Information-Theoretic Deconvolution Approximation of Treatment Effect Distribution
This study proposes an information-theoretic deconvolution method to approximate the entire distribution of individual treatment effect. This method uses higher-order information implied by the standard average treatment effect estimator to construct a maximum entropy approximation to the treatment effect distribution. This method is able to approximate the underlying distribution even if it is entirely random or dependent on unobservable covariates. The asymptotic properties of the proposed estimator is discussed. This estimator is shown to minimize the Kullback-Leibler distance between the underlying distribution and the approximations. Monte Carlo simulations and experiments with real data demonstrate the efficacy and flexibility of the proposed deconvolution estimator. This method is applied to data from the U.S. Job Training Partnership Act (JTPA) program to estimate the distribution of its impact on individual earnings.
|Date of creation:||25 Jan 2007|
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- Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
- Dalén, Jörgen, 1987. "Algebraic bounds on standardized sample moments," Statistics & Probability Letters, Elsevier, vol. 5(5), pages 329-331, August.
- Sergio Firpo, 2004.
"Efficient Semiparametric Estimation of Quantile Treatment Effects,"
Econometric Society 2004 North American Summer Meetings
605, Econometric Society.
- Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, 01.
- Zellner, Arnold & Highfield, Richard A., 1988. "Calculation of maximum entropy distributions and approximation of marginalposterior distributions," Journal of Econometrics, Elsevier, vol. 37(2), pages 195-209, February.
- James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 487-535.
- White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
- Joel L. Horowitz & Marianthi Markatou, 1996. "Semiparametric Estimation of Regression Models for Panel Data," Review of Economic Studies, Oxford University Press, vol. 63(1), pages 145-168.
- Wu, Ximing, 2003. "Calculation of maximum entropy densities with application to income distribution," Journal of Econometrics, Elsevier, vol. 115(2), pages 347-354, August.
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