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Why Is Growth in Developing Countries So Hard to Measure?

Author

Listed:
  • Noam Angrist
  • Pinelopi Koujianou Goldberg
  • Dean Jolliffe

Abstract

Occasional widely publicized controversies have led to the perception that growth statistics from developing countries are not to be trusted. Based on the comparison of several data sources and analysis of novel IMF audit data, we find no support for the view that growth is on average measured less accurately or manipulated more in developing than in developed countries. While developing countries face many challenges in measuring growth, so do higher-income countries, especially those with complex and sometimes rapidly changing economic structures. However, we find consistently higher dispersion of growth estimates from developing countries, lending support to the view that classical measurement error is more problematic in poorer countries and that a few outliers may have had a disproportionate effect on (mis)measurement perceptions. We identify several measurement challenges that are specific to poorer countries, namely limited statistical capacity, the use of outdated data and methods, the large share of the agricultural sector, the informal economy, and limited price data. We show that growth measurement based on the System of National Accounts (SNA) can be improved if supplemented with information from other data sources (for example, satellite-based data on vegetation yields) that address some of the limitations of SNA.

Suggested Citation

  • Noam Angrist & Pinelopi Koujianou Goldberg & Dean Jolliffe, 2021. "Why Is Growth in Developing Countries So Hard to Measure?," Journal of Economic Perspectives, American Economic Association, vol. 35(3), pages 215-242, Summer.
  • Handle: RePEc:aea:jecper:v:35:y:2021:i:3:p:215-42
    DOI: 10.1257/jep.35.3.215
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    Citations

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    Cited by:

    1. Contreras , Ivette & Khamis, Melanie & Newhouse, David & Weber, Michael, 2023. "How Did Countries Respond to the COVID-19 Crisis? Emerging Patterns on Jobs-Relates Policies," Jobs Group Papers, Notes, and Guides 32579893, The World Bank.
    2. Dang, Hai-Anh H. & Pullinger, John & Serajuddin, Umar & Stacy, Brian, 2024. "Reviewing Assessment Tools for Measuring Country Statistical Capacity," GLO Discussion Paper Series 1383, Global Labor Organization (GLO).
    3. Dang, Hai Anh H. & Jolliffe, Dean & Serajuddin, Umar & Stacy, Brian, 2024. "Country statistical capacity: a recent assessment tool and further reflections on the way forward," LSE Research Online Documents on Economics 124060, London School of Economics and Political Science, LSE Library.
    4. Shapiro, Daniel & Oh, Chang Hoon & Zhang, Peng, 2023. "Nighttime lights data and their implications for IB research," Journal of International Management, Elsevier, vol. 29(5).
    5. GIBSON, John & ZHANG, Xiaoxuan & PARK, Albert & YI, Jiang & XI, Li, 2024. "Remotely measuring rural economic activity and poverty : Do we just need better sensors?," CEI Working Paper Series 2023-08, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    6. Yuanyuan Gu & Jhorland Ayala-García, 2022. "Emigration and Tax Revenue," Documentos de trabajo sobre Economía Regional y Urbana 312, Banco de la Republica de Colombia.
    7. Prydz, Espen Beer & Jolliffe, Dean & Serajuddin, Umar, 2021. "Mind the Gap," GLO Discussion Paper Series 944, Global Labor Organization (GLO).
    8. Espen Beer Prydz & Dean Jolliffe & Umar Serajuddin, 2022. "Disparities in Assessments of Living Standards Using National Accounts and Household Surveys," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(S2), pages 385-420, December.
    9. Gong, Da & Shang, Zhuocheng & Su, Yaqin & Yan, Andong & Zhang, Qi, 2024. "Economic impacts of China's zero-COVID policies," China Economic Review, Elsevier, vol. 83(C).
    10. Omoniyi Alimi & Geua Boe-Gibson & John Gibson, 2022. "Noisy Night Lights Data: Effects on Research Findings for Developing Countries," Working Papers in Economics 22/12, University of Waikato.
    11. Blankespoor,Brian & Ru,Yating & Wood-Sichra,Ulrike & Chambers,Thomas Timothy & You,Liangzhi & Kalvelagen,Erwin, 2022. "Estimating Local Agricultural GDP across the World," Policy Research Working Paper Series 10109, The World Bank.

    More about this item

    JEL classification:

    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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