before switching to -xtgls- despite havibng a large N, small T dataset,, please note the dramatically different times (in seconds) taken by -xtreg- and -xtgls- to perform the same simple panel data regression:

Code:

. set rmsg on r; t=0.00 15:48:21 . xtreg ln_wage i.race, re Random-effects GLS regression Number of obs = 28,534 Group variable: idcode Number of groups = 4,711 R-sq: Obs per group: within = 0.0000 min = 1 between = 0.0198 avg = 6.1 overall = 0.0186 max = 15 Wald chi2(2) = 99.02 corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 ------------------------------------------------------------------------------ ln_wage | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- race | black | -.1300382 .013486 -9.64 0.000 -.1564702 -.1036062 other | .1011474 .0562889 1.80 0.072 -.0091768 .2114716 | _cons | 1.691756 .0071865 235.41 0.000 1.677671 1.705841 -------------+---------------------------------------------------------------- sigma_u | .38195681 sigma_e | .32028665 rho | .58714668 (fraction of variance due to u_i) ------------------------------------------------------------------------------ r; t=0.61 15:48:28 . xtgls ln_wage i.race Cross-sectional time-series FGLS regression Coefficients: generalized least squares Panels: homoskedastic Correlation: no autocorrelation Estimated covariances = 1 Number of obs = 28,534 Estimated autocorrelations = 0 Number of groups = 4,711 Estimated coefficients = 3 Obs per group: min = 1 avg = 6.056888 max = 15 Wald chi2(2) = 542.80 Log likelihood = -19162 Prob > chi2 = 0.0000 ------------------------------------------------------------------------------ ln_wage | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- race | black | -.1427862 .006243 -22.87 0.000 -.1550222 -.1305502 other | .080671 .0274112 2.94 0.003 .026946 .134396 | _cons | 1.714338 .0033339 514.21 0.000 1.707804 1.720873 ------------------------------------------------------------------------------ r; t=692.49 16:00:07 .

-skipping -xttest2- and -xttest3-;

- graphically inspect your residual distribution;

-robustify/cluster your standard errors if you suspect that (especially) heteroskedasticity can bite your results (as said, serial correlation is expected to be a minor nuisance with a short T dimension).

Otherwise, as many econometricians usually do, go -cluster-/-robust- from scratch; with 200 -panelid- you have enough clusters to survive.

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