2000
DOI: 10.3386/t0248
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Estimation of Limited-Dependent Variable Models with Dummy Endogenous Regressors: Simple Strategies for Empirical Practice

Abstract: (1980), Bronars and Grogger (1994), Gangadharan and Rosenbloom (1996), andAngrist and Evans (1998

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Cited by 323 publications
(259 citation statements)
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“…In order to take this into account, we also conducted separate analyses for the counties where the university hospitals are located (Troms, Sør-Trøndelag and Hordaland). The results, which are presented in columns (3) and (4), show that the point estimates increase slightly relative to column (2), indicating an average individual-level treatment e ect of about ten percentage points for the compliant subpopulation.…”
mentioning
confidence: 93%
See 1 more Smart Citation
“…In order to take this into account, we also conducted separate analyses for the counties where the university hospitals are located (Troms, Sør-Trøndelag and Hordaland). The results, which are presented in columns (3) and (4), show that the point estimates increase slightly relative to column (2), indicating an average individual-level treatment e ect of about ten percentage points for the compliant subpopulation.…”
mentioning
confidence: 93%
“…2 Later research has shown that this result is sensitive to the inclusion of state speci c trends (Mazumder 2008). 3 Cutler and Lleras-Muney (2012) and Mazumder (2012) review this literature.…”
mentioning
confidence: 99%
“…To increase efficiency of the estimator, our instrumental variables (IV) approach takes account of the binary nature of the endogenous variables by estimating a Probit model in the first stage and by adopting GMM estimation in the second stage (Angrist, 2001;Wooldridge, 2010, chapter 21). Specifically, we adapt Wooldridge's Procedure 21.1 as follows:…”
Section: Estimationmentioning
confidence: 99%
“…The other option of demeaning all of the variables, to allow us to ignore the fixed effects terms, would bias the standard error estimates. Using the linear probability model in the first stage avoids these problems and allows us to estimate the causal effect of the treatment consistently and efficiently (Angrist 2000). For an earlier application of the linear probability model for endogenous regressors, see Heckman and MaCurdy (1985).…”
Section: Resultsmentioning
confidence: 99%