Lights, Camera,... Income!: Estimating Poverty Using National Accounts, Survey Means, and Lights

Maxim Pinkovskiy and Xavier Sala-i-Martin

No 19831, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: In this paper we try to understand whether national accounts GDP per capita or survey mean income or consumption better proxy for true income per capita. We propose a data-driven method to assess the relative quality of GDP per capita versus survey means by comparing the evolution of each series to the evolution of satellite-recorded nighttime lights. Our main assumption, which is robust to a variety of specification checks, is that the measurement error in nighttime lights is unrelated to the measurement errors in either national accounts or survey means. We obtain estimates of weights on national accounts and survey means in an optimal proxy for true income; these weights are very large for national accounts and very modest for survey means. We conclusively reject the null hypothesis that the optimal weight on surveys is greater than the optimal weight on national accounts, and we generally fail to reject the null hypothesis that the optimal weight on surveys is zero. Using the estimated optimal weights, we compute estimates of true income per capita and $1/day poverty rates for the developing world and its regions. We get poverty estimates that are substantially lower and fall substantially faster than those of Chen and Ravallion (2010) or of the survey-based poverty literature more generally.

JEL-codes: D31 E01 O1 O4 (search for similar items in EconPapers)
Date: 2014-01
Note: DEV EFG
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

Published as Lights, Camera, … Income! Illuminating the National Accounts-Household Surveys Debate With Xavier Sala-i-Martin The Quarterly Journal of Economics, 131 (2): 579-631, May 2016

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Working Paper: Lights, camera,...income! Estimating poverty using national accounts, survey means, and lights (2014)
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