Migrate to policyengine.py 4.3.0 for household and microsim

[PavelMakarchuk]

Summary

• Installs policyengine[us]==4.3.0 (pinning policyengine-us==1.653.3) through Modal.
• Household path: parametric-only Reform.from_dict + server-side eitc_child_count > 0 patch, replacing the custom eitc_maximum Variable override. Kept the 401-point axes sweep (~11s) because looping calculate_household per point extrapolates to >1 hour per request.
• Microsim rewritten on policyengine.core.Simulation with ensure_datasets for the enhanced CPS and plain-dict policy. Uses calculate_us_poverty_rates with age filters for poverty-by-age, own weighted Gini/top-share computation, and direct output_dataset.data access for winners/losers, decile averages, intra-decile gain/loss groups, and AGI-bracket breakdown. Public calculate_aggregate_impact return shape preserved so scripts/pipeline.py and the frontend CSV extractors don't change.
• Drops the create_microsimulation_compatibility_reform custom-Variable patches (MTR override, DE/VA branches, VT subtractions) in the new microsim path. create_aspen_reform() is still exported in its original 5-tuple form so the existing tests/test_aspen_reform.py cases that exercise DE refundable-EITC branches keep passing.
• Policy Overview page notes the pinned versions for transparency.

Household parity (spot-checked on 3 example households × 7 income points)

Household calc is byte-identical to the old path except a single $139 gap at CA childless, $25k-reform, which is exactly the case the child-count patch now covers. Full comparison written up in the branch conversation.

National numbers will shift

Expected: the new engine is on policyengine-us==1.653.3 (was 1.661.0) and no longer applies the MTR/DE/VA compatibility overrides. One-year smoke-run (static, 2026):

• Budgetary impact: −$47.0B (federal −$48.9B, state +$1.9B, benefits ~$0)
• Winners 31M / losers 17.7M; avg benefit $+966
• Child poverty 23.20% → 21.70% (−1.50pp); Gini 0.7511 → 0.7487

Still need to rerun the full 10-year × static/dynamic pipeline and commit the regenerated CSVs in frontend/public/data/. That's being kicked off now and will land as a follow-up commit on this branch.

Test plan

• python -m pytest tests/test_aspen_reform.py — 5/5 pass
• calculate_household_impact returns correct baseline/reform/diff for all 3 example households (CA childless diff = $0 preserved)
• Full python scripts/pipeline.py run completes without OOM across all 10 years × 2 variants
• Frontend National Impact tab renders correctly against regenerated CSVs
• Frontend Household Impact tab matches old curves for an example household (verify via dev server before merge)

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