You can obtain tests for poolability across cross sections by specifying the POOLTEST option in the MODEL statement. The null hypothesis of poolability assumes homogeneous slope coefficients.
For the unrestricted model, run a regression for each cross section and save the sum of squared residuals as . Sum over all cross sections to obtain
. For the restricted model, save the sum of squared residuals for each cross section as
. Sum over all cross sections to obtain
. If the test applies to all coefficients (including the constant), then the restricted model is the pooled model (OLS); if the test applies to coefficients other than the constant, then the restricted model is the fixed one-way model with cross-sectional fixed effects. Let k be the number of regressors except the constant. The degrees of freedom for the unrestricted model is
. If the constant is restricted to be the same, the degrees of freedom for the restricted model is
and the number of restrictions is
. If the restricted model is the fixed one-way model, the degrees of freedom is
and the number of restrictions is
. So the F test is
For large N and T, you can use a chi-square distribution to approximate the limiting distribution, namely, . The test is the same as the Chow test (Chow 1960) extended to N linear regressions.
Zellner (1962) also proved that the likelihood ratio test for null hypothesis of poolability can be based on the F statistic. The likelihood ratio can be expressed as . Because
, under the null hypothesis LR is asymptotically distributed as chi-square with q degrees of freedom.