Various forecasts using panel data with spatial error correlation are compared using Monte Carlo experiments. The true data generating process is assumed to be a simple error component regression model with spatial remainder disturbances of the autoregressive or moving average type. The best...

This paper reconsiders the Tobin q investment model studied by Hsiao et al. (1999) using a panel of 337 U.S. firms over the period 1982–1998. It contrasts the out-of-sample forecasts performance of hierarchical Bayes, shrinkage, as well as heterogeneous and homogeneous panel data estimators....

This paper studies the performance of panel unit root tests when spatial effects are present that account for cross-section correlation. Monte Carlo simulations show that there can be considerable size distortions in panel unit root tests when the true specification exhibits spatial error...

This paper contrasts the performance of heterogeneous and shrinkage estimators versus the more traditional homogeneous panel data estimators. The analysis utilizes a panel data set from 21 French regions over the period 1973–1998 and a dynamic demand specification to study the gasoline demand...

Chamberlain [Chamberlain, G., 1982. Multivariate regression models for panel data. Journal of Econometrics 18, 5-46] showed that the fixed effects (FE) specification imposes testable restrictions on the coefficients from regressions of all leads and lags of dependent variables on all leads and...