Become The Master Of Applying Spatial Regression Models


Although the classical econometric methods provide information on the geographic distribution of poverty, they do not take into account the spatial dependence of the data and generally they do not consider any environmental information. Therefore, methods which use spatial analysis tools are required to explore such spatial dimensions of poverty and its linkages with the environmental conditions. This study investigates an approach based on the spatial regression model, for mapping poverty in Ecuador. It also documents the use and impact of such an approach and the opportunities it offers.

Following a brief introduction, the study reviews two econometric methods that are widely used for analysing poverty and compares their results with the results obtained by the spatial regression method. The differences in numerical results were not large, but statistically significant for the Ecuador data. The study also includes a simulation study on sensitivity analysis for scenarios for public policy intervention.

Keywords: poverty mapping, spatial regression model, Ecuador, statistical estimation, GIS

This series replaces the following:

  • Environment and Energy Series
  • Remote Sensing Centre Series
  • Agrometeorology Working Papers

A list of documents published in the above series and other information can be found at the following Web site:

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