Pooled estimation of long-run relationships in dynamic heterogeneous panels

Abstract

It is now quite common to have panels in which T, the number of time series observations on the N groups, is quite large. The usual practice is either to estimate N separate regressions and calculate the mean, which we call the Mean Group estimator, or to pool the data and assume the slope coefficients and variances are identical. In this paper, the authors propose an intermediate procedure, referred to as the Pooled Mean Group (PMG) estimator, which constrains the long-run coefficients to be identical, but allows the short- run coefficients and error variances to differ across groups. The stationary case is considered as well as the case where the underlying regressors follow unit root processes, and for both cases the asymptotic distribution of the PMG estimator as T tends to infinity is derived, for a fixed N. The authors also provide an empirical application to aggregate consumption functions across 24 OECD economies.

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