Advertisement

Probit in a Spatial Context: A Monte Carlo Analysis

  • Kurt J. Beron
  • Wim P. M. Vijverberg
Part of the Advances in Spatial Science book series (ADVSPATIAL)

Abstract

Data are often observed in a binary form: vote for or vote against; buy or don’t buy; build or don’t build; move or don’t move, etc. In classical econometrics this situation has been extensively studied and appropriate procedures developed to handle the nature of the data. The standard model however does not allow for spatial processes to drive the choices made by decision makers. For example, whether one city increases its sales tax may depend the actions of neighboring cities. Whether one jurisdiction subsidizes the construction of a new sports arena depends on the options that are offered to the sports enterprise by other jurisdictions — which has been occurring with increasing frequency in the United States, at the threat of the team moving elsewhere. In both of these cases, the conventional probit model fails to account for interdependencies.

Keywords

Spatial Dependence Probit Model Monte Carlo Sample Spatial Error Spatial Context 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Kurt J. Beron
    • 1
  • Wim P. M. Vijverberg
    • 1
  1. 1.University of Texas at DallasUSA

Personalised recommendations