This paper examines the consequences of model misspecification using a panel data model with spatially autocorrelated disturbances. The performance of several maximum likelihood estimators assuming different specifications for this model are compared using Monte Carlo experiments. These include...

This paper prooses a generalized panel data model with random effects and first-order spatially autocorrelated residuals that encompasses two previously suggested specifications. The first one is described in Anselin's (1988) book and the second one by Kapoor, Kelejian, and Prucha (2007). Our...

This paper studies the spatial random effects and spatial fixed effects model. The model includes a Cliff and Ord type spatial lag of the dependent variable as well as a spatially lagged one-way error component structure, accounting for both heterogeneity and spatial correlation across units. We...

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...

We present a theoretical model of moral hazard and adverse selection in an imperfectly competitive loans market that is suitable for application to Africa. The model allows for variation in both the level of contract enforcement (depending on the quality of governance) and the degree of market...

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...