亚开行-基于机器学习的贫困地图中的空间异质性：模型在哪里表现不佳？（英）

ASIAN DEVELOPMENT BANKADB ECONOMICSWORKING PAPER SERIESNO. 798September 2025SPATIAL HETEROGENEITY IN MACHINE LEARNING-BASED POVERTY MAPPINGWHERE DO MODELS UNDERPERFORM?Yating Ru, Elizabeth Tennant, David S. Matteson, and Christopher B. BarrettASIAN DEVELOPMENT BANKThe ADB Economics Working Paper Series presents research in progress to elicit comments and encourage debate on development issues in Asia and the Pacific. The views expressed are those of the authors and do not necessarily reflect the views and policies of ADB or its Board of Governors or the governments they represent.ADB Economics Working Paper SeriesYating Ru, Elizabeth Tennant, David S. Matteson, and Christopher B. BarrettNo. 798 | September 2025Yating Ru (yru@adb.org) is a natural resources and agriculture economist at the Sectors Department 2, Asian Development Bank. Elizabeth Tennant (ejt58@cornell.edu) is a research associate and a visiting lecturer; David S. Matteson (matteson@cornell.edu) is a professor and associate department chair of statistics and data science; and Christopher B. Barrett (cbb2@cornell.edu) is the Stephen B. and Janice G. Ashley professor of applied economics and management at Cornell University. Spatial Heterogeneity in Machine Learning-Based Poverty Mapping: Where Do Models Underperform?  Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO)© 2025 Asian Development Bank6 ADB Avenue, Mandaluyong City, 1550 Metro Manila, PhilippinesTel +63 2 8632 4444; Fax +63 2 8636 2444www.adb.orgSome rights reserved. Published in 2025.ISSN 2313-6537 (print), 2313-6545 (PDF)Publication Stock No. WPS250340-2DOI: http://dx.doi.org/10.22617/WPS250340-2The views expressed in this publication are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or its Board of Governors or the governments they represent. ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. The mention of specific companies or products of manufacturers does not imply that they are endorsed or recommended by ADB in preference to others of a similar nature that are not mentioned.By making any designation of or reference to a particular territory or geographic area in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area.This publication is available under the Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) https://creativecommons.org/licenses/by/3.0/igo/. By using the content of this publication, you agree to be bound by the terms of this license. For attribution, translations, adaptations, and permissions, please read the provisions and terms of use at https://www.adb.org/terms-use#openaccess.This CC license does not apply to non-ADB copyright materials in this publication. If the material is attributed to another source, please contact the copyright owner or publisher of that s