To analyze panel data in Stata, you follow a structured workflow: preparing your data format, declaring the panel structure, and then running specific "xt" (cross-sectional time-series) commands. 1. Data Structure: Wide vs. Long Stata requires panel data to be in .
Analyzing panel data (data that follows the same entities—like countries, firms, or people—over multiple time periods) is one of Stata's greatest strengths. This guide covers the essential workflow to get you from raw data to a published regression . 1. Preparing Your Data stata panel data
reghdfe ln_wage hours age tenure, absorb(idcode) vce(cluster idcode) To analyze panel data in Stata, you follow
Use this if you believe the unobserved traits (like a person's innate ability or a country's culture) are correlated with your independent variables. FE "wipes out" all time-invariant variables to focus strictly on within-entity Long Stata requires panel data to be in
This ignores the panel structure and pools all data together. It is simple but often biased if unobserved unit-specific characteristics exist (omitted variable bias).