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GDP Solera. The Ideal Vintage Mix

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We exploit the information in the successive vintages of GDE and GDI from the current comprehensive revision to obtain an improved timely measure of US aggregate output by exploiting cointegration between the different measures and taking seriously their monthly release calendar. We also combine all existing overlapping comprehensive revisions to achieve further improvements. We pay particular attention to the Great Recession and the pandemic, which, despite producing dramatic fluctuations, does not generate noticeable revisions in previous growth rates. The estimated parameters of our dynamic state-space model suggest that comprehensive revisions have not changed the long-run growth rate of US GDP.

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  • Martín Almuzara & Dante Amengual & Gabriele Fiorentini & Enrique Sentana, 2022. "GDP Solera. The Ideal Vintage Mix," Working Papers wp2022_2204, CEMFI.
  • Handle: RePEc:cmf:wpaper:wp2022_2204
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    1. S. Borağan Aruoba, 2008. "Data Revisions Are Not Well Behaved," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(2‐3), pages 319-340, March.
    2. Ryan Greenaway-McGrevy, 2011. "Is GDP or GDI a better measure of output? A statistical approach," BEA Working Papers 0076, Bureau of Economic Analysis.
    3. 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.
    4. Gabriele Fiorentini & Enrique Sentana, 2019. "Dynamic specification tests for dynamic factor models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 325-346, April.
    5. John Y. Campbell & N. Gregory Mankiw, 1987. "Are Output Fluctuations Transitory?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(4), pages 857-880.
    6. Athanasios Orphanides, 2001. "Monetary Policy Rules Based on Real-Time Data," American Economic Review, American Economic Association, vol. 91(4), pages 964-985, September.
    7. 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.
    8. J. Steven Landefeld & Eugene P. Seskin & Barbara M. Fraumeni, 2008. "Taking the Pulse of the Economy: Measuring GDP," Journal of Economic Perspectives, American Economic Association, vol. 22(2), pages 193-216, Spring.
    9. 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.
    10. Richard Stone & D. G. Champernowne & J. E. Meade, 1942. "The Precision of National Income Estimates," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 9(2), pages 111-125.
    11. Richard J. Smith & Martin R. Weale & Steven E. Satchell, 1998. "Measurement Error with Accounting Constraints: Point and Interval Estimation for Latent Data with an Application to U.K. Gross Domestic Product," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(1), pages 109-134.
    12. Bruce T. Grimm, 2007. "The Statistical Discrepancy," BEA Papers 0071, Bureau of Economic Analysis.
    13. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
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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.

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    More about this item

    Keywords

    Cointegration; Comprehensive revisions; Signal extraction; US aggregate output; Vintages.;
    All these keywords.

    JEL classification:

    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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