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To Hold Out or Not to Hold Out

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Author Info

  • Frank Schorfheide

    ()
    (Department of Economics, University of Pennsylvania)

  • Kenneth I. Wolpin

    ()
    (Department of Economics, University of Pennsylvania)

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    Abstract

    A recent literature has developed that combines two prominent empirical approaches to ex ante policy evaluation: randomized controlled trials (RCT) and structural estimation. The RCT provides a “gold-standard" estimate of a particular treatment, but only of that treatment. Structural estimation provides the capability to extrapolate beyond the experimental treatment, but is based on untestable assumptions and is subject to structural data mining. Combining the approaches by holding out from the structural estimation exercise either the treatment or control sample allows for external validation of the underlying behavioral model. Although intuitively appealing, this holdout methodology is not well grounded. For instance, it is easy to show that it is suboptimal from a Bayesian perspective. Using a stylized representation of a randomized controlled trial, we provide a formal rationale for the use of a holdout sample in an environment in which data mining poses an impediment to the implementation of the ideal Bayesian analysis and a numerical illustration of the potential benefits of holdout samples.

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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 13-059.

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    Length: 27 pages
    Date of creation: 14 Oct 2013
    Date of revision:
    Handle: RePEc:pen:papers:13-059

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    Related research

    Keywords: Bayesian Analysis; Model Selection; Principal-Agent Models; Randomized Controlled Trials;

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    1. Alvaro Sandroni, 2003. "The reproducible properties of correct forecasts," International Journal of Game Theory, Springer, vol. 32(1), pages 151-159, December.
    2. Lamont, Owen A., 2002. "Macroeconomic forecasts and microeconomic forecasters," Journal of Economic Behavior & Organization, Elsevier, vol. 48(3), pages 265-280, July.
    3. Hidehiko Ichimura & Christopher R. Taber, 2000. "Direct Estimation of Policy Impacts," NBER Technical Working Papers 0254, National Bureau of Economic Research, Inc.
    4. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
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