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Information, Forecasts and Measurement of the Business Cycle


  • Evans, George W.
  • Reichlin, Lucrezia


The Beveridge-Nelson (BN) technique provides a forecast-based method of decomposing a variable such as output, into trend and cycle when the variable is integrated of order one (I (1)). This paper considers the multivariate generalization of the BN decomposition when the information set includes other I (1) and/or stationary variables. We show that the relative importance of the cyclical component depends on the information set, and in particular that multivariate BN decompositions necessarily ascribe more importance to the cyclical component than does the univariate decomposition, provided the information set includes a variable which Granger-causes output. We illustrate the results for post-war data for the United States.

Suggested Citation

  • Evans, George W. & Reichlin, Lucrezia, 1993. "Information, Forecasts and Measurement of the Business Cycle," CEPR Discussion Papers 756, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:756

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    References listed on IDEAS

    1. Joseph E. Stiglitz, 1974. "Incentives and Risk Sharing in Sharecropping," Review of Economic Studies, Oxford University Press, vol. 41(2), pages 219-255.
    2. Steven Shavell, 1979. "Risk Sharing and Incentives in the Principal and Agent Relationship," Bell Journal of Economics, The RAND Corporation, vol. 10(1), pages 55-73, Spring.
    3. Bulow, Jeremy I & Summers, Lawrence H, 1984. "The Taxation of Risky Assets," Journal of Political Economy, University of Chicago Press, vol. 92(1), pages 20-39, February.
    4. Ahsan, Syed M, 1974. "Progression and Risk-Taking," Oxford Economic Papers, Oxford University Press, vol. 26(3), pages 318-328, November.
    5. Meyer, Jack, 1987. "Two-moment Decision Models and Expected Utility Maximization," American Economic Review, American Economic Association, vol. 77(3), pages 421-430, June.
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    More about this item


    Business Cycles; Cycle; Forecast; Granger Casuality; Information; Integrated Series; Trend;

    JEL classification:

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


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