Small area estimation of non-monetary poverty with geospatial data

Takaaki Masaki, David Newhouse, Ani Rudra Silwal, Adane Bedada, Ryan Engstrom
2022 Statistical Journal of the IAOS  
This paper evaluates the benefits of combining household surveys with satellite and other geospatial data to generate small area estimates of non-monetary poverty. Using data from Tanzania and Sri Lanka and applying a household-level empirical best (EB) predictor mixed model, we find that combining survey data with geospatial data significantly improves both the precision and accuracy of our non-monetary poverty estimates. While the EB predictor model moderately underestimates standard errors
more » ... those point estimates, coverage rates are similar to standard survey-based standard errors that assume independent outcomes across clusters.
doi:10.3233/sji-210902 fatcat:uw43245elffotegg5elq2y3axu