A Practical Comparison of the Bivariate Probit and Linear IV Estimators

By R. Chiburis, Jishnu Das, Michael Lokshin. 2011

220 citations recorded by the source corpus.

This paper presents asymptotic theory and Monte-Carlo simulations comparing maximum-likelihood bivariate probit and linear instrumental variables estimators of treatment effects in models with a binary endogenous treatment and binary outcome. The three main contributions of the paper are (a) clarifying the relationship between the Average Treatment Effect obtained in the bivariate probit model and the Local Average Treatment Effect estimated through linear IV; (b) comparing the mean-square error and the actual size and power of tests based on these estimators across a wide range of parameter values relative to the existing literature; and (c) assessing the performance of misspecification tests for bivariate probit models. The authors recommend two changes to common practices: bootstrapped confidence intervals for both estimators, and a score test to check goodness of fit for the bivariate probit model.

Subfields: Economics and Econometrics, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7bd98a2254d60cdc4c55b63ac39be61b2a3406c1

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Citations in the corpus

Agricultural Cooperatives and Investment in Organic Soil Amendments and Chemical Fertilizer in China (2018, methodology): “We used bootstrap replications to reduce sampling noise (Chiburis et al. 2011).”
The Economic Costs of Type 2 Diabetes: A Global Systematic Review (2015, unknown): “Nonetheless, there is some discussion in the econometrics literature regarding the best method to estimate these cases, as it has also been argued that, because the linear IV technique does not depend on the assumption of normality of the error terms, in contrast to the bivariate probit model, its r”
Self-employment and intention of permanent urban settlement: Evidence from a survey of migrants in China’s four major urbanising areas (2015, methodology): “As the dependent variable and the endogenous independent variable are both binary, we follow the literature (Chiburis et al., 2011) in using both the bivariate Probit model and a linear IV approach.”
School Attendance, Child Labour, and Remittances from International Migration in El Salvador (2011, methodology): “Given the lack of consensus among econometricians on the right regression specification model for cases with binary dependent variables (for example, school attendance) and binary endogenous regressors (for example, receive remittances) (see Chiburis et al, 2010 ), this article follows the recommen”
The role of investment banker directors in M&A (2014, methodology): “Instead, we rely on probit and bivariate probit estimations to infer the marginal effect of IB directors on a firm's acquisition propensity, because these estimations are considered more appropriate and efficient in a setting like ours (Greene, 1998; Chiburis, Das, and Lokshin, 2012).”