OLS regression has typically been used in housing research to determine the relationship of a particular housing characteristic with selling price. Results differ across studies, not only in terms of size of OLS coefficients and statistical significance, but sometimes in direction of effect....

In this study we apply a spatial conditional logit model to determine factors influencing land cover change in three contiguous counties in West Georgia between 1992 and 2001 using point (pixel) based observations of land characteristics. We found that accessibility to population and population...

Housing rents may be influenced by characteristics of nearby properties, an effect captured by spatial autoregression in a hedonic rent equation. We investigate the implications of spatial autoregression for measuring the marginal welfare effects due to a change in a residential amenity such as...

We extend the three-step generalized methods of moments (GMM) approach of Kapoor, Kelejian, and Prucha (2007), which corrects for spatially correlated errors in static panel data models, by introducing a spatial lag and a one-period lag of the dependent variable as additional explanatory...

We extend the three-step generalized methods of moments (GMM) approach of Kapoor et al. (2007), which corrects for spatially correlated errors in static panel data models, by introducing a spatial lag and a one-period lag of the dependent variable as additional explanatory variables. Combining...

This paper focuses on the estimation and predictive performance of several estimators for the dynamic and autoregressive spatial lag panel data model with spatially correlated disturbances. In the spirit of Arellano and Bond (1991) and Mutl (2006), a dynamic spatial GMM estimator is proposed...

A multivariate spatial autoregressive model of local public expenditure determination with autoregressive disturbance is developed and estimated in this paper. The empirical model is developed on the principles of utility maximization of a strictly quasi concave community utility function. The...

Data on agricultural and natural resource management typically have spatial patterns related to the landscapes from which they came. Consequently, econometric models designed to explain the determinants of humans' natural resource management practices or their outcomes often have spatial...

A multivariate spatial autoregressive model of local public expenditure determination with autoregressive disturbance is developed and estimated in this paper. The empirical model is developed on the principles of utility maximization of a strictly quasi concave community utility function. The...

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...