_baseline = Simulation(situation=base_household)
-
- income_range = sim_baseline.calculate(
- "employment_income", map_to="household", period=2026
- )
- ptc_range_baseline = sim_baseline.calculate(
- "aca_ptc", map_to="household", period=2026
- )
-
- ptc_range_reform = None
- if show_ira:
- sim_ira = Simulation(situation=base_household, reform=reform_ira)
- ptc_range_reform = sim_ira.calculate(
- "aca_ptc", map_to="household", period=2026
- )
-
- ptc_range_700fpl = None
- if show_700fpl and reform_700fpl is not None:
- sim_700fpl = Simulation(situation=base_household, reform=reform_700fpl)
- ptc_range_700fpl = sim_700fpl.calculate(
- "aca_ptc", map_to="household", period=2026
- )
-
- # Find x-axis range
- max_income_with_ptc = 200000
- ptc_arrays_to_check = [ptc_range_baseline]
- if ptc_range_reform is not None:
- ptc_arrays_to_check.append(ptc_range_reform)
- if ptc_range_700fpl is not None:
- ptc_arrays_to_check.append(ptc_range_700fpl)
-
- for ptc_arr in ptc_arrays_to_check:
- for i in range(len(ptc_arr) - 1, -1, -1):
- if ptc_arr[i] > 0:
- max_income_with_ptc = max(max_income_with_ptc, income_range[i])
- break
-
- x_axis_max = min(1000000, max_income_with_ptc * 1.1)
-
- # Delta
- if ptc_range_reform is not None:
- delta_range = ptc_range_reform - ptc_range_baseline
- elif ptc_range_700fpl is not None:
- delta_range = ptc_range_700fpl - ptc_range_baseline
- else:
- delta_range = np.zeros_like(ptc_range_baseline)
-
- # Create comparison chart
- fig = go.Figure()
-
- fig.add_trace(
- go.Scatter(
- x=income_range,
- y=ptc_range_baseline,
- mode="lines",
- name="PTC (baseline)",
- line=dict(color=COLORS["gray"], width=3),
- )
- )
-
- if show_ira and ptc_range_reform is not None:
- fig.add_trace(
- go.Scatter(
- x=income_range,
- y=ptc_range_reform,
- mode="lines",
- name="PTC (IRA extension)",
- line=dict(color=COLORS["secondary"], width=3),
- )
- )
-
- if show_700fpl and ptc_range_700fpl is not None:
- fig.add_trace(
- go.Scatter(
- x=income_range,
- y=ptc_range_700fpl,
- mode="lines",
- name="PTC (700% FPL extension)",
- line=dict(color=PURPLE, width=3),
- )
- )
-
- fig.update_layout(
- title={
- "text": "Premium Tax Credits by Household Income (2026)",
- "font": {"size": 20, "color": COLORS["primary"]},
- },
- xaxis_title="Annual household income",
- yaxis_title="Annual premium tax credit",
- height=400,
- xaxis=dict(tickformat="$,.0f", range=[0, x_axis_max]),
- yaxis=dict(tickformat="$,.0f", rangemode="tozero"),
- plot_bgcolor="white",
- paper_bgcolor="white",
- font=dict(family="Roboto, sans-serif"),
- legend=dict(orientation="h", yanchor="bottom", y=0.98, xanchor="right", x=1),
- margin=dict(l=80, r=40, t=60, b=80),
- **add_logo_to_layout(),
- )
-
- # Create delta chart
- fig_delta = go.Figure()
-
- if show_ira and ptc_range_reform is not None:
- delta_ira = ptc_range_reform - ptc_range_baseline
- fig_delta.add_trace(
- go.Scatter(
- x=income_range,
- y=delta_ira,
- mode="lines",
- name="IRA extension gain",
- line=dict(color=COLORS["secondary"], width=3),
- fill="tozeroy",
- fillcolor="rgba(44, 100, 150, 0.2)",
- )
- )
-
- if show_700fpl and ptc_range_700fpl is not None:
- delta_700 = ptc_range_700fpl - ptc_range_baseline
- fig_delta.add_trace(
- go.Scatter(
- x=income_range,
- y=delta_700,
- mode="lines",
- name="700% FPL extension gain",
- line=dict(color=PURPLE, width=3),
- fill="tozeroy" if not show_ira else None,
- fillcolor="rgba(148, 103, 189, 0.2)" if not show_ira else None,
- )
- )
-
- fig_delta.update_layout(
- title={
- "text": "PTC Gain from Extending Enhanced Subsidies (2026)",
- "font": {"size": 20, "color": COLORS["primary"]},
- },
- xaxis_title="Annual household income",
- yaxis_title="Annual PTC gain",
- height=400,
- xaxis=dict(tickformat="$,.0f", range=[0, x_axis_max]),
