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Statistical capacity and corrupt bureaucracies

Author

Listed:
  • Manuel Oechslin

    (Department of Economics)

  • Elias Steiner

    (Department of Economics)

Abstract

In many developing countries, economic statistics (such as the growth rate of GDP) are imprecise, making it difficult to evaluate economic reforms and learn “what works”. Improving economic statistics has thus become a priority of international organizations. In this paper, we isolate an insidious mechanism—a type of observer effect—by which a push for better statistics can make matters worse. Precise statistics require the collection of data from a large number of firms. If firms suspect that detailed information, when spreading through the bureaucracy, is misused to collect bribes, they have weaker incentives to invest. As a result, the effects of reforms are muted, making it even harder to discover “what works”. To suppress this mechanism, efforts to improve economic statistics should be comprehensive and also include institutional aspects.

Suggested Citation

  • Manuel Oechslin & Elias Steiner, 2022. "Statistical capacity and corrupt bureaucracies," The Review of International Organizations, Springer, vol. 17(1), pages 143-174, January.
    • Handle: RePEc:spr:revint:v:17:y:2022:i:1:d:10.1007_s11558-021-09421-5
    DOI: 10.1007/s11558-021-09421-5
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    1. Giovanni Immordino & Marco Pagano, 2010. "Legal Standards, Enforcement, and Corruption," Journal of the European Economic Association, MIT Press, vol. 8(5), pages 1104-1132, September.
    2. Paunov, Caroline, 2016. "Corruption's asymmetric impacts on firm innovation," Journal of Development Economics, Elsevier, vol. 118(C), pages 216-231.
    3. Emanuele Colonnelli & Mounu Prem, 2022. "Corruption and Firms [Mafia and Public Spending: Evidence on the Fiscal Multiplier from a Quasi-experiment]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(2), pages 695-732.
    4. Jakob Svensson, 2003. "Who Must Pay Bribes and How Much? Evidence from a Cross Section of Firms," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 207-230.
    5. Zakharov, Nikita, 2019. "Does corruption hinder investment? Evidence from Russian regions," European Journal of Political Economy, Elsevier, vol. 56(C), pages 39-61.
    6. Hodler, Roland & Raschky, Paul A., 2014. "Economic shocks and civil conflict at the regional level," Economics Letters, Elsevier, vol. 124(3), pages 530-533.
    7. Charles F. Manski, 2015. "Communicating Uncertainty in Official Economic Statistics: An Appraisal Fifty Years after Morgenstern," Journal of Economic Literature, American Economic Association, vol. 53(3), pages 631-653, September.
    8. Estrin, Saul & Korosteleva, Julia & Mickiewicz, Tomasz, 2013. "Which institutions encourage entrepreneurial growth aspirations?," Journal of Business Venturing, Elsevier, vol. 28(4), pages 564-580.
    9. Hans Pitlik & Björn Frank & Mathias Firchow, 2010. "The demand for transparency: An empirical note," The Review of International Organizations, Springer, vol. 5(2), pages 177-195, June.
    10. Andrew Kerner & Morten Jerven & Alison Beatty, 2017. "Does it pay to be poor? Testing for systematically underreported GNI estimates," The Review of International Organizations, Springer, vol. 12(1), pages 1-38, March.
    11. Abhijit Banerjee & Rema Hanna & Jordan Kyle & Benjamin A. Olken & Sudarno Sumarto, 2019. "Private Outsourcing and Competition: Subsidized Food Distribution in Indonesia," Journal of Political Economy, University of Chicago Press, vol. 127(1), pages 101-137.
    12. Justin Sandefur & Amanda Glassman, 2015. "The Political Economy of Bad Data: Evidence from African Survey and Administrative Statistics," Journal of Development Studies, Taylor & Francis Journals, vol. 51(2), pages 116-132, February.
    13. 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.
    14. Barro, Robert J, 1990. "Government Spending in a Simple Model of Endogenous Growth," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 103-126, October.
    15. Dani Rodrik, 2010. "Diagnostics before Prescription," Journal of Economic Perspectives, American Economic Association, vol. 24(3), pages 33-44, Summer.
    16. Benjamin A. Olken & Rohini Pande, 2012. "Corruption in Developing Countries," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 479-509, July.
    17. Johannes Binswanger & Manuel Oechslin, 2015. "Disagreement and Learning about Reforms," Economic Journal, Royal Economic Society, vol. 0(584), pages 853-886, May.
    18. Caroline Freund & Mary Hallward-Driemeier & Bob Rijkers, 2016. "Deals and Delays: Firm-level Evidence on Corruption and Policy Implementation Times," The World Bank Economic Review, World Bank, vol. 30(2), pages 354-382.
    19. Beekman, Gonne & Bulte, Erwin & Nillesen, Eleonora, 2014. "Corruption, investments and contributions to public goods: Experimental evidence from rural Liberia," Journal of Public Economics, Elsevier, vol. 115(C), pages 37-47.
    20. Karthik Muralidharan & Paul Niehaus, 2017. "Experimentation at Scale," Journal of Economic Perspectives, American Economic Association, vol. 31(4), pages 103-124, Fall.
    21. Malesky, Edmund J. & Samphantharak, Krislert, 2008. "Predictable Corruption and Firm Investment: Evidence from a Natural Experiment and Survey of Cambodian Entrepreneurs," Quarterly Journal of Political Science, now publishers, vol. 3(3), pages 227-267, October.
    22. Jie Bai & Seema Jayachandran & Edmund J Malesky & Benjamin A Olken, 2019. "Firm Growth and Corruption: Empirical Evidence from Vietnam," The Economic Journal, Royal Economic Society, vol. 129(618), pages 651-677.
    23. Fisman, Raymond & Svensson, Jakob, 2007. "Are corruption and taxation really harmful to growth? Firm level evidence," Journal of Development Economics, Elsevier, vol. 83(1), pages 63-75, May.
    24. Binswanger, Johannes & Oechslin, Manuel, 2020. "Better statistics, better economic policies?," European Economic Review, Elsevier, vol. 130(C).
    25. Hainmueller, Jens & Mummolo, Jonathan & Xu, Yiqing, 2019. "How Much Should We Trust Estimates from Multiplicative Interaction Models? Simple Tools to Improve Empirical Practice," Political Analysis, Cambridge University Press, vol. 27(2), pages 163-192, April.
    26. Francien Berry & Massimiliano Iommi & Mr. Michael Stanger & Louis Venter, 2018. "The Status of GDP Compilation Practices in 189 Economies and the Relevance for Policy Analysis," IMF Working Papers 2018/037, International Monetary Fund.
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    More about this item

    Keywords

    Economic statistics; Experimentation; Informativeness; Corruption; Observer effect;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts

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