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Exploring The Usefulness Of A Nonrandom Holdout Sample For Model Validation: Welfare Effects On Female Behavior

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  • Michael P. Keane
  • Kenneth I. Wolpin

Abstract

A particularly challenging use of decision-theoretic models in economics is to forecast the impact of large changes in the environment. The problem we explore in this article is how to gain confidence in a model's ability to predict the impact of such large changes. We show that an approach to validation and model selection that includes the choice of a "nonrandom holdout sample," a sample that differs significantly from the estimation sample along the policy dimension that the model is meant to forecast, can be fruitful. Copyright 2007 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.

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Bibliographic Info

Article provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.

Volume (Year): 48 (2007)
Issue (Month): 4 (November)
Pages: 1351-1378

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Handle: RePEc:ier:iecrev:v:48:y:2007:i:4:p:1351-1378

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  1. Keane, Michael P & Wolpin, Kenneth I, 1994. "The Solution and Estimation of Discrete Choice Dynamic Programming Models by Simulation and Interpolation: Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 648-72, November.
  2. Keane, Michael & Moffitt, Robert, 1998. "A Structural Model of Multiple Welfare Program Participation and Labor Supply," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(3), pages 553-89, August.
  3. Bontemps, Christian & Robin, Jean-Marc & van den Berg, Gerard J, 2000. "Equilibrium Search with Continuous Productivity Dispersion: Theory and Nonparametric Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 41(2), pages 305-58, May.
  4. Robert M. Sauer & Michael P. Keane, 2004. "A Computationally Practical Simulation Estimation Algorithm for Dynamic Panel Data Models with Unobserved Endogenous State Variables," Econometric Society 2004 North American Summer Meetings 136, Econometric Society.
  5. Heckman, J.J. & Hotz, V.J., 1988. "Choosing Among Alternative Nonexperimental Methods For Estimating The Impact Of Social Programs: The Case Of Manpower Training," University of Chicago - Economics Research Center, Chicago - Economics Research Center 88-12, Chicago - Economics Research Center.
  6. Keane, Michael, 1993. "Simulation estimation for panel data models with limited dependent variables," MPRA Paper 53029, University Library of Munich, Germany.
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