- yaxis=dict(tickformat="$,.0f", rangemode="tozero"),
- plot_bgcolor="white",
- paper_bgcolor="white",
- font=dict(family="Roboto, sans-serif"),
- showlegend=True,
- margin=dict(l=80, r=40, t=60, b=80),
- **add_logo_to_layout(),
- )
-
- # Calculate benefit info
- benefit_indices = np.where(delta_range > 0)[0]
- if len(benefit_indices) > 0:
- benefit_info = {
- "min_income": float(income_range[benefit_indices[0]]),
- "max_income": float(income_range[benefit_indices[-1]]),
- "max_benefit": float(np.max(delta_range[benefit_indices])),
- }
- else:
- benefit_info = None
-
- # Get SLCSP and FPL
- slcsp_array = sim_baseline.calculate("slcsp", map_to="household", period=2026)
- fpl_array = sim_baseline.calculate("tax_unit_fpg", period=2026)
- slcsp = float(np.max(slcsp_array))
- fpl = float(fpl_array[len(fpl_array) // 2])
-
- return (
- fig,
- fig_delta,
- benefit_info,
- income_range,
- ptc_range_baseline,
- ptc_range_reform if ptc_range_reform is not None else np.zeros_like(ptc_range_baseline),
- ptc_range_700fpl,
- slcsp,
- fpl,
- x_axis_max,
- )
-
- except Exception as e:
- st.error(f"Error generating charts: {str(e)}")
- import traceback
- st.error(traceback.format_exc())
- return None, None, None, None, None, None, None, 0, 0, 200000
-
-
-if __name__ == "__main__":
- main()
diff --git a/precompute_households.py b/precompute_households.py
index 7283616..1c6cf40 100644
--- a/precompute_households.py
+++ b/precompute_households.py
@@ -16,7 +16,7 @@
from aca_calc.calculations.household import build_household_situation
from aca_calc.calculations.reforms import create_enhanced_ptc_reform, create_700fpl_reform
-# Preset households (same as in app.py)
+# Preset households used by the React app's household explorer.
PRESET_HOUSEHOLDS = {
"florida_family": {
"name": "Florida Family of 4",
diff --git a/pyproject.toml b/pyproject.toml
index 3ba0cb0..870de1e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -5,7 +5,6 @@ description = "ACA Premium Tax Credit Calculator - Compare 2026 credits with and
readme = "README.md"
requires-python = ">=3.10"
dependencies = [
- "streamlit>=1.28.0",
"policyengine-us>=1.400.0",
"numpy>=1.24.0",
"pandas>=2.0.0",
@@ -26,6 +25,9 @@ build-backend = "setuptools.build_meta"
[tool.setuptools]
py-modules = []
+[tool.setuptools.package-data]
+aca_calc = ["data/*.json"]
+
[tool.setuptools.packages.find]
exclude = ["archive*", "notebooks*", "tests*"]
diff --git a/requirements.txt b/requirements.txt
index f4fa2ac..8ffd74b 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,3 @@
-streamlit
policyengine_us>=1.409.0
numpy
pandas
diff --git a/src/App.css b/src/App.css
index 5f6ba56..6916f55 100644
--- a/src/App.css
+++ b/src/App.css
@@ -44,6 +44,9 @@
}
.page-tab {
+ display: inline-flex;
+ align-items: center;
+ justify-content: center;
padding: 8px 20px;
border: 2px solid var(--pe-border);
border-radius: 24px;
@@ -53,6 +56,7 @@
font-weight: 500;
color: var(--pe-text-secondary);
cursor: pointer;
+ text-decoration: none;
transition: all var(--pe-transition-fast);
}
@@ -180,15 +184,8 @@
/* Calculator page */
.calculator-page {
- width: 100%;
- height: calc(100vh - 140px);
- padding: 0;
-}
-
-.calculator-iframe {
- width: 100%;
- height: 100%;
- border: none;
+ max-width: 100%;
+ padding: var(--pe-space-lg) 0;
}
.back-button {
diff --git a/src/App.jsx b/src/App.jsx
index 5c55943..6dc3243 100644
--- a/src/App.jsx
+++ b/src/App.jsx
@@ -1,16 +1,18 @@
'use client';
-import { useState, useRef } from "react";
+import { useState, useRef, useEffect } from "react";
import HealthBenefitsChart from "./components/HealthBenefitsChart";
import ScrollSection from "./components/ScrollSection";
import CliffComparisonTable from "./components/CliffComparisonTable";
import ContributionScheduleTable from "./components/ContributionScheduleTable";
