Statistical Treatment Rules for Heterogeneous Populations: With Application to Randomized Experiments
AbstractThis 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0242.
Date of creation: May 1999
Date of revision:
Publication status: published as Manski, Charles F. "Statistical Treatment Rules For Heterogeneous Populations," Econometrica, 2004, v72(4,Jul), 1221-1246.
Contact details of provider:
Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
Web page: http://www.nber.org
More information through EDIRC
This paper has been announced in the following NEP Reports:
- NEP-ALL-1999-06-08 (All new papers)
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.:
- repec:att:wimass:9526 is not listed on IDEAS
- 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.
- Charles F. Manski, 1993.
"The Mixing Problem in Program Evaluation,"
NBER Technical Working Papers
0148, National Bureau of Economic Research, Inc.
- Rajeev Dehejia, 1999.
"Program Evaluation as a Decision Problem,"
NBER Working Papers
6954, National Bureau of Economic Research, Inc.
- repec:att:wimass:8909 is not listed on IDEAS
- Manski, C.F. & Sandefur, G.D. & Mclanahan, S. & Powers, D., 1990. "Alternative Estimates Of The Effect Of Family Stucture During Adolescence On Hight School Graduation," Working papers 90-31, Wisconsin Madison - Social Systems.
- Frank Stafford, 1985. "Income-Maintenance Policy and Work Effort: Learning from Experiments and Labor-Market Studies," NBER Chapters, in: Social Experimentation, pages 95-144 National Bureau of Economic Research, Inc.
- Charles F. Manski, 1997.
"Monotone Treatment Response,"
Econometric Society, vol. 65(6), pages 1311-1334, November.
- Manski, Charles F, 1990.
"Nonparametric Bounds on Treatment Effects,"
American Economic Review,
American Economic Association, vol. 80(2), pages 319-23, May.
- Hotz, V Joseph & Mullin, Charles H & Sanders, Seth G, 1997. "Bounding Causal Effects Using Data from a Contaminated Natural Experiment: Analysing the Effects of Teenage Childbearing," Review of Economic Studies, Wiley Blackwell, vol. 64(4), pages 575-603, October.
- 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.
- Imbens, Guido W & Angrist, Joshua D, 1994.
"Identification and Estimation of Local Average Treatment Effects,"
Econometric Society, vol. 62(2), pages 467-75, March.
- Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
- Manski, C.F. & Nagin, D.S., 1996.
"Bounding Disagreements About Treatment Effects: A Case Study of Sentencing and Recidivism,"
9526r, Wisconsin Madison - Social Systems.
- repec:att:wimass:9217 is not listed on IDEAS
- 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, Wiley Blackwell, vol. 64(4), pages 487-535, October.
- 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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().
If references are entirely missing, you can add them using this form.