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Ex Post and Ex Ante Analysis of Provisional Data

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  • Giampiero M. Gallo
  • Massimiliano Marcellino

Abstract

In this paper we suggest a framework to assess the degree of reliability of provisional estimates as forecasts of final data, and we reexamine the question of the most appropriate way in which available data should be used for ex ante forecasting in the presence of a data revision process. Various desirable properties for provisional data are suggested, as well as procedures for testing them, taking into account the possible nonstationarity of economic variables. For illustration, the methodology is applied to assess the quality of the US M1 data production process and to derive a conditional model whose performance in forecasting is then tested against other alternatives based on simple transformations of provisional data or of past final data.

Suggested Citation

  • Giampiero M. Gallo & Massimiliano Marcellino, "undated". "Ex Post and Ex Ante Analysis of Provisional Data," Working Papers 141, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    • Handle: RePEc:igi:igierp:141
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    References listed on IDEAS

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    1. Maravall, Agustin & Pierce, David A, 1986. "The Transmission of Data Noise into Policy Noise in U.S. Monetary Control," Econometrica, Econometric Society, vol. 54(4), pages 961-979, July.
    2. Kenneth A. Kavajecz, 1994. "The evolution of the Federal Reserve's monetary aggregates: a timeline," Proceedings, Federal Reserve Bank of St. Louis, issue Mar, pages 32-66.
    3. Kavajecz, Kenneth & Collins, Sean, 1995. "Rationality of Preliminary Money Stock Estimates," The Review of Economics and Statistics, MIT Press, vol. 77(1), pages 32-41, February.
    4. Boschen, John F. & Grossman, Herschel I., 1982. "Tests of equilibrium macroeconomics using contemporaneous monetary data," Journal of Monetary Economics, Elsevier, vol. 10(3), pages 309-333.
    5. Richard G. Anderson & Kenneth A. Kavajecz, 1994. "A historical perspective on the Federal Reserve's monetary aggregates: definition, construction and targeting," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 1-31.
    6. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    7. Osterwald-Lenum, Michael, 1992. "A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(3), pages 461-472, August.
    8. Hakkio, Craig S. & Rush, Mark, 1989. "Market efficiency and cointegration: an application to the sterling and deutschemark exchange markets," Journal of International Money and Finance, Elsevier, vol. 8(1), pages 75-88, March.
    9. Barro, Robert J. & Hercowitz, Zvi, 1980. "Money stock revisions and unanticipated money growth," Journal of Monetary Economics, Elsevier, vol. 6(2), pages 257-267, April.
    10. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    11. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    12. Richard G. Anderson & Kenneth A. Kavajecz, 1994. "A historical perspective on the Federal Reserve's monetary aggregates," Working Papers 1994-006, Federal Reserve Bank of St. Louis.
    13. Spanos,Aris, 1986. "Statistical Foundations of Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521269124, October.
    14. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    15. Hamilton, James D & Perez-Quiros, Gabriel, 1996. "What Do the Leading Indicators Lead?," The Journal of Business, University of Chicago Press, vol. 69(1), pages 27-49, January.
    16. Hansen, Bruce E, 1997. "Approximate Asymptotic P Values for Structural-Change Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 60-67, January.
    17. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    18. Patterson, Kerry D & Heravi, Saeed M, 1991. "Data Revisions and the Expenditure Components of GDP," Economic Journal, Royal Economic Society, vol. 101(407), pages 887-901, July.
    19. Kenneth A. Kavajecz, 1994. "The evolution of the Federal Reserve's monetary aggregates: a timeline," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 32-66.
    20. Hamilton, James D., 1988. "Rational-expectations econometric analysis of changes in regime : An investigation of the term structure of interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 385-423.
    21. Francis X. Diebold & Glenn D. Rudebusch, 1989. "Forecasting output with the composite leading index: an ex ante analysis," Finance and Economics Discussion Series 90, Board of Governors of the Federal Reserve System (U.S.).
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    Cited by:

    1. Fabio Busetti, 2001. "The use of preliminary data in econometric forecasting: an application with the Bank of Italy Quarterly Model," Temi di discussione (Economic working papers) 437, Bank of Italy, Economic Research and International Relations Area.
    2. Andres Fernandez & Norman R. Swanson, 2009. "Real-time datasets really do make a difference: definitional change, data release, and forecasting," Working Papers 09-28, Federal Reserve Bank of Philadelphia.
    3. Fabio Busetti, 2006. "Preliminary data and econometric forecasting: an application with the Bank of Italy Quarterly Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 1-23.
    4. 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.

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