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Lights, Camera … Income! Illuminating the National Accounts-Household Surveys Debate

Author

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  • Maxim Pinkovskiy
  • Xavier Sala-i-Martin

Abstract

GDP per capita and household survey means present conflicting pictures of the rate of economic development in emerging countries. One of the areas in which the national accounts–household surveys debate is key is the measurement of developing world poverty. We propose a data-driven method to assess the relative quality of GDP per capita and survey means by comparing them 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. Additionally, we provide evidence that national accounts are good indicators of desirable outcomes for the poor (such as longer life expectancy, better education and access to safe water), and we show that surveys appear to perform worse in developing countries that are richer and that are growing faster. Therefore, we interpret our results as providing support for estimates of world poverty that are based on national accounts. JEL Code: I32.

Suggested Citation

  • Maxim Pinkovskiy & Xavier Sala-i-Martin, 2016. "Lights, Camera … Income! Illuminating the National Accounts-Household Surveys Debate," The Quarterly Journal of Economics, Oxford University Press, vol. 131(2), pages 579-631.
  • Handle: RePEc:oup:qjecon:v:131:y:2016:i:2:p:579-631.
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    File URL: http://hdl.handle.net/10.1093/qje/qjw003
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    Citations

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    Cited by:

    1. Pinkovskiy, Maxim L. & Sala-i-Martin, Xavier X., 2016. "Newer need not be better: evaluating the Penn World Tables and the World Development Indicators using nighttime lights," Staff Reports 778, Federal Reserve Bank of New York.
    2. Mussa, Richard, 2017. "Poverty in Malawi: Policy Analysis with Distributional Changes," MPRA Paper 75980, University Library of Munich, Germany.
    3. Donna Feir & Rob Gillezeau & Maggie Jones, 2017. "Illuminating Economic Development in Indigenous Communities," Department Discussion Papers 1704, Department of Economics, University of Victoria.
    4. Pfeifer, Gregor & Wahl, Fabian & Marczak, Martyna, 2016. "Illuminating the world cup effect: Night lights evidence from South Africa," Hohenheim Discussion Papers in Business, Economics and Social Sciences 16-2016, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    5. repec:bla:etrans:v:25:y:2017:i:3:p:439-469 is not listed on IDEAS
    6. Brian Nolan & Max Roser & Stefan Thewissen, 2016. "GDP Per Capita Versus Median Household Income: What Gives Rise to Divergence Over Time?," LIS Working papers 672, LIS Cross-National Data Center in Luxembourg.
    7. repec:kap:jecgro:v:22:y:2017:i:2:d:10.1007_s10887-016-9139-2 is not listed on IDEAS
    8. Donna Feir & Rob Gillezeau & Maggie Jones, 2017. "The Slaughter of the North American Bison and Reversal of Fortunes on the Great Plains," Department Discussion Papers 1701, Department of Economics, University of Victoria.
    9. Jaqueson K Galimberti, 2017. "Forecasting GDP growth from the outer space," KOF Working papers 17-427, KOF Swiss Economic Institute, ETH Zurich.
    10. Mussa, Richard, 2017. "To Err is Human: Inconsistencies in Food Conversion Factors and Inequality in Malawi," MPRA Paper 75981, University Library of Munich, Germany.
    11. Doppelhofer, Gernot & Hansen, Ole-Petter Moe & Weeks, Melvyn, 2016. "Determinants of long-term economic Growth redux: A Measurement Error Model Averaging (MEMA) approach," Discussion Paper Series in Economics 19/2016, Norwegian School of Economics, Department of Economics.

    More about this item

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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