import ContributionScheduleChart from "./components/ContributionScheduleChart";
import HouseholdExplorer from "./components/HouseholdExplorer";
+import Calculator from "./components/Calculator";
+import LocalImpact from "./views/LocalImpact";
import "./App.css";
// Import precomputed household data
-import cliffDemoData from "../data/households/cliff_demo.json";
+import cliffDemoData from "./data/households/cliff_demo.json";
// Scroll sections content - background first, then household example, then health programs, then reforms
const SECTIONS = [
@@ -165,11 +167,71 @@ Click below to explore how four different households are affected—with details
},
];
+const PAGE_ROUTES = {
+ "": "main",
+ "overview": "main",
+ "households": "households",
+ "calculator": "calculator",
+ "local-impact": "local",
+ "local": "local",
+};
+
+const ROUTE_PAGES = {
+ main: "",
+ households: "households",
+ calculator: "calculator",
+ local: "local-impact",
+};
+
+function getPageFromHash() {
+ if (typeof window === "undefined") {
+ return "main";
+ }
+ const hash = window.location.hash.slice(1);
+ const [route] = hash.split("?");
+ return PAGE_ROUTES[route] || "main";
+}
+
+function isEmbedded() {
+ if (typeof window === "undefined") {
+ return false;
+ }
+ const urlParams = new URLSearchParams(window.location.search);
+ return urlParams.get("embedded") === "true";
+}
+
function App() {
const [activeSection, setActiveSection] = useState(0);
- const [currentPage, setCurrentPage] = useState("main"); // "main", "households", or "calculator"
+ const [currentPage, setCurrentPage] = useState(() => getPageFromHash());
+ const [embedded] = useState(() => isEmbedded());
const chartRef = useRef(null);
+ useEffect(() => {
+ const handleHashChange = () => {
+ setCurrentPage(getPageFromHash());
+ };
+
+ window.addEventListener("hashchange", handleHashChange);
+ return () => window.removeEventListener("hashchange", handleHashChange);
+ }, []);
+
+ const navigateToPage = (page) => {
+ const route = ROUTE_PAGES[page];
+ const currentHash = window.location.hash.slice(1);
+ const [, queryString] = currentHash.split("?");
+
+ if (page === "calculator" && queryString) {
+ window.location.hash = `${route}?${queryString}`;
+ } else {
+ window.location.hash = route;
+ }
+ setCurrentPage(page);
+ };
+
+ useEffect(() => {
+ window.scrollTo(0, 0);
+ }, [currentPage]);
+
// Get current section
const currentSection = SECTIONS[activeSection] || SECTIONS[0];
@@ -230,7 +292,8 @@ function App() {
index={index}
isActive={activeSection === index}
onInView={handleSectionInView}
- onExploreHouseholds={() => setCurrentPage("households")}
+ onExploreHouseholds={() => navigateToPage("households")}
+ onOpenCalculator={() => navigateToPage("calculator")}
/>
))}
@@ -243,7 +306,7 @@ function App() {
@@ -251,39 +314,64 @@ function App() {
);
+ const renderLocalImpactPage = () => ;
+ const renderCalculatorPage = () => (
+
+
+
+ );
+
return (
-
-
-
-
ACA Premium Tax Credits: 2025 vs 2026
-
- Modeling how the scheduled expiration of IRA enhancements affects health insurance costs
-
-
-
-
+
+ {!embedded && (
+
+
+
ACA Premium Tax Credits: 2025 vs 2026
+
+ Modeling how the scheduled expiration of IRA enhancements affects health insurance costs
+
+ {(() => {
+ const hasBaseline = userResults.baseline > 0;
+ const hasIra = userResults.ira > 0;
+ const hasFpl700 = userResults.fpl700 > 0;
+ const fpl = userResults.fplPct.toFixed(0);
+
+ // Check if on Medicaid or CHIP based on actual calculations
+ if (userResults.onMedicaid || userResults.onChip) {
+ const programs = [];
+ if (userResults.onMedicaid) programs.push("Medicaid");
+ if (userResults.onChip) programs.push("CHIP");
+ const programList = programs.join(" and ");
+ return (
+
+ At {fpl}% FPL, your household would be covered by {programList}.
