This paper compares various forecasts using panel data with spatial error correlation. 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 linear unbiased predictor...

This paper compares various forecasts using panel data with spatial error correlation. 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 linear unbiased predictor...

This paper considers various estimators using panel data seemingly unrelated regressions (SUR) with spatial error correlation. The true data generating process is assumed to be SUR with spatial error of the autoregressive or moving average type. Moreover, the remainder term of the spatial...

This paper examines the stationarity of carbon dioxide (CO2) emissions per capita for a set of 36 countries covering the period 1870-2006. We employ recently developed unit root and stationarity tests that allow for the mean reverting process to be nonlinear and take into account cross sectional...

The idea that certain economic variables are roughly constant in the long-run is an old one. Kaldor described them as stylized facts, whereas Klein and Kosobud labelled them great ratios. While such ratios are widely adopted in theoretical models in economics as conditions for balanced growth,...

This paper develops a Stein-like combined estimator for large heterogeneous panel data models under common structural breaks. The model allows for cross-sectional dependence through a general multifactor error structure. By utilizing the common correlated effects (CCE) estimation technique, we...

Using data for 70 U.S. metropolitan areas, this study explores spatial heterogeneity in house price dynamics. We use recent advances in panel econometrics that allow for spatial heterogeneity, cross-sectional dependence, and non-stationary but cointegrated data. We test for spatial differences...

(Spatial) panel data are routinely modelled in discrete time (DT). However, there are compelling arguments for continuous time (CT) modelling of (spatial) panel data. Particularly, most social processes evolve in CT, so that statistical analysis in DT is an oversimplification, gives an...