IDEAS home Printed from https://ideas.repec.org/a/wej/wldecn/679.html

Making Data Measurement Errors Transparent: The Case of the IMF

Author

Listed:
  • Peter A.G. van Bergeijk

Abstract

In 1950 Morgenstern pointed out that absolute precision and certainty are impossible in economic observations, but estimates are often hampered by a substantial degree of measurement error. Unlike the natural sciences, economists in general do not report measurement errors for the key concepts such as prices, value or production that it seeks to define, measure and explain. For most macroeconomic concepts two approaches are available: the Implicit Minimal Measurement Error and the Maximum Ratio. Studying different vintages of the IMF World Economic Outlook data base it was found that the estimates on average have an implicit minimal measurement error of 4.3% and maximum ratio of 17.9%. An agenda is proposed for removing disincentives (creating incentives) for stakeholders (academics, data collectors and producers) since reporting measurement error will result in better research, better policy and ultimately better data.

Suggested Citation

  • Peter A.G. van Bergeijk, 2017. "Making Data Measurement Errors Transparent: The Case of the IMF," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 18(3), pages 133-154, July.
    • Handle: RePEc:wej:wldecn:679
    as

    Download full text from publisher

    File URL: https://www.world-economics-journal.com/Papers/Details.aspx?ID=679
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sinclair, Tara M. & Stekler, H.O., 2013. "Examining the quality of early GDP component estimates," International Journal of Forecasting, Elsevier, vol. 29(4), pages 736-750.
    2. Susanne M. Schennach, 2016. "Recent Advances in the Measurement Error Literature," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 341-377, October.
    3. Bruce D. Meyer & Wallace K. C. Mok & James X. Sullivan, 2015. "Household Surveys in Crisis," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 199-226, Fall.
    4. Laurent Ferrara, 2013. "Comments on: Examining the quality of early GDP component estimates," Post-Print hal-01385874, HAL.
    5. 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.
    6. Mark Bils, 2017. "Misallocation or Mismeasurement?," 2017 Meeting Papers 715, Society for Economic Dynamics.
    7. Peter A.G. van Bergeijk, 2009. "Economic Diplomacy and the Geography of International Trade," Books, Edward Elgar Publishing, number 13518, June.
    8. John M. Abowd & Martha H. Stinson, 2013. "Estimating Measurement Error in Annual Job Earnings: A Comparison of Survey and Administrative Data," The Review of Economics and Statistics, MIT Press, vol. 95(5), pages 1451-1467, December.
    9. Blattman, Christopher & Jamison, Julian & Koroknay-Palicz, Tricia & Rodrigues, Katherine & Sheridan, Margaret, 2016. "Measuring the measurement error: A method to qualitatively validate survey data," Journal of Development Economics, Elsevier, vol. 120(C), pages 99-112.
    10. Hendrik Wolff & Howard Chong & Maximilian Auffhammer, 2011. "Classification, Detection and Consequences of Data Error: Evidence from the Human Development Index," Economic Journal, Royal Economic Society, vol. 121(553), pages 843-870, June.
    11. Verónica Cañal-Fernández, 2012. "Accuracy and reliability of Spanish regional accounts (CRE-95)," Empirical Economics, Springer, vol. 43(3), pages 1299-1320, December.
    12. Peter A.G. van Bergeijk, 2010. "On the Brink of Deglobalization," Books, Edward Elgar Publishing, number 14122, June.
    13. Marcel Boumans, 2012. "Observations in a Hostile Environment: Morgenstern on the Accuracy of Economic Observations," History of Political Economy, Duke University Press, vol. 44(5), pages 114-136, Supplemen.
    14. Martin Eichenbaum & Nir Jaimovich & Sergio Rebelo & Josephine Smith, 2014. "How Frequent Are Small Price Changes?," American Economic Journal: Macroeconomics, American Economic Association, vol. 6(2), pages 137-155, April.
