Working Paper
38

geoSIMEX: A Generalized Approach To Modeling Spatial Imprecision

Date Published

Apr 1, 2017

Authors

Daniel Runfola, Robert Marty, Seth Goodman, Michael Lefew, Ariel BenYishay

Publisher

Citation

Runfola, Daniel et al. 2017. geoSIMEX: A Generalized Approach To Modeling Spatial Imprecision. AidData Working Paper #38. Williamsburg, VA: AidData at William & Mary.

Announcement

There is a large and growing set of literature examining how different classes of models can integrate information on spatial imprecision in order to more accurately reflect available data. Here, we present a flexible approach - geoSIMEX - which can provide parameter and error estimates while adjusting for spatial imprecision. We illustrate this approach through a case study leveraging a novel, publically available dataset recording the location of Chinese aid in Southeast Asia at varying levels of precision. Using a difference-in-difference modeling approach, we integrate Chinese aid information with satellite derived data on vegetation (NDVI) to examine if Chinese aid has caused an increase or decrease in vegetation. Following multiple approaches which do not incorporate spatial imprecision, we find that Chinese aid had a negative impact on vegetation; once spatial imprecision was incorporated into our estimates through the geoSIMEX procedure no evidence of impact is found.

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Dan Runfola
Research & Evaluation

Dan Runfola

Senior Geospatial Scientist

Robert Marty

Robert Marty

Research Assistant

Seth Goodman
Research & Evaluation

Seth Goodman

Data Engineer

Ariel BenYishay
Research & Evaluation

Ariel BenYishay

Chief Economist, Director of Research and Evaluation

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