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

Joshua Angrist

No 248, NBER Technical Working Papers from National Bureau of Economic Research, Inc

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.

JEL-codes: C34 C35 (search for similar items in EconPapers)
Date: 2000-01
New Economics Papers: this item is included in nep-ecm
Note: TWP
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Published as Angrist, Joshua D. "Estimation Of Limited Dependent Variable Models With Dummy Endogenous Regressors: Simple Strategies For Empirical Practice," Journal of Business and Economic Statistics, 2001, v19(1,Jan), 2-15.

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Journal Article: Estimations of Limited Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice (2001)
Working Paper: Estimation of Limited-Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice (1999)
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