Monte Carlo simulations are used to explore the small-sample properties of a mean group and two pooled panel estimators of a regression coefficient when the regressor is I(1). We compare and contrast the effect of I(0) and I(1) errors and homogeneous and heterogeneous coefficients in a design based on two typical PPP panels. The results confirm that the asymptotic theory is relevant to practical applications. With I(0) errors and homogeneous coefficients, the estimators are unbiased, dispersion depends on the signal-noise ratio and falls at rate T(rootN) as expected. With I(1) errors and no cointegration, dispersion falls at rate rootN. When heterogeneity is introduced with I(0) errors, the dispersion of the pooled estimators falls at rate root N, but that of the mean group continues to fall at rate T(rootN). Finally, the pooled estimators are likely to lead to distorted inference both in the case of I(1) errors and the case of I(0) errors with heterogeneous coefficients case. The mean group estimators are, however, are generally correctly sized
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