This article reviews the recent literature on the developmental effects of resource abundance, assessing likely effects and channels with respect to key development outcomes. To date, this area has received less analysis, although it is relevant to the United Nations' Sustainable Development Goals agenda, as a significant number of the world's poor live in African resourcerich economies. We argue that the presence of a natural resource sector per se does not necessarily translate into worse development outcomes. The natural resource experience varies to a significant extent. Countries with similar levels of resource rents can end up with significantly different achievements in terms of income inequality, poverty, education, and health. The challenge is to explain the different natural resource experiences. A pivotal mechanism behind the developmental effects of the natural resources sector is the type of states and political institutions that resource-abundant economies develop. 4.1 , . • • � -Review in Advance first posted on May 25, 2021. (Changes may still occur before final publication.

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Proxy means test (PMT) poverty targeting tools have become common tools for beneficiary targeting and poverty assessment where full means tests are costly. Currently popular estimation procedures for generating these tools prioritize minimization of in-sample prediction errors; however, the objective in generating such tools is out-of-sample prediction. We present evidence that prioritizing minimal out-of-sample error, identified through cross-validation and stochastic ensemble methods, in PMT tool development can substantially improve the out-of-sample performance of these targeting tools. We take the United States Agency for International Development (USAID) poverty assessment tool and base data for demonstration of these methods; however, the methods applied in this paper should be considered for PMT and other poverty-targeting tool development more broadly.

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