Skill Name

Purpose

Describe what this skill does and when an economist should use it. Be specific about the problem it solves.

When to Use

  • Use this skill when you need to…
  • This is especially helpful for…

Instructions

Follow these steps to complete the task:

Step 1: Understand the Context

Before generating any code, ask the user:

  • What is the research question?
  • What data format are you working with?
  • What software/language preference do you have?

Step 2: Generate the Output

Based on the context, generate [code/document/analysis] that:

  1. Follows best practices - Use standard conventions for [Stata/R/Python/LaTeX]
  2. Is reproducible - Include comments explaining each step
  3. Handles edge cases - Check for missing data, outliers, etc.

Step 3: Verify and Explain

After generating output:

  • Explain what the code does
  • Highlight any assumptions made
  • Suggest next steps or improvements

Example Prompts

Users might invoke this skill with prompts like:

  • “Run a difference-in-differences analysis on my treatment data”
  • “Clean this dataset and create summary statistics”
  • “Write the methodology section for my regression analysis”

Example Output

* Example Stata code this skill might generate
* ============================================

* Load data
use "data.dta", clear

* Summary statistics
summarize var1 var2 var3

* Main regression
regress y x1 x2 x3, robust
eststo model1

* Export results
esttab model1 using "results.tex", replace

Requirements

Software

  • Stata 17+ / R 4.0+ / Python 3.10+

Packages

  • For R: tidyverse, fixest, modelsummary
  • For Python: pandas, statsmodels, linearmodels
  • For Stata: Built-in commands

Best Practices

When using this skill, ensure:

  1. Data is properly formatted - Variables named clearly, no special characters
  2. Sample is defined - Clear inclusion/exclusion criteria
  3. Output is documented - All results are reproducible

Common Pitfalls

Avoid these mistakes:

  • ❌ Running analysis without checking data quality first
  • ❌ Ignoring missing values or outliers
  • ❌ Not specifying robust standard errors when needed

References

  • [Relevant documentation or textbook]
  • [Academic paper on methodology]
  • [Software package documentation]

Changelog

v1.0.0

  • Initial release