policyengine-uk-data

Name: policyengine-uk-data
Availability: InStock
Author: PolicyEngine

Impute wealth variables from WAS into FRS datasets via impute_from_was.

31|6|Updated Oct 19, 2025

Search Tags:#imputation #datasets #wealth #WAS #FRS #uk

Ready to run

npx skills add https://github.com/PolicyEngine/policyengine-claude --skill policyengine-uk-data

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: policyengine-uk-data
Source: https://github.com/PolicyEngine/policyengine-claude/tree/main/skills/data-science/policyengine-uk-data-skill
Command: npx skills add https://github.com/PolicyEngine/policyengine-claude --skill policyengine-uk-data

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

PolicyEngine UK Data enhances the Family Resources Survey (FRS) by imputing wealth variables from the Wealth and Assets Survey (WAS), enabling richer wealth analyses in UK microsimulations.

Core Features & Use Cases

WEALTH IMPUTATION: Adds WAS-derived wealth variables to FRS datasets.
Data Coverage: Bridges wealth information gap in large UK surveys for policy analysis.
Use Case: Run analyses comparing post-policy wealth distributions using enhanced FRS data.

Quick Start

Load the enhanced FRS dataset and apply WAS-based wealth imputations to generate wealth-aware analytics.

Frequently Asked Questions about policyengine-uk-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I add wealth variables to FRS survey data?▼

Wealth imputation adds WAS-derived wealth variables to Family Resources Survey datasets. This Skill applies statistical matching to bridge the wealth information gap, enabling enhanced analyses of household finances in UK microsimulations without collecting new survey data.

What's the difference between FRS and WAS datasets?▼

The Family Resources Survey (FRS) is a large UK household survey lacking detailed wealth data, while the Wealth and Assets Survey (WAS) specializes in wealth but has smaller sample sizes. This Skill combines both by imputing WAS wealth variables into FRS records for comprehensive policy analysis.

Can I use imputed wealth data for policy analysis and validation?▼

Yes. The Skill supports derived variables, validation utilities, and testing scenarios designed for analysts and policy researchers. Enhanced FRS datasets with imputed wealth enable wealth-aware policy comparisons and modular pipeline integration across calibration and validation workflows.

What happens after wealth imputation—how do I use the enhanced data?▼

After imputation, the enriched FRS dataset is ready for downstream analysis: run wealth distribution comparisons, model post-policy outcomes, or export results for further processing. The modular design integrates with existing FRS enhancement pipelines for seamless analyst workflows.

Do I need to preprocess my FRS data before imputation?▼

The Skill handles FRS datasets as input and applies RENAMES mappings and derived balance calculations internally. Ensure your FRS data matches standard survey structure; the modular Python implementation manages technical transformation and validation steps automatically.

What are the limitations of wealth imputation from WAS?▼

Imputation relies on statistical matching between FRS and WAS samples, so accuracy depends on representative overlap and homogeneity assumptions. Results are estimates, not observed values; use validation utilities provided to assess fit for your specific policy research context.