import wooldridge as wooimport linearmodels as plmwagepan = woo.dataWoo('wagepan')wagepan['t'] = wagepan['year']wagepan['entity'] = wagepan['nr']wagepan = wagepan.set_index(['nr'])# include group specific means:wagepan['married_b'] = wagepan.groupby('nr').mean()['married']wagepan['union_b'] = wagepan.groupby('nr').mean()['union']wagepan = wagepan.set_index(['year'], append=True)# estimate CRE:reg_cre = plm.RandomEffects.from_formula(formula='lwage ~ married + union + C(t)*educ + married_b + union_b',data=wagepan)results_cre = reg_cre.fit()# RE test as an Wald test on the CRE specific coefficients:wtest = results_cre.wald_test(formula='married_b = union_b = 0')print(f'wtest: \n{wtest}\n')
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