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...

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...

The purpose of the paper is to test the long-run steady state of growth factors hypothesized to influence U.S. manufacturing investment flows. These factors include agglomeration, market structure, labor, infrastructure, and fiscal policy. Spatial cross-regressive and spatial Durbin models are...

This paper shows that spatial panel data models can be successfully applied to an econometric analysis of farm-scale precision agriculture data. The application focuses on the estimation of the effect of controlled drainage water management equipment on corn yields. Using field-level precision...

The paper starts with a discussion of a conceptual model of location factors in U.S. manufacturing investment at the state level. The purpose of the paper is to test the relative importance of growth factors influencing investment and whether or not they have changed in importance over time....

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...