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ABSTRACT
Morocco has integrated the human development paradigm into their country-wide planning goals. The 2004 Moroccan census measured HDI for every commune in Morocco, the smallest spatial unit for which data are available. However, when the 2014 Moroccan census was released HDI values were omitted . To measure the change in HDI over the 10-year period, this article uses spatial econometric models along with the RandomForest algorithm in order to make out-of-sample predictions for 2014 HDI scores at the Moroccan commune level. The article concludes that in certain situations RandomForest can outperform spatial econometric models, and discusses the benefits this approach.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Matthew R Lehnert
Matthew R Lehnert is an Assistant Professor in the school of Humanities and Social Sciences at Al Akhawayn University in Morocco. His research interests include spatial data science, spatial statistics, spatial machine learning, and spatial econometrics. E-Mail: [email protected]
Oleg Smirnov
Oleg Smirnov is a Professor in the school of Economics at the University of Toledo. His research interests include Regional and Spatial Economics. E-Mail:[email protected]