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

52 Pages Posted: 25 Jan 2014 Last revised: 1 Sep 2014

See all articles by Maxim Pinkovskiy

Maxim Pinkovskiy

Federal Reserve Bank of New York

Xavier Sala-i-Martin

Columbia University, Graduate School of Arts and Sciences, Department of Economics

Multiple version iconThere are 2 versions of this paper

Date Written: January 2014

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.

Suggested Citation

Pinkovskiy, Maxim and Sala-i-Martin, Francesc Xavier, Lights, Camera,... Income!: Estimating Poverty Using National Accounts, Survey Means, and Lights (January 2014). NBER Working Paper No. w19831. Available at SSRN: https://ssrn.com/abstract=2384290

Maxim Pinkovskiy (Contact Author)

Federal Reserve Bank of New York ( email )

Francesc Xavier Sala-i-Martin

Columbia University, Graduate School of Arts and Sciences, Department of Economics ( email )

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United States
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