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econ-data-analysis

Enforce reproducible workflows for economic data analysis with validation and documentation.

8|2|Updated Apr 9, 2026
Search Tags:#data validation#sensitivity analysis#reproducible research#regression analysis#panel data#economic data analysis#notebook workflows
One-click install
npx skills add https://github.com/FuZhiyu/superRA --skill econ-data-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: econ-data-analysis
Source: https://github.com/FuZhiyu/superRA/tree/main/skills/econ-data-analysis
Command: npx skills add https://github.com/FuZhiyu/superRA --skill econ-data-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill prevents silent errors in economic data analysis by enforcing disciplined data description, transparent transformations, validation, and reproducible documentation throughout the research workflow.

Core Features & Use Cases

  • Describe and Validate Data: Inspect panel structure, variable distributions, data types, missingness, outliers, and post-transformation changes.
  • Analyze with Integrity: Guide safe merges, filtering, reshaping, aggregation, deduplication, time-series operations, variable construction, and missing-data handling with row-count logging and documented decisions.
  • Support Reproducible Research: Structure notebook-compatible analysis scripts, design sensitivity checks, preserve analytical evidence during integration, and protect headline results from drift.
  • Use Case: Apply the Skill to clean a panel dataset, construct growth variables, merge macroeconomic controls, run regressions, generate figures, and document the resulting findings in a task record.

Quick Start

Use the econ-data-analysis skill to plan and execute a rigorous analysis of the available economic or financial data, including diagnostics, transformations, validation checks, figures, and documented results.

Frequently Asked Questions about econ-data-analysis

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

FAQPage Schema
How do I ensure reproducible research when running economic data analysis?▼

Reproducible economic data analysis requires explicit data inventories, row-count logs, missingness diagnostics, notebook-compatible scripts, and protected headline results to prevent silent errors during transformations.

What is the best way to validate panel data before running a regression analysis?▼

Validating panel data before regression analysis involves inspecting panel structure, checking variable distributions, logging missingness, identifying outliers, and performing economic-sense checks on post-transformation changes.

How do I prevent silent errors when merging and filtering cross-sectional datasets?▼

Preventing silent errors when merging and filtering cross-sectional datasets requires disciplined row-count logging, documented transformation decisions, and explicit diagnostics for missing data and distribution changes.

Can I use notebook workflows for time-series and financial data aggregation?▼

Notebook workflows support time-series and financial data aggregation by structuring compatible analysis scripts, preserving analytical evidence during integration, and protecting headline results from drift.

Why does my economic data analysis produce inconsistent headline results?▼

Inconsistent headline results in economic data analysis often occur when transformations lack sensitivity checks, row-count logs, and protected result tracking, allowing undocumented changes to alter findings.

When should I run sensitivity analysis during variable construction?▼

Sensitivity analysis should run during variable construction to verify economic-sense checks, detect distribution shifts, and ensure that constructed growth variables and macroeconomic controls remain stable across transformations.

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