+ Premium tax credits are not available when eligible for these programs.
+
+ );
+ }
+
+ // Below 100% FPL with no Medicaid - coverage gap
+ if (userResults.fplPct < 100 && !hasBaseline && !hasIra && !hasFpl700) {
+ return (
+
+ At {fpl}% FPL, you fall into the coverage gap.
+ Your state has not expanded Medicaid, so adults at this income level don't qualify.
+ Marketplace subsidies are only available starting at 100% FPL,
+ leaving a gap in coverage for those below 100% FPL in non-expansion states.
+
+ );
+ }
+
+ // Above 700% FPL - only IRA could help
+ if (userResults.fplPct > 700) {
+ return (
+
+ At {fpl}% FPL, you are above the 700% FPL threshold.
+ {hasIra
+ ? " The IRA Extension would provide subsidies, but the 700% FPL Bill only extends eligibility to 700% FPL."
+ : " Your required contribution under the IRA Extension (8.5% of income) exceeds the benchmark premium cost, so you would not receive subsidies under either reform option."}
+
+ );
+ }
+
+ // Above 400% FPL but under 700%
+ if (userResults.fplPct > 400) {
+ if (hasIra && hasFpl700) {
+ return (
+
+ At {fpl}% FPL, you are above the 400% FPL cliff but within range of both reform options.
+ Under baseline 2026 law, you would receive no premium tax credits.
+ Both reform options would provide you with subsidies.
+
+ At {fpl}% FPL, you are above the 400% FPL cliff.
+ The IRA Extension would provide subsidies. The 700% FPL Bill would not provide subsidies because
+ your required contribution (9.25% of income) would exceed the benchmark premium cost.
+
+ );
+ } else {
+ return (
+
+ At {fpl}% FPL, you are above the 400% FPL cliff.
+ Your income is high enough that your required contribution would exceed the benchmark premium cost,
+ so neither reform option would provide subsidies at this income level.
+
+ );
+ }
+ }
+
+ // Between 138% and 400% FPL
+ if (hasBaseline) {
+ return (
+
+ At {fpl}% FPL, you are in the marketplace subsidy range.
+ You would receive subsidies under baseline law, but the reform options
+ would increase your credits by lowering your required contribution percentage.
+
+ );
+ } else {
+ return (
+
+ At {fpl}% FPL, you are in the marketplace subsidy range.
+ Your required contribution under baseline law would exceed the benchmark premium cost,
+ so you would not receive subsidies. The reform options lower required contributions and may provide credits.
+
+ );
+ }
+ })()}
+
+
+ )}
+
+ {!userResults && (
+
+
Enter your income above to see how each policy would affect your premium tax credits.
+ {activeDistrictLabel || getStateName(activeState)}
+
+ {activeContext
+ ? formatMetricValue(activeMetricValue, activeMetric)
+ : "No CMS district data"}
+
+
+ {activeContext && activeMetricAvailable
+ ? `${formatNumber(activeContext.marketplace_plan_selections)} plan selections; ${formatNumber(activeContext.aptc_consumers)} receive APTC and ${formatNumber(activeContext.non_aptc_consumers)} do not. Average paid premium is ${formatCurrency(activeContext.average_premium_after_aptc)}/mo.`
+ : unavailableMessage(activeState)}
+
+ {context.fineGrainedCmsAvailable
+ ? "This HealthCare.gov state has CMS county/ZIP PUF detail, but this county is not matched in the compact dataset yet."
+ : "State-based marketplace enrollment detail is reported outside the CMS county/ZIP PUF structure used in this first slice."}
+