世界银行-当汇总误导时：用汇总数据进行单位级小面积贫困估计的偏差（英）

Policy Research Working Paper11110When Aggregation MisleadsBias in Unit-Level Small Area Estimates of Poverty with Aggregate DataPaul Andres Corral RodasPoverty and Equity Global Department May 2025 Public Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedProduced by the Research Support TeamAbstractThe Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.Policy Research Working Paper 11110This paper explores why small area poverty estimates from models at the household level that only use aggregate data as covariates, exhibit systematic bias. The analysis demonstrates that this bias stems from the model’s inabil-ity to capture the complete between-household variation in welfare, as they rely solely on covariates aggregated at geographic levels. Through model-based simulations, the paper shows that the bias in these models is minimized when the empirical variability of simulated welfare based on the model is closest to the true empirical variance of welfare at the area level. This finding also has implications for bias in unit-level models.This paper is a product of the Poverty and Equity Global Department. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The author may be contacted at pcorralrodas@worldbank.org. When Aggregation Misleads: Bias in Unit-Level Small AreaEstimates of Poverty with Aggregate DataPaul Andres Corral Rodas∗Key words: Small area estimation; poverty mapping; satellite imagery; census; official statisticsJEL classification: C13; C55; C87; C15∗The World Bank Group - Poverty and Equity Global Practice (pcorralrodas@worldbank.org). The author ac-knowledges financial support from the World Bank. Special thanks to Carlos Rodriguez-Castelan, Alexandru Cojo-caru, Tara Vishwanath, and Isabel Molina for comments on an earlier draft. Full replication package for the resultspresented in this paper may be found in: https://github.com/pcorralrodas/UC_source_of_bias1IntroductionHousehold surveys aimed at gauging a population’s living standards often lack representativenessbeyond broad regions or specific population demographics. Additionally, there is a risk tha