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Calibration-Based Predictive Distributions: An Application of Prequential Analysis to Interest Rates, Money, Prices, and Output

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  • Kling, John L
  • Bessler, David A

Abstract

Some techniques of probability forecasting are applied to time-series data on interest rates, money stock, consumer prices, and output. A sequential method for debiasing (recalibrating) predictive distributions and outcomes is developed, and the authors estimated sequences of unadjusted and recalibrated distributions are tested for calibration. After recalibration, the calibration hypothesis cannot be rejected for most of the time-series and forecast horizons. Furthermore, traditional point forecasts can be improved when the forecasts are derived from recalibrated distributions. Copyright 1989 by the University of Chicago.

Suggested Citation

  • Kling, John L & Bessler, David A, 1989. "Calibration-Based Predictive Distributions: An Application of Prequential Analysis to Interest Rates, Money, Prices, and Output," The Journal of Business, University of Chicago Press, vol. 62(4), pages 477-499, October.
  • Handle: RePEc:ucp:jnlbus:v:62:y:1989:i:4:p:477-99
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    Cited by:

    1. Clements, Michael P., 2018. "Are macroeconomic density forecasts informative?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 181-198.
    2. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
    3. Goodwin, Barry K., 1992. "Forecasting Cattle Prices in the Presence of Structural Change," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 24(02), pages 11-22, December.
    4. Casillas-Olvera, Gabriel & Bessler, David A., 2006. "Probability forecasting and central bank accountability," Journal of Policy Modeling, Elsevier, vol. 28(2), pages 223-234, February.
    5. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, Elsevier.
    6. Bessler, David & Kibriya, Shahriar & Chen, Junyi & Price, Ed, 2014. "On Forecasting Conflict in Sudan: 2009-2012," MPRA Paper 60069, University Library of Munich, Germany.
    7. Herbst, Edward & Schorfheide, Frank, 2012. "Evaluating DSGE model forecasts of comovements," Journal of Econometrics, Elsevier, vol. 171(2), pages 152-166.
    8. Frank Schorfheide & Dongho Song, 2015. "Real-Time Forecasting With a Mixed-Frequency VAR," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 366-380, July.
    9. David Bessler & Robert Ruffley, 2004. "Prequential analysis of stock market returns," Applied Economics, Taylor & Francis Journals, vol. 36(5), pages 399-412.
    10. repec:eee:eneeco:v:65:y:2017:i:c:p:411-423 is not listed on IDEAS
    11. repec:eee:ejores:v:264:y:2018:i:3:p:1020-1032 is not listed on IDEAS
    12. Roberto Casarin & Federico Bassetti & Francesco Ravazzolo, 2015. "Bayesian Nonparametric Calibration and Combination of Predictive Distributions," Working Papers 2015:04, Department of Economics, University of Venice "Ca' Foscari".
    13. repec:oup:erevae:v:45:y:2018:i:1:p:121-142. is not listed on IDEAS
    14. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2015. "Forecasting in a DSGE Model with Banking Intermediation: Evidence from the US," Working Papers 292, University of Milano-Bicocca, Department of Economics, revised Feb 2015.
    15. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2015. "Forecasting with Instabilities: an Application to DSGE Models with Financial Frictions," Working Papers 201523, School of Economics, University College Dublin.

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