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Manipulability of Future-Independent Tests

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  • Alvaro Sandroni

    ()
    (Department of Economics, University of Pennsylvania)

  • Wojciech Olszewski

    ()
    (Department of Economics, Northwestern University)

Abstract

The difficulties in properly anticipating key economic variables may encourage decision makers to rely on experts’ forecasts. Professional forecasters, however, may not be reliable and so their forecasts must be empirically tested. This may induce experts to forecast strategically in order to pass the test. A test can be ignorantly passed if a false expert, with no knowledge of the data generating process, can pass the test. Many tests that are unlikely to reject correct forecasts can be ignorantly passed. Tests that cannot be ignorantly passed do exist, but these tests must make use of predictions contingent on data not yet observed at the time the forecasts are rejected. Such tests cannot be run if forecasters report only the probability of the next period’s events on the basis of the actually observed data. This result shows that it is difficult to dismiss false, but strategic, experts who know how theories are tested. This result also shows an important role that can be played by predictions contingent on data not yet observed.

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Bibliographic Info

Paper provided by Penn Institute for Economic Research, Department of Economics, University of Pennsylvania in its series PIER Working Paper Archive with number 08-014.

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Length: 36 pages
Date of creation: 15 Apr 2008
Date of revision:
Handle: RePEc:pen:papers:08-014

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Keywords: Testing Strategic Experts;

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References

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  7. Alvaro Sandroni & Wojciech Olszewski, 2008. "Falsifiability," PIER Working Paper Archive 08-016, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  8. Michael P. Keane & David E. Runkle, 1998. "Are Financial Analysts' Forecasts of Corporate Profits Rational?," Journal of Political Economy, University of Chicago Press, vol. 106(4), pages 768-805, August.
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  12. Alvaro Sandroni & Wojciech Olszewski, 2008. "Strategic Manipulation of Empirical Tests," PIER Working Paper Archive 08-015, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  13. Morgan, John & Stocken, Phillip C, 2003. " An Analysis of Stock Recommendations," RAND Journal of Economics, The RAND Corporation, vol. 34(1), pages 183-203, Spring.
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Citations

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Cited by:
  1. 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.
  2. Feinberg, Yossi & Lambert, Nicolas S., 2011. "Mostly Calibrated," Research Papers 2090, Stanford University, Graduate School of Business.
  3. Colin, Stewart, 2011. "Nonmanipulable Bayesian testing," Journal of Economic Theory, Elsevier, vol. 146(5), pages 2029-2041, September.
  4. Freedman, David A., 2009. "Diagnostics cannot have much power against general alternatives," International Journal of Forecasting, Elsevier, vol. 25(4), pages 833-839, October.
  5. Alvaro Sandroni & Wojciech Olszewski, 2008. "Strategic Manipulation of Empirical Tests," PIER Working Paper Archive 08-015, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  6. Alvaro Sandroni & Wojciech Olszewski, 2008. "Falsifiability," PIER Working Paper Archive 08-016, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.

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