Correcting For Spatial Effects In Limited Dependent Variable Regression: Assessing The Value Of "Ad-Hoc" Techniques
AbstractA common test for spatial dependence in regression analysis with continuous dependent variables is the Moran's I. For limited dependent variable models, the standard definition of a residual breaks down because yi is qualitative. Efforts to correct for potential spatial effects in limited dependent variable models have relied on ad-hoc methods such as including a spatial lag variable or using a regular sample that omits neighboring observations. Kelejian and Prucha have recently developed a version of Moran's I for limited dependent variable models. We present the statistic in a more accessible way and use it to test the value of previously-used ad-hoc techniques with a specific data set. Keywords: Morans I, Spatial Autocorrelation, Limited Dependent Variable Models, Land-Use Change, Geographical Information Systems (GIS),
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Bibliographic InfoPaper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 2002 Annual meeting, July 28-31, Long Beach, CA with number 19782.
Date of creation: 2002
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Moran's I; Spatial Autocorrelation; Limited Dependent Variable Models; Land-Use Change; Geographical Information Systems (GIS); Research Methods/ Statistical Methods;
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