This article applies recent advances in productivity and efficiency measurement to the evaluation of skillbiased technical change. Using the general index approach we are able to establish an explicit and unconstrained time path for nonneutral technical change between production and...

One of the oldest and largest literatures in empirical economics is concerned with the estimation of demand and supply of goods, services, and factors across national or subnational borders (see Leamer and Levinsohn, 1995). The respective empirical models specified and estimated are often...

This paper studies the effect of hospital ownership on treatment rates allowing for spatial correlation among hospitals. Competition among hospitals and knowledge spillovers generate significant externalities which we try to capture using the spatial Durbin model. Using a panel of 2342 hospitals...

This paper focuses on the estimation and predictive performance of several estimators for the time-space dynamic panel data model with Spatial Moving Average Random Effects (SMA-RE) structure of the disturbances. A dynamic spatial Generalized Moments (GM) estimator is proposed which combines the...

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...

Alcohol consumption in Russia is legendary and has been reported to be the third leading cause of death in the former Soviet Union after heart disease and cancer. Are Russian alcohol consumers rational addicts? This paper uses eight rounds of a nationally representative Russian survey spanning...

This paper extends the work of Baltagi et al. (2018) to the popular dynamic panel data model. We investigate the robustness of Bayesian panel data models to possible misspecication of the prior distribution. The proposed robust Bayesian approach departs from the standard Bayesian framework in...

Many data situations require the consideration of network effects among the cross-sectional units of observation. In this paper, we present a generalized panel model which accounts for two features: (i) three types of network effects on the right-hand side of the model, namely through weighted...

This paper extends the Baltagi et al. (2018, 2021) static and dynamic ?-contamination papers to dynamic space-time models. We investigate the robustness of Bayesian panel data models to possible misspecification of the prior distribution. The proposed robust Bayesian approach departs from the...