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We extend the popular bias-based test of Stock and Yogo (2005) for instrument strength in linear instrumental variables regressions with multiple endogenous regressors to be robