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Shining a Light on Purchasing Power Parities

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  • Maxim Pinkovskiy
  • Xavier Sala-i-Martin

Abstract

Nighttime lights data are a measure of economic activity whose error is plausibly independent of the measurement errors of most conventional indicators. Therefore, we can use nighttime lights as an independent benchmark to assess existing measures of economic activity (Pinkovskiy and Sala-i-Martin (2016)). We employ this insight to generate three findings in the study of PPP-adjusted estimates of GDP around the world between 1992 and 2010. First, we find that while market exchange rates described poor economies better than did PPP-adjusted estimates in the late 1990s (Dowrick and Akmal 2008; Almas 2012), this pattern has disappeared by the 2010s. Second, we also find that estimates of PPPs have been steadily improving from one price survey round to the next, including during the controversial 2005 and 2011 rounds. Third, we leverage this fact to assess whether it is optimal to measure relative prices as close as possible to the year of interest or to use the latest available relative price data and discard the rest, and provide a theoretical framework in which the latter may be optimal. Using data from the Penn World Tables, we find that, indeed, it is optimal to only use the latest price data, and hence, to revise existing PPP-adjusted estimates whenever a new price survey is released.

Suggested Citation

  • Maxim Pinkovskiy & Xavier Sala-i-Martin, 2018. "Shining a Light on Purchasing Power Parities," NBER Working Papers 24419, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:24419
    Note: DEV EFG IFM
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    References listed on IDEAS

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    1. Elias Papaioannou, 2014. "National Institutions and Subnational Development in Africa," The Quarterly Journal of Economics, Oxford University Press, vol. 129(1), pages 151-213.
    2. Jerry Hausman, 2001. "Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 57-67, Fall.
    3. Stelios Michalopoulos & Elias Papaioannou, 2013. "Preā€Colonial Ethnic Institutions and Contemporary African Development," Econometrica, Econometric Society, vol. 81(1), pages 113-152, January.
    4. Robert J. Barro, 1991. "Economic Growth in a Cross Section of Countries," The Quarterly Journal of Economics, Oxford University Press, vol. 106(2), pages 407-443.
    5. Johnson, Simon & Larson, William & Papageorgiou, Chris & Subramanian, Arvind, 2013. "Is newer better? Penn World Table Revisions and their impact on growth estimates," Journal of Monetary Economics, Elsevier, vol. 60(2), pages 255-274.
    6. Kravis, Irving B & Heston, Alan W & Summers, Robert, 1978. "Real GDP per Capita for More Than One Hundred Countries," Economic Journal, Royal Economic Society, vol. 88(350), pages 215-242, June.
    7. World Bank, 2006. "World Development Indicators 2006," World Bank Publications, The World Bank, number 8151, September.
    8. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
    9. Doll, Christopher N.H. & Muller, Jan-Peter & Morley, Jeremy G., 2006. "Mapping regional economic activity from night-time light satellite imagery," Ecological Economics, Elsevier, vol. 57(1), pages 75-92, April.
    10. Steve Dowrick & Muhammad Akmal, 2005. "Contradictory Trends In Global Income Inequality: A Tale Of Two Biases," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 51(2), pages 201-229, June.
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    JEL classification:

    • A1 - General Economics and Teaching - - General Economics
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • F00 - International Economics - - General - - - General

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