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Statistical Treatment Rules for Heterogeneous Populations: With Application to Randomized Experiments

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Author Info
Charles F. Manski

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Abstract

This paper uses Wald's concept of the risk of a statistical decision function to address the question: How should sample data on treatment response be used to guide treatment choices in a heterogeneous population? Statistical treatment rules (STRs) are statistical decision functions that map observed covariates of population members and sample data on treatment response into treatment choices. I propose evaluation of STRs by their expected welfare (negative risk in Wald's terms), and I apply this criterion to compare two STRs when the sample data are generated by a classical randomized experiment. The rules compared both embody the reasonable idea that persons should be assigned the treatment with the best empirical success rate, but they differ in their use of covariate information. The conditional success (CS) rule selects treatments with the best empirical success rates conditional on specified covariates and the unconditional success (US) rule selects a treatment with the best unconditional empirical success rate. The main finding is a proposition giving finite-sample bounds on expected welfare under the two rules. The bounds, which rest on a large-deviations theorem of Hoeffding, yield explicit sample-size and distributional conditions under which the CS Rule is superior to the US rule.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0242.

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Date of creation: May 1999
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Handle: RePEc:nbr:nberte:0242

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Charles F. Manski, 1997. "Monotone Treatment Response," Econometrica, Econometric Society, vol. 65(6), pages 1311-1334, November.
  2. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267. [Downloadable!] (restricted)
  3. Rajeev Dehejia, 1999. "Program Evaluation as a Decision Problem," NBER Working Papers 6954, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  4. repec:att:wimass:199217 is not listed on IDEAS
  5. Heckman, James J & Smith, Jeffrey, 1997. "Making the Most Out of Programme Evaluations and Social Experiments: Accounting for Heterogeneity in Programme Impacts," Review of Economic Studies, Blackwell Publishing, vol. 64(4), pages 487-535, October. [Downloadable!] (restricted)
  6. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March. [Downloadable!] (restricted)
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  7. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-23, May. [Downloadable!] (restricted)
  8. repec:att:wimass:199526r is not listed on IDEAS
  9. Manski, Charles F., 2000. "Identification problems and decisions under ambiguity: Empirical analysis of treatment response and normative analysis of treatment choice," Journal of Econometrics, Elsevier, vol. 95(2), pages 415-442, April. [Downloadable!] (restricted)
  10. Manski, Charles F, 1997. "The Mixing Problem in Programme Evaluation," Review of Economic Studies, Blackwell Publishing, vol. 64(4), pages 537-53, October. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Mark C. Berger & Dan Black & Jeffrey Smith, 2000. "Evaluating Profiling as a Means of Allocating Government Services," UWO Department of Economics Working Papers 200018, University of Western Ontario, Department of Economics. [Downloadable!]
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