Add comprehensive SNAP utility allowance data (FY2019-FY2026, sub-regions, household size)

[MaxGhenis]

Summary

• Add FY2019, FY2023, and FY2026 SNAP utility allowance values for all 53 states/territories
• Split Alaska into 6 SNAP utility sub-regions (Central, Northern, Northwest, Southcentral, Southeast, Southwest) per 7 AAC 45.531, with county-to-region mapping
• Split New York into 3 sub-regions (Nassau/Suffolk, NYC, Other NY) with county mapping
• Add household-size-based SUA and BUA for AZ, TN, VA (NC was already modeled)
• Add HI and GU individual utility allowances (electricity, gas, water) that vary by household size
• Rename participating_states → states parameter files for clarity

Data sourced from USDA SNAP utility allowance spreadsheets and snapscreener.com.

Test plan

• All 257 SNAP tests pass locally
• CI passes

🤖 Generated with Claude Code

[codecov]

Codecov Report

❌ Patch coverage is 85.50725% with 10 lines in your changes missing coverage. Please review.
✅ Project coverage is 94.15%. Comparing base (63a7861) to head (12d5d62).
⚠️ Report is 6 commits behind head on main.

Files with missing lines	Patch %	Lines
..._us/variables/gov/usda/snap/snap_utility_region.py	80.76%	8 Missing and 2 partials ⚠️

Additional details and impacted files

@@             Coverage Diff             @@
##              main    #7726      +/-   ##
===========================================
- Coverage   100.00%   94.15%   -5.85%     
===========================================
  Files            5        4       -1     
  Lines           69      171     +102     
  Branches         2       14      +12     
===========================================
+ Hits            69      161      +92     
- Misses           0        8       +8     
- Partials         0        2       +2     

Flag	Coverage Δ
unittests	94.15% <85.50%> (-5.85%)	⬇️

Flags with carried forward coverage won't be shown. Click here to find out more.

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

[MaxGhenis]

Microsim impact analysis

Ran household-level examples comparing 2024 vs 2026 values — all features working correctly:

SUA examples:

State	2024 SUA	2026 SUA	Change
CA	$7,299	$7,956	+$657 (+9.0%)
NC HH3 (by HH size)	$8,607	$9,216	+$609 (+7.1%)
AK (Southcentral sub-region)	$7,053	$7,092	+$39 (+0.6%)
NY (Other NY sub-region)	$9,933	$10,524	+$591 (+6.0%)

IUA examples:

State	2024 IUA	2026 IUA	Change
HI HH2 (by HH size)	$11,331	$11,608	+$277
AK (Southcentral)	$7,053	$7,132	+$79

Aggregate microsim (Enhanced CPS): Utility expense variables (electricity_expense, gas_expense, etc.) are all zero in the current microdata, so the aggregate SNAP impact is near-zero. The parameters are correct and verified at the household level — the microdata gap is tracked separately.