Just as he felt victory, he remembered the "Panel Data Demons": and Autocorrelation . In panel data, the errors from one year often whisper to the errors of the next.
xtserial y x1 x2
This produces , which are robust to all three issues, ensuring your p-values are actually reliable in complex datasets. Summary Checklist for your Stata Panel Project Set & Validate: xtset followed by xtdescribe . Decompose: Use xtsum to check for within-group variation. Test: Run a Hausman test (with robust options if needed). Adjust: Use L. and D. operators for lags and differences. Protect: Use vce(cluster id) or xtscc for inference.
reshape long y, i(id) j(year)
testparm i.year // after FE regression
This will estimate a random-effects model of y on x1 and x2 .
This runs the Levin-Lin-Chu test. Other exclusive options include:
Just as he felt victory, he remembered the "Panel Data Demons": and Autocorrelation . In panel data, the errors from one year often whisper to the errors of the next.
xtserial y x1 x2
This produces , which are robust to all three issues, ensuring your p-values are actually reliable in complex datasets. Summary Checklist for your Stata Panel Project Set & Validate: xtset followed by xtdescribe . Decompose: Use xtsum to check for within-group variation. Test: Run a Hausman test (with robust options if needed). Adjust: Use L. and D. operators for lags and differences. Protect: Use vce(cluster id) or xtscc for inference. stata panel data exclusive
reshape long y, i(id) j(year)
testparm i.year // after FE regression
This will estimate a random-effects model of y on x1 and x2 . Just as he felt victory, he remembered the
This runs the Levin-Lin-Chu test. Other exclusive options include: Summary Checklist for your Stata Panel Project Set