Stata Panel Data !!install!! [ 2025-2026 ]

xtreg income education experience, fe estimates store fe_model Use code with caution. Estimate the Random Effects model and save the estimates:

Used when the lagged dependent variable is included as a predictor (e.g., ). Use xtabond or xtabond2 (for Difference or System GMM).

Visual xtline ln_wage if idcode <= 20, overlay

Stata uses the xtreg prefix to estimate standard panel data models. Pooled OLS stata panel data

xtreg income education experience, re estimates store re_model Use code with caution. Run the Hausman test: hausman fe_model re_model Use code with caution.

FE is Stata’s superstar. It controls for time-invariant unobservables (e.g., corporate culture, country geography). But:

To analyze panel data in , you must first ensure the data is in "long" format—where each row represents one observation for a specific entity at a specific time 1. Declaring Panel Data Structure Before using specialized panel commands, you must tell which variable identifies the (e.g., countries, firms) and which identifies (e.g., years). xtset panelvar timevar xtset country year Visual xtline ln_wage if idcode <= 20, overlay

Before modeling, explore the variation within and between your entities using specialized panel description commands. Summarizing Panel Data

Want to include a lagged dependent variable? FE is inconsistent (Nickell bias). Enter Arellano-Bond ( xtabond ). Stata’s implementation is powerful but:

* 3. Run Random Effects quietly xtreg y x, re FE is Stata’s superstar

In panel data, the error term of one period may be correlated with the next.

Standard errors in panel regressions can easily be distorted by violations of classical assumptions. Heteroskedasticity

To work with panel data in Stata, follow these steps:

xtserial ln_wage hours age tenure