    15. Peter Egger & Jan Průša, 2016. "The determinants of trade costs: a random coefficient approach," Empirical Economics, Springer, vol. 50(1), pages 51-58, February.
    16. John Gibson & Kathleen Beegle & Joachim De Weerdt & Jed Friedman, 2015. "What does Variation in Survey Design Reveal about the Nature of Measurement Errors in Household Consumption?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(3), pages 466-474, June.
    17. Dean Croushore, 2011. "Frontiers of Real-Time Data Analysis," Journal of Economic Literature, American Economic Association, vol. 49(1), pages 72-100, March.
    18. Alexander W. Salter & Daniel J. Smith, 2017. "What You Don'T Know Can Hurt You: Knowledge Problems In Monetary Policy," Contemporary Economic Policy, Western Economic Association International, vol. 35(3), pages 505-517, July.
    19. Donal O’Neill & Olive Sweetman, 2013. "The consequences of measurement error when estimating the impact of obesity on income," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 2(1), pages 1-20, December.
    20. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2016. "Learning from Potentially Biased Statistics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 52(1 (Spring), pages 59-108.
    21. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2016. "Learning from Potentially Biased Statistics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(1 (Spring), pages 59-108.
    22. Maxim L. Pinkovskiy & Xavier X. Sala-i-Martin, 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.
    23. Jacobs, Jan P.A.M. & van Norden, Simon, 2011. "Modeling data revisions: Measurement error and dynamics of "true" values," Journal of Econometrics, Elsevier, vol. 161(2), pages 101-109, April.
    24. Peter A.G. van Bergeijk, 2013. "Earth Economics," Books, Edward Elgar Publishing, number 14673, June.
    25. Boumans, Marcel, 2015. "Science Outside the Laboratory: Measurement in Field Science and Economics," OUP Catalogue, Oxford University Press, number 9780199388288.
    26. Alberto Cavallo & Guillermo Cruces & Ricardo Perez-Truglia, 2016. "Learning from Potentially-Biased Statistics: Household Inflation Perceptions and Expectations in Argentina," NBER Working Papers 22103, National Bureau of Economic Research, Inc.
    27. Carletto, Calogero & Savastano, Sara & Zezza, Alberto, 2013. "Fact or artifact: The impact of measurement errors on the farm size–productivity relationship," Journal of Development Economics, Elsevier, vol. 103(C), pages 254-261.
    28. Cawley, John & Maclean, Johanna Catherine & Hammer, Mette & Wintfeld, Neil, 2015. "Reporting error in weight and its implications for bias in economic models," Economics & Human Biology, Elsevier, vol. 19(C), pages 27-44.
    29. Francisco Benita & Carlos M. Urzúa, 2016. "Mirror trade statistics between China and Latin America," Journal of Chinese Economic and Foreign Trade Studies, Emerald Group Publishing Limited, vol. 9(3), pages 177-189, October.
    30. Philipp Bagus, 2011. "Morgenstern's Forgotten Contribution: A Stab to the Heart of Modern Economics," American Journal of Economics and Sociology, Wiley Blackwell, vol. 70(2), pages 540-562, April.
    31. Aruoba, S. Borağan & Diebold, Francis X. & Nalewaik, Jeremy & Schorfheide, Frank & Song, Dongho, 2016. "Improving GDP measurement: A measurement-error perspective," Journal of Econometrics, Elsevier, vol. 191(2), pages 384-397.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Peter A.G. van Bergeijk, 2021. "Pandemic Economics," Books, Edward Elgar Publishing, number 20401, June.
    2. van Bergeijk, P.A.G., 2018. "China’s economic hegemony (1-2050 AD)," ISS Working Papers - General Series 637, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. van Bergeijk, P.A.G., 2017. "Measurement error of global production," ISS Working Papers - General Series 632, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    2. Mazzi Gian Luigi & Mitchell James & Carausu Florabela, 2021. "Measuring and Communicating the Uncertainty in Official Economic Statistics," Journal of Official Statistics, Sciendo, vol. 37(2), pages 289-316, June.
    3. Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 151-178, Spring.
    4. Andrew C. Chang & Phillip Li, 2018. "Measurement Error In Macroeconomic Data And Economics Research: Data Revisions, Gross Domestic Product, And Gross Domestic Income," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1846-1869, July.
    5. Ana Beatriz Galvão & James Mitchell, 2019. "Measuring Data Uncertainty: An Application using the Bank of England's "Fan Charts" for Historical GDP Growth," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-08, Economic Statistics Centre of Excellence (ESCoE).
    6. Pappalardo, Gioacchino & West, Grant Howard & Nayga, Rodolfo M. & Toscano, Sabrina & Pecorino, Biagio, 2022. "The effect of a UNESCO world heritage site designation on willingness to pay to preserve an agri-environmental good: The case of the dry stone walls in Mt. Etna," Land Use Policy, Elsevier, vol. 114(C).
    7. Das, Abhiman & Lahiri, Kajal & Zhao, Yongchen, 2019. "Inflation expectations in India: Learning from household tendency surveys," International Journal of Forecasting, Elsevier, vol. 35(3), pages 980-993.
    8. Miranda-Zanetti, Maximilano & Delbianco, Fernando & Tohmé, Fernando, 2019. "Tampering with inflation data: A Benford law-based analysis of national statistics in Argentina," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 761-770.
    9. Ha Trong Nguyen & Huong Thu Le & Luke Connelly & Francis Mitrou, 2023. "Accuracy of self‐reported private health insurance coverage," Health Economics, John Wiley & Sons, Ltd., vol. 32(12), pages 2709-2729, December.
    10. Ana Beatriz Galvão & James Mitchell & Johnny Runge, 2019. "Communicating Data Uncertainty: Experimental Evidence for U.K. GDP," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2019-20, Economic Statistics Centre of Excellence (ESCoE).
    11. Jan P.A.M. Jacobs & Samad Sarferaz & Simon van Norden & Jan-Egbert Sturm, 2013. "Modeling Multivariate Data Revisions," CIRANO Working Papers 2013s-44, CIRANO.
    12. De Magalhães, Leandro & Santaeulàlia-Llopis, Raül, 2018. "The consumption, income, and wealth of the poorest: An empirical analysis of economic inequality in rural and urban Sub-Saharan Africa for macroeconomists," Journal of Development Economics, Elsevier, vol. 134(C), pages 350-371.
    13. Alberto Cavallo, 2017. "Are Online and Offline Prices Similar? Evidence from Large Multi-channel Retailers," American Economic Review, American Economic Association, vol. 107(1), pages 283-303, January.
    14. Abay, Kibrom A. & Ayalew, Hailemariam & Terfa, Zelalem & Karugia, Joseph & Breisinger, Clemens, 2025. "How good are livestock statistics in Africa? Can nudging and direct counting improve the quality of livestock asset data?," Journal of Development Economics, Elsevier, vol. 176(C).
    15. Dong, Hao & Millimet, Daniel L., 2023. "Embrace the Noise: It Is OK to Ignore Measurement Error in a Covariate, Sometimes," IZA Discussion Papers 16508, IZA Network @ LISER.
    16. Davillas, Apostolos & Jones, Andrew M., 2021. "The implications of self-reported body weight and height for measurement error in BMI," Economics Letters, Elsevier, vol. 209(C).
    17. Dean Croushore, 2009. "Commentary on Estimating U.S. output growth with vintage data in a state-space framework," Review, Federal Reserve Bank of St. Louis, vol. 91(Jul), pages 371-382.
    18. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    19. Evan S. Totty & Thor Watson, 2026. "Privacy Protection and Accuracy: What Do We Know? Do We Know Things?? Let’s Find Out!," NBER Chapters, in: Data Privacy Protection and the Conduct of Applied Research: Methods, Approaches and New Findings, National Bureau of Economic Research, Inc.
    20. Sinclair, Tara M., 2019. "Characteristics and implications of Chinese macroeconomic data revisions," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1108-1117.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wej:wldecn:679. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ed Jones (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.