Unobserved heterogeneity in panel time series models

Recently, the large T panel literature has emphasized unobserved, time-varying heterogeneity that may stem from omitted common variables or global shocks that a¤ect each individual unit di¤erently. These latent common factors induce cross-section dependence and may lead to inconsistent regression coe¢ cient estimates if they are correlated with the explanatory variables. Moreover, if the process underlying these factors is nonstationary, the individual regressions will be spurious but pooling or averaging across individual estimates still permits consistent estimation of a long-run coe¢ cient. The need to tackle both error cross-section dependence and persistent autocorrelation is motivated by the evidence of their pervasiveness found in three well-known, international …nance and macroeconomic examples. A range of estimators is surveyed and their …nite-sample properties are examined by means of Monte Carlo experiments. These reveal that a mean group version of the common-correlated-e¤ects estimator stands out as the most robust since it is the preferred choice in rather general (non) stationary settings where regressors and errors share common factors and their factor loadings are possibly dependent. Other approaches which perform reasonably well include the two-way …xed e¤ects, demeaned mean group and between estimators but they are less e¢ cient than the common-correlated-e¤ects estimator. Keywords : Factor analysis; global shocks; latent variables JEL Classi…cation : C32; F31