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

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  • Maxim Pinkovskiy
  • Xavier Sala-i-Martin
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

  • Maxim Pinkovskiy & Xavier Sala-i-Martin, 2014. "Lights, Camera,... Income!: Estimating Poverty Using National Accounts, Survey Means, and Lights," NBER Working Papers 19831, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:19831
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    Cited by:

    1. Paola Pena & Joaquin A. Urrego & Juan M. Villa, 2015. "Civil Conflict and Antipoverty Programmes: Effects on Demobilisation," Documentos de Trabajo de Valor Público 12748, Universidad EAFIT.
    2. John Gibson, 2016. "Poverty Measurement: We Know Less than Policy Makers Realize," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 3(3), pages 430-442, September.
    3. Bluhm, Richard & Krause, Melanie, 2022. "Top lights: Bright cities and their contribution to economic development," Journal of Development Economics, Elsevier, vol. 157(C).
    4. Lionel Roger, 2018. "Blinded by the light? Heterogeneity in the luminosity-growth nexus and the African growth miracle," Discussion Papers 2018-04, University of Nottingham, CREDIT.
    5. Shimeles, Abebe, 2014. "Growth and Poverty in Africa: Shifting Fortunes and New Perspectives," IZA Discussion Papers 8751, Institute of Labor Economics (IZA).
    6. Villa, Juan M., 2014. "Social transfers and growth: The missing evidence from luminosity data," WIDER Working Paper Series 090, World Institute for Development Economic Research (UNU-WIDER).
    7. Alberto Alesina & Stelios Michalopoulos & Elias Papaioannou, 2016. "Ethnic Inequality," Journal of Political Economy, University of Chicago Press, vol. 124(2), pages 428-488.
    8. Roger Fouquet & Stephen Broadberry, 2015. "Seven Centuries of European Economic Growth and Decline," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 227-244, Fall.
    9. Anna Orthofer, 2017. "Concepts and Measures of Saving: Selected Issues for South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 85(2), pages 222-241, June.
    10. Juan M. Villa, 2014. "Social Transfers and Growth: The Missing Evidence from Luminosity Data," WIDER Working Paper Series wp-2014-090, World Institute for Development Economic Research (UNU-WIDER).
    11. John Gibson & Chao Li, 2017. "The Erroneous Use Of China'S Population And Per Capita Data: A Structured Review And Critical Test," Journal of Economic Surveys, Wiley Blackwell, vol. 31(4), pages 905-922, September.
    12. Anthony Mveyange & Christian Skovsgaard & Tine Lesner, 2015. "Does HIV/AIDS matter for economic growth in sub-Saharan Africa?," WIDER Working Paper Series wp-2015-086, World Institute for Development Economic Research (UNU-WIDER).
    13. Anthony Mveyange, 2015. "Night lights and regional income inequality in Africa," WIDER Working Paper Series 085, World Institute for Development Economic Research (UNU-WIDER).
    14. Klemens,Ben & Coppola,Andrea & Shron,Max, 2015. "Estimating local poverty measures using satellite images : a pilot application to Central America," Policy Research Working Paper Series 7329, The World Bank.
    15. Madalina-Gabriela Anghel & Alexandru Manole & Alina-Georgiana Solomon, 2017. "Using the System of National Accounts in the Forecasting Activity," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 7(2), pages 91-96, April.
    16. Bergs, Rolf, 2016. "Exploring the Spatial Economy by Night," MPRA Paper 69764, University Library of Munich, Germany, revised 28 Feb 2016.
    17. Stelios Michalopoulos & Elias Papaioannou, 2020. "Historical Legacies and African Development," Journal of Economic Literature, American Economic Association, vol. 58(1), pages 53-128, March.
    18. Basihos, Seda, 2016. "Nightlights as a Development Indicator: The Estimation of Gross Provincial Product (GPP) in Turkey," MPRA Paper 75553, University Library of Munich, Germany, revised 09 Sep 2016.
    19. Anthony Mveyange & Christian Skovsgaard & Tine Lesner, 2015. "Does HIV/AIDS matter for economic growth in sub-Saharan Africa?," WIDER Working Paper Series 086, World Institute for Development Economic Research (UNU-WIDER).
    20. Moatsos Michail, 2016. "Global Absolute Poverty: Behind the Veil of Dollars," Journal of Globalization and Development, De Gruyter, vol. 7(2), pages 1-28, December.
    21. Artem Kochnev, 2019. "Dying Light: War and Trade of the Separatist-Controlled Areas of Ukraine," wiiw Working Papers 161, The Vienna Institute for International Economic Studies, wiiw.
    22. Anthony Mveyange, 2015. "Night lights and regional income inequality in Africa," WIDER Working Paper Series wp-2015-085, World Institute for Development Economic Research (UNU-WIDER).

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    More about this item

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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