Arbeitspapier

Lights, camera...income!: Estimating poverty using national accounts, survey means, and lights

In this paper, we try to understand whether measures of GDP per capita taken from the national accounts or measures of mean income or consumption derived from household surveys 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-a-day poverty rates for the developing world and its regions. We obtain poverty estimates that are substantially lower and fall substantially faster than those of Chen and Ravallion (2010) specifically or of the survey-based poverty literature more generally.

Language
Englisch

Bibliographic citation
Series: Staff Report ; No. 669

Classification
Wirtschaft
Personal Income, Wealth, and Their Distributions
Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
Subject
economic growth
development

Event
Geistige Schöpfung
(who)
Pinkovskiy, Maxim
Sala-i-Martin, Xavier
Event
Veröffentlichung
(who)
Federal Reserve Bank of New York
(where)
New York, NY
(when)
2014

Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Pinkovskiy, Maxim
  • Sala-i-Martin, Xavier
  • Federal Reserve Bank of New York

Time of origin

  • 2014

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