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budget.households is the sum of squared household weights

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@PavelMakarchuk ci sta già lavorando.

Dal 12/10/2026.

  • #767 di @PavelMakarchuk — aperta

Valutazione

Difficoltà
2/5
Tempo stimato
1-3 ore
Idoneità per principianti
20/100
Tipo di issue
Bug
Chiarezza
Specificata chiaramente
Stato di attività
Ferma
Stack tecnologico
python
Ambito
backend, databases, testing

Direzione di ricerca

Start in simulation_output_budget.build_budgetary_impact and inspect how _sum_output_variable handles the household MicroDataFrame and its household_weight column. The existing test test_builder_budgetary_impact_uses_materialized_columns_and_uk_state_tax_zero uses plain DataFrames; add coverage with a real MicroDataFrame and verify the household count is 3 for weights [1, 2]. An open linked pull request (#767) is already addressing this issue.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Problem

The economy comparison's budget.households is the sum of squared household weights, not the household count. It is about 10⁴ times too high on every run, national and state:

Run (/us/economy/{reform}/over/2) budget.households Actual households
region=state/ny, 2026 135,597,233,840 ~7.5 million
region=state/ca, 2026 197,620,236,261 ~13.5 million
region=state/va, 2027 44,192,009,994 ~3.3 million

Cause

simulation_output_budget.build_budgetary_impact sets households=_sum_output_variable(baseline, "household_weight", entity="household").

_sum_output_variable returns float(data[variable].sum()). Here data is the household MicroDataFrame, which policyengine weights by household_weight. So data["household_weight"] is a weighted MicroSeries, and its .sum() is Σ w × w.

Weights [1, 2] give 5.0 instead of 3.0. The existing test (test_builder_budgetary_impact_uses_materialized_columns_and_uk_state_tax_zero) uses plain pd.DataFrames, so it never caught this.

This came in with 36d3be0 ("adapt simulation worker to PolicyEngine v4 outputs").

The other budget fields are correct. They are meant to be weighted sums.

Impact

Clients divide by this field. For example, policyengine-app-v2 computes the headline average change per household as -budget.budgetary_impact / budget.households. That number is therefore about 10⁴ times too small on every report.

Fix

Count entities with a plain sum of their weight column, and test it on a real MicroDataFrame.

Lingua principale
Python
Stelle
1
Fork
1
Merge medio
1g 11h
PR unite (30g)
50

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