Stata Panel Data Portable Now
From wide to long:
estat abond And estat sargan for overidentification test. For long panels (large T):
reshape wide income_, i(id) j(year) Before modeling, explore the data using panel-specific commands. Visualizing Panel Data xtline wage, overlay legend(off) title("Wage trajectories by individual") xtline wage, by(idcode, note("First 20 individuals")) ylabel(, angle(0)) Correlation Structures pwcorr wage hours tenure age But remember: panel correlations must respect dependence. Use xtcorr for cross-sectional correlation over time. Part 5: Core Panel Data Models in Stata This is the heart of Stata panel data analysis. Model 1: Pooled OLS (Naïve Model) Ignores panel structure entirely. Useful as a baseline. stata panel data
isid idcode year, sort duplicates report idcode year duplicates drop idcode year, force // Use with caution misstable summarize drop if missing(your_dependent_var, your_key_independent_var) 3. Create Lag and Lead Variables Crucial for dynamic models:
xtscc wage hours tenure, fe lag(2) (Requires xtscc package from SSC: ssc install xtscc ) xtreg wage hours tenure, fe vce(bootstrap, reps(200)) Part 7: Diagnostics for Panel Models Run these after your main estimation. 1. Serial Correlation in Errors (Wooldridge test) xtserial wage hours tenure Null: no first-order serial correlation. 2. Cross-Sectional Dependence (Pesaran’s test) Important for macro or spatial panels. From wide to long: estat abond And estat
reg wage hours tenure age i.year, robust Ignores unobserved individual heterogeneity (e.g., ability, motivation). Standard errors are likely biased. Model 2: Fixed Effects (FE) – "Within Estimator" The workhorse model. Removes all time-invariant unobserved heterogeneity by demeaning each panel's data. Only estimates effects of variables that vary within units over time. Command: xtreg wage hours tenure age, fe or equivalently:
Stata has become the industry standard for panel data analysis, offering an intuitive yet powerful suite of tools. From (the cornerstone command) to sophisticated fixed effects, random effects, and dynamic panel models, Stata provides a seamless workflow. Use xtcorr for cross-sectional correlation over time
reshape long income_, i(id) j(year) From long to wide:
