Estimation of Limited-Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice

40 Pages Posted: 11 Aug 2000

See all articles by Joshua D. Angrist

Joshua D. Angrist

Massachusetts Institute of Technology (MIT) - Department of Economics; National Bureau of Economic Research (NBER); IZA Institute of Labor Economics

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Date Written: November 1999

Abstract

Applied economists have long struggled with the question of how to accommodate binary endogenous regressors in models with binary and non-negative outcomes. I argue here that much of the difficulty with limited-dependent variables comes from a focus on structural parameters, such as index coefficients, instead of causal effects. Once the object of estimation is taken to be the causal effect of treatment, a number of simple strategies is available. These include conventional two-stage least squares, multiplicative models for conditional means, linear approximation of nonlinear causal models, models for distribution effects, and quantile regression with an endogenous binary regressor. The estimation strategies discussed in the paper are illustrated by using multiple births to estimate the effect of childbearing on employment status and hours of work.

Suggested Citation

Angrist, Joshua, Estimation of Limited-Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice (November 1999). MIT Department of Economics Working Paper No. 99-31. Available at SSRN: https://ssrn.com/abstract=237485 or http://dx.doi.org/10.2139/ssrn.237485

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