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Strategic Manipulation of Empirical Tests

Author

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  • Alvaro Sandroni

    () (Department of Economics, University of Pennsylvania)

  • Wojciech Olszewski

    () (Department of Economics, Northwestern University)

Abstract

Theories can be produced by experts seeking a reputation for having knowledge. Hence, a tester could anticipate that theories may have been strategically produced by uninformed experts who want to pass an empirical test. We show that, with no restriction on the domain of permissible theories, strategic experts cannot be discredited for an arbitrary but given number of periods, no matter which test is used (provided that the test does not reject the actual data-generating process). Natural ways around this impossibility result include 1) assuming that unbounded data sets are available and 2) restricting the domain of permissible theories (opening the possibility that the actual data-generating process is rejected out of hand). In both cases, it is possible to dismiss strategic experts, but only to a limited extent. These results show significant limits on what data can accomplish when experts produce theories strategically.

Suggested Citation

  • 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.
  • Handle: RePEc:pen:papers:08-015
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    References listed on IDEAS

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    1. Nabil I. Al-Najjar & Jonathan Weinstein, 2008. "Comparative Testing of Experts," Econometrica, Econometric Society, vol. 76(3), pages 541-559, May.
    2. Wojciech Olszewski & Alvaro Sandroni, 2008. "Manipulability of Future-Independent Tests," Econometrica, Econometric Society, vol. 76(6), pages 1437-1466, November.
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    Citations

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    Cited by:

    1. Wojciech Olszewski & Alvaro Sandroni, 2008. "Manipulability of Future-Independent Tests," Econometrica, Econometric Society, vol. 76(6), pages 1437-1466, November.
    2. Dean Foster & Rakesh Vohra, 2011. "Calibration: Respice, Adspice, Prospice," Discussion Papers 1537, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    3. Colin, Stewart, 2011. "Nonmanipulable Bayesian testing," Journal of Economic Theory, Elsevier, vol. 146(5), pages 2029-2041, September.
    4. Francisco Barreras & Álvaro J. Riascos, 2016. "Screening multiple potentially false experts," MONOGRAFÍAS 015075, QUANTIL.
    5. Yossi Feinberg & Colin Stewart, 2008. "Testing Multiple Forecasters," Econometrica, Econometric Society, vol. 76(3), pages 561-582, May.
    6. Feinberg, Yossi & Lambert, Nicolas S., 2011. "Mostly Calibrated," Research Papers 2090, Stanford University, Graduate School of Business.
    7. Hu, Tai Wei & Shmaya, Eran, 2013. "Expressible inspections," Theoretical Economics, Econometric Society, vol. 8(2), May.
    8. Al-Najjar, Nabil & Sandroni, Alvaro, 2013. "A difficulty in the testing of strategic experts," Mathematical Social Sciences, Elsevier, vol. 65(1), pages 5-9.
    9. Francisco Barreras, 2017. "Screening Multiple Uninformed Experts," DOCUMENTOS DE TRABAJO QUANTIL 015282, QUANTIL.
    10. 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.

    More about this item

    Keywords

    Testing Strategic Experts;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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