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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.

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Paper provided by IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University in its series Working Papers with number 141.

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Handle: RePEc:igi:igierp:141

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  1. 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.
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  10. 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.).
  11. 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 461-72, August.
  12. 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 961-79, July.
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  15. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
  16. 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.
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Cited by:
  1. Norman R. Swanson & Andres Fernandez, 2011. "Real-Time Datasets Really Do Make a Difference: Definitional Change, Data Release, and Forecasting," Departmental Working Papers 201113, Rutgers University, Department of Economics.
  2. 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.

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