Add ACA Premium Tax Credit targets from IRS SOI data#508
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Add ACA Premium Tax Credit targets from IRS SOI data#508daphnehanse11 wants to merge 4 commits intomainfrom
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The SOI 22incd.csv file contains PTC count (N85530) and amount (A85530) columns at national, state, and congressional district levels, but they were not being ingested. This adds PTC to the existing IRS conditional strata pipeline so calibration can target PTC dollar amounts by geography. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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We need to think about a custom uprating here to get to 2024. |
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Adds aca_ptc ingestion from IRS SOI data (code 85530) to etl_irs_soi.py and updates DATABASE_GUIDE.md to reflect stratum_group_id 119. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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) * Fix stale calibration targets by deriving time_period from dataset - Remove hardcoded CBO_YEAR and TREASURY_YEAR constants - Add --dataset CLI argument to etl_national_targets.py - Derive time_period from sim.default_calculation_period - Default to HuggingFace production dataset The dataset itself is now the single source of truth for the calibration year, preventing future drift when updating to new base years. Closes #503 Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * Use income_tax_positive for CBO calibration in loss.py The CBO income_tax parameter represents positive-only receipts (refundable credit payments in excess of liability are classified as outlays, not negative receipts). Using income_tax_positive matches this definition. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * Add --dataset argument to all database ETL scripts All ETL scripts now derive their target year from the dataset's default_calculation_period instead of hardcoding years. This ensures all calibration targets stay synchronized when updating to a new base year annually. Updated scripts: - create_initial_strata.py - etl_age.py - etl_irs_soi.py (with configurable --lag for IRS data delay) - etl_medicaid.py - etl_snap.py - etl_state_income_tax.py Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * Add 119th Congress district code support for 2024 ACS data - Update parse_ucgid to recognize both 5001800US (118th) and 5001900US (119th Congress) - Expand Puerto Rico and territory filters to handle both Congress code formats - Update TERRITORY_UCGIDS and NON_VOTING_GEO_IDS with 119th Congress codes This ensures consistent redistricting alignment: 2024 ACS data uses 119th Congress codes natively, and IRS SOI data is converted via the 116th→119th mapping matrix. Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com> * Remove seed-related changes to reduce PR scope Revert deterministic hash-based medicaid/SSI seed logic in cps.py, update Makefile seed to 3526. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * Upgrade policyengine-us to 1.550.1 in uv.lock Needed for income_tax_positive variable used in loss.py. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> * Cherry-pick ACA PTC targets from PR #508 and update changelog Adds aca_ptc ingestion from IRS SOI data (code 85530) to etl_irs_soi.py and updates DATABASE_GUIDE.md to reflect stratum_group_id 119. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * Split local area publish into build+stage and promote phases Prevents silent no-op promotes by detecting when HF commits don't change HEAD. Adds separate promote workflow for manual gate before pushing staging files to production. Also bumps calibration epochs from 200 to 250. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
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Fixes #509
Summary
22incd.csv) which were already present in the raw data but not being loadedaca_ptcto theTARGETSlist inetl_irs_soi.py, creating conditional strata (aca_ptc > 0) with bothtax_unit_countandaca_ptcdollar targets at national, state, and CD levels (stratum_group_id 119)aca_ptcvariable metadata andaca_ptc_recipientsvariable groupaca_ptcto the calibration weight fitting target filterTest plan
make databaseand verify PTC strata are created at all three geographic levelsaca_ptctargets appear in the targets table with reasonable values (national PTC ~$50-60B range)fit_calibration_weights.pyand confirm PTC targets appear in the matrix🤖 Generated with Claude Code