Several spatial econometric approaches are available to model spatially correlated disturbances in count models, but there are at present no structurally consistent count models incorporating spatial lag autocorrelation. A two-step, limited information maximum likelihood estimator is proposed to...

Attracting manufacturing investment remains a viable regional development policy. Previous research in the location literature has informed policymakers which factors are most important for attracting new firm investment. Far less is known about the dynamics of firm death and the possible...

Learning English is a potentially profitable investment for immigrants in the U.S.: while there are initial costs, the subsequent benefits include the ability to communicate with the majority of the population, potentially leading to better paying jobs and economic success in the new country....

Site-specific data is spatially variable, precluding traditional econometric analysis. Some field-scale experimental designs present logistical, operational and mathematical problems in estimating treatment differences, specifically when adjacent observations are of different treatments such as...

This study uses Monte Carlo analysis to investigate the performances of five different meta-analysis (MA) estimators: the Fixed Effects (FE) estimator, the Weighted Least Squares (WLS) estimator, the Random Effects (RE) estimator, the Precision Effect Test (PET) estimator, and the Precision...

This paper analyzes the geographic distribution of “green energy” sector clustering in the lower 48 United States using recent developments in industry concentration analysis. Evidence suggests that the ten green energy subsectors and the aggregate of the firms comprising the green energy...

This research uses a sequence of hedonic housing price regressions to estimate open space amenity values. The iterative approach empirically identifies the range of distance over which open space affects housing values. After controlling for numerous other factors in the spatial hedonic model,...

Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the number of specific types of precision agriculture technologies adopted by cotton farmers. Particular attention is...

We used survey data collected from cotton farmers in 12 southern U.S. states to identify factors influencing cotton farmers’ decisions to adopt precision farming. Using a seemingly unrelated ordered probit model, we found that younger, educated and computer literate farmers chose precision...

Replaced with revised version of paper 02/16/11.