Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/259481 
Erscheinungsjahr: 
2021
Schriftenreihe/Nr.: 
ADB Economics Working Paper Series No. 643
Verlag: 
Asian Development Bank (ADB), Manila
Zusammenfassung: 
Granular spatial information on the distributions of human population is relevant to a variety of fields like health, economics, and other areas of public sector planning. This paper applies ensemble methods and aims at assessing their applicability to analyzing and forecasting population density on a grid level. In a first step, we use a Random Forest approach to estimate population density in the Philippines and Thailand on a 100 meter by 100-meter level. Second, we use different specifications of Random Forest and Bayesian model averaging techniques to create forecasts of the grid-level population density in three Thailand provinces and evaluate their predictive power.
Schlagwörter: 
population mapping
big data
random forest estimation
Philippines
Thailand
JEL: 
C19
D30
O15
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Dokumentart: 
Working Paper

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