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Mostly Calibrated

  • Feinberg, Yossi

    (Stanford University)

  • Lambert, Nicolas S.

    (Stanford University)

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    Prequential testing of a forecaster is known to be manipulable if the test must pass an informed forecaster for all possible true distributions. Stewart (2011) provides a non-manipulable prequential likelihood test that only fails an informed forecaster on a small, category I, set of distributions. We present a prequential test based on calibration that also fails the informed forecaster on at most a category I set of true distributions and is non-manipulable. Our construction sheds light on the relationship between likelihood and calibration with respect to the distributions they reject.

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    Paper provided by Stanford University, Graduate School of Business in its series Research Papers with number 2090.

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    Date of creation: Dec 2011
    Date of revision:
    Handle: RePEc:ecl:stabus:2090
    Contact details of provider: Postal: Stanford University, Stanford, CA 94305-5015
    Phone: (650) 723-2146
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    1. Eddie Dekel & Yossi Feinberg, 2006. "Non-Bayesian Testing of a Stochastic Prediction," Discussion Papers 1418, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    2. Feinberg, Yossi & Stewart, Colin, 2007. "Testing Multiple Forecasters," Research Papers 1957, Stanford University, Graduate School of Business.
    3. Wojciech Olszewski & Alvaro Sandroni, 2006. "Strategic Manipulation of Empirical Tests," Discussion Papers 1425, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    4. Colin Stewart, 2009. "Nonmanipulable Bayesian Testing," Working Papers tecipa-360, University of Toronto, Department of Economics.
    5. Kalai, Ehud & Lehrer, Ehud & Smorodinsky, Rann, 1999. "Calibrated Forecasting and Merging," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 151-169, October.
    6. Nabil I. Al-Najjar & Jonathan Weinstein, 2006. "Comparative Testing of Experts," Levine's Working Paper Archive 321307000000000590, David K. Levine.
    7. Alvaro Sandroni, 2003. "The reproducible properties of correct forecasts," International Journal of Game Theory, Springer, vol. 32(1), pages 151-159, December.
    8. Lehrer, Ehud, 2001. "Any Inspection Is Manipulable," Econometrica, Econometric Society, vol. 69(5), pages 1333-47, September.
    9. Al-Najjar, Nabil I. & Sandroni, Alvaro & Smorodinsky, Rann & Weinstein, Jonathan, 2010. "Testing theories with learnable and predictive representations," Journal of Economic Theory, Elsevier, vol. 145(6), pages 2203-2217, November.
    10. Alvaro Sandroni & Wojciech Olszewski, 2008. "Manipulability of Future-Independent Tests," PIER Working Paper Archive 08-014, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    11. Shmaya, Eran, 2008. "Many inspections are manipulable," Theoretical Economics, Econometric Society, vol. 3(3), September.
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