Randomization as an Instrumental Variable
This paper discusses how randomized social experiments operate as an instrumental variable. For two types of randomization schemes, the fundamental experimental estimation equations are derived from the principle that experiments equate bias in control and experimental samples. Using conventional econometric representations, we derive the orthogonality conditions for the fundamental estimation equations. Randomization is a multiple instrumental variable in the sense that one randomization defines the parameter of interest expressed as a function of multiple endogenous variables in the conventional usage of that term. It orthogonalizes the treatment variable simultaneously with respect to the other regressors in the model and the disturbance term for the conditional population. However, conventional `structural' parameters are not in general identified by the two types of randomization schemes widely used in practice.
|Date of creation:||Sep 1995|
|Date of revision:|
|Publication status:||published as Heckman, James J. "Randomization As An Instrumental Variable," Review of Economics and Statistics, 1996, v78(2,May), 336-341.|
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- Heckman, J. & Smith, J. & Taber, C., 1994.
"Accounting for Dropouts in Evaluations of Social Experiments,"
University of Chicago - Economics Research Center
94-3, Chicago - Economics Research Center.
- James Heckman & Jeffrey Smith & Christopher Taber, 1994. "Accounting for Dropouts in Evaluations of Social Experiments," NBER Technical Working Papers 0166, National Bureau of Economic Research, Inc.
- Angrist, J.D. & Imbens, G.W., 1991.
"Sources of Identifying Information in Evaluation Models,"
Harvard Institute of Economic Research Working Papers
1568, Harvard - Institute of Economic Research.
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- 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.
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