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The Properties of Market-Based and Survey Forecasts for Different Data Releases

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  • Lanne, Markku

Abstract

We compare the accuracy of the survey forecasts and forecasts implied by economic binary options on the U.S. nonfarm payroll change. These options are available for a number of ranges of the announced figure, and each pays $1 if the released nonfarm payroll change falls in the given range. For the first-release data both the market-based and survey forecasts are biased, while they are rational and approximately equally accurate for later releases. Both forecasts are more accurate for later releases. Because of predictability in the revision process, this indicates that the investors in the economic derivatives market are incapable of taking the measurement error in the preliminary estimates efficiently into account. This suggests that economic stability could be enhanced by more accurate first-release figures.

Suggested Citation

  • Lanne, Markku, 2007. "The Properties of Market-Based and Survey Forecasts for Different Data Releases," MPRA Paper 3877, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:3877
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    References listed on IDEAS

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    1. Ottaviani, Marco & Sorensen, Peter Norman, 2006. "The strategy of professional forecasting," Journal of Financial Economics, Elsevier, vol. 81(2), pages 441-466, August.
    2. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
    3. Bomfim, Antulio N., 2001. "Measurement error in general equilibrium: the aggregate effects of noisy economic indicators," Journal of Monetary Economics, Elsevier, vol. 48(3), pages 585-603, December.
    4. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    5. Refet Gürkaynak & Justin Wolfers, 2005. "Macroeconomic Derivatives: An Initial Analysis of Market-Based Macro Forecasts, Uncertainty, and Risk," NBER Chapters, in: NBER International Seminar on Macroeconomics 2005, pages 11-50, National Bureau of Economic Research, Inc.
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    Keywords

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    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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