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Instrumental Variables Estimation of Average Treatment Effects in Econometrics and Epidemiology

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  • Joshua D. Angrist
Abstract
The average effect of intervention or treatment is a parameter of interest in both epidemiology and econometrics. A key difference between applications in the two fields is that epidemiologic research is more likely to involve qualitative outcomes and nonlinear models. An example is the recent use of the Vietnam era draft lottery to construct estimates of the effect of Vietnam era military service on civilian mortality. In this paper. I present necessary and sufficient conditions for linear instrumental variables. techniques to consistently estimate average treatment effects in qualitative or other nonlinear models. Most latent index models commonly applied to qualitative outcomes in econometrics fail to satisfy these conditions, and monte carlo evidence on the bias of instrumental estimates of the average treatment effect in a bivariate probit model is presented. The evidence suggests that linear instrumental variables estimators perform nearly as well as the correctly specified maximum likelihood estimator. especially in large samples. Linear instrumental variables and the normal maximum likelihood estimator are also remarkably robust to non-normality.

Suggested Citation

  • Joshua D. Angrist, 1991. "Instrumental Variables Estimation of Average Treatment Effects in Econometrics and Epidemiology," NBER Technical Working Papers 0115, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberte:0115
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    References listed on IDEAS

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    1. Nelson, Charles R & Startz, Richard, 1990. "Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator," Econometrica, Econometric Society, vol. 58(4), pages 967-976, July.
    2. Angrist, Joshua D, 1990. "Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records," American Economic Review, American Economic Association, vol. 80(3), pages 313-336, June.
    3. White, Halbert, 1982. "Instrumental Variables Regression with Independent Observations," Econometrica, Econometric Society, vol. 50(2), pages 483-499, March.
    4. Joshua Angrist & Alan Krueger, 1989. "Why Do World War II Veterans Earn More Than Nonveterans?," Working Papers 634, Princeton University, Department of Economics, Industrial Relations Section..
    5. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    6. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    7. Angrist, Joshua & Krueger, Alan B, 1994. "Why Do World War II Veterans Earn More Than Nonveterans?," Journal of Labor Economics, University of Chicago Press, vol. 12(1), pages 74-97, January.
    8. Angrist, Joshua D, 1990. "Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records: Errata," American Economic Review, American Economic Association, vol. 80(5), pages 1284-1286, December.
    9. Newey, Whitney K., 1986. "Linear instrumental variable estimation of limited dependent variable models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 32(1), pages 127-141, June.
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