Correcting For Spatial Effects In Limited Dependent Variable Regression: Assessing The Value Of "Ad-Hoc" Techniques
A 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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9508, Université Laval - Département d'économique.
- Denis Bolduc & Bernard Fortin & Stephen Gordon, 1997. "Multinomial Probit Estimation of Spatially Interdependent Choices: An Empirical Comparison of Two New Techniques," International Regional Science Review, , vol. 20(1-2), pages 77-101, April.
- Bolduc, D. & Fortin, B. & Gordon, S., 1995. "Multinomial Probit Estimation of Spatially Interdependent Choices: An Empirical Comparison of Two New Techniques," Papers 9508, Laval - Recherche en Politique Economique.
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