policyengine-analysis

Policy impact analysis uses microsimulation to model how reforms affect households at different income levels. This skill applies PolicyEngine's simulation engine to calculate changes in taxes, credits, and net income across income deciles, revealing distributional effects and identifying winners and losers from proposed policy changes.

Yes. This skill provides pre-configured visualization templates for Plotly charts and Streamlit dashboards designed for policy research. You can create branded, publication-ready dashboards that display reform impacts, household case studies, and comparative analysis across income ranges and geographic regions.

Household-level analysis extracts specific tax, credit, and income metrics using PolicyEngine's variable catalog, then applies them to individual or representative households. This skill standardizes the workflow to compute metrics like income_tax, ctc, and household_net_income for case studies, state-by-state comparisons, and parametric reforms.

This skill provides standardized patterns for parameter-based and structural reforms, ensuring consistent setup, simulation execution, and output generation. It covers data extraction from PolicyEngine catalogs, computation of reform impacts, and export of results ready for notebooks, dashboards, and research reports.

The skill is designed for PolicyEngine microsimulation projects, with core support for policyengine-us. The framework applies to both baseline and reform simulations across different jurisdictions, supporting comparative analysis and region-specific dashboards where PolicyEngine coverage exists.

Core dependencies include pandas for data handling, numpy for computation, plotly for visualization, and policyengine-us for microsimulation. These tools provide the data processing, numerical analysis, and reform simulation engine needed to compute and visualize policy impacts.