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Can GDP Measurement Be Further Improved? Data Revision and Reconciliation

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  • Jan P. A. M. Jacobs
  • Samad Sarferaz
  • Jan-Egbert Sturm
  • Simon van Norden

Abstract

Recent years have seen many attempts to combine expenditure-side estimates of U.S. real output (GDE) growth with income-side estimates (GDI) to improve estimates of real GDP growth. We show how to incorporate information from multiple releases of noisy data to provide more precise estimates while avoiding some of the identifying assumptions required in earlier work. This relies on a new insight: using multiple data releases allows us to distinguish news and noise measurement errors in situations where a single vintage does not. We find that (a) the data prefer averaging across multiple releases instead of discarding early releases in favor of later ones, and (b) that initial estimates of GDI are quite informative. Our new measure, GDP++, undergoes smaller revisions and tracks expenditure measures of GDP growth more closely than either the simple average of the expenditure and income measures published by the BEA or the GDP growth measure of Aruoba et al. published by the Federal Reserve Bank of Philadelphia.

Suggested Citation

  • Jan P. A. M. Jacobs & Samad Sarferaz & Jan-Egbert Sturm & Simon van Norden, 2022. "Can GDP Measurement Be Further Improved? Data Revision and Reconciliation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 423-431, January.
    • Handle: RePEc:taf:jnlbes:v:40:y:2022:i:1:p:423-431
    DOI: 10.1080/07350015.2020.1831928
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    References listed on IDEAS

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    1. Martín Almuzara & Gabriele Fiorentini & Enrique Sentana, 2023. "Aggregate Output Measurements: A Common Trend Approach," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 3-33, Emerald Group Publishing Limited.
    2. 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.
    3. Ivana Komunjer & Serena Ng, 2011. "Dynamic Identification of Dynamic Stochastic General Equilibrium Models," Econometrica, Econometric Society, vol. 79(6), pages 1995-2032, November.
    4. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
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    6. Weale, Martin, 1992. "Estimation of Data Measured with Error and Subject to Linear Restrictions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(2), pages 167-174, April-Jun.
    7. Dennis J. Fixler & Jeremy J. Nalewaik, 2007. "News, noise, and estimates of the \"true\" unobserved state of the economy," Finance and Economics Discussion Series 2007-34, Board of Governors of the Federal Reserve System (U.S.).
    8. 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.
    9. Jeremy J. Nalewaik, 2012. "Estimating Probabilities of Recession in Real Time Using GDP and GDI," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 235-253, February.
    10. Daniel M. Rees & David Lancaster & Richard Finlay, 2015. "A State-Space Approach to Australian Gross Domestic Product Measurement," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 48(2), pages 133-149, June.
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    Citations

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    Cited by:

    1. Maria do Rosário Anjos, 2021. "Free Competition and Fiscal Policy in European Union," Journal of International Business Research and Marketing, Inovatus Services Ltd., vol. 6(6), pages 25-30, September.
    2. Ana Beatriz Galvão & James Mitchell, 2023. "Real‐Time Perceptions of Historical GDP Data Uncertainty," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(3), pages 457-481, June.
    3. Sekine, Toshitaka, 2022. "Looking from Gross Domestic Income: Alternative view of Japan’s economy," Japan and the World Economy, Elsevier, vol. 64(C).
    4. James Mitchell & Gary Koop & Stuart McIntyre & Aubrey Poon, 2020. "Reconciled Estimates of Monthly GDP in the US," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-16, Economic Statistics Centre of Excellence (ESCoE).
    5. repec:wrk:wrkemf:37 is not listed on IDEAS
    6. Maria do Rosário Anjos, 2020. "Free Competition and Fiscal Policy in European Union," International Journal of Operations Management, Inovatus Services Ltd., vol. 1(1), pages 49-56, October.
    7. Eiji Goto & Jan P.A.M. Jacobs & Tara M. Sinclair & Simon van Norden, 2023. "Employment reconciliation and nowcasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(7), pages 1007-1017, November.
    8. Zhang, HongWei & Xie, Yuan, 2024. "Assessing natural resources, rebounding trends, digital economic structure and green recovery dynamics in China," Resources Policy, Elsevier, vol. 88(C).
    9. Kurt Graden Lunsford, 2023. "The Discrepancy Between Expenditure- and Income-Side Estimates of US Output," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2023(01), pages 1-7, January.

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    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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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