Abstract :
An important reason for analyzing panel data is to observe the dynamic nature of an
economic variable separately from its time-invariant unobserved heterogeneity. This
paper examines how to estimate the autocovariances of a variable separately from its
time-invariant unobserved heterogeneity. When both cross-sectional and time series
sample sizes tend to infinity, we show that the within-group autocovariances are
consistent, although they are severely biased when the time series length is short. The
biases have the leading term that converges to the long-run variance of the individual
dynamics. This paper develops methods to estimate the long-run variance in panel
data settings and to alleviate the biases of the within-group autocovariances based
on the proposed long-run variance estimators. Monte Carlo simulations reveal that
the procedures developed in this paper effectively reduce the biases of the estimators
for small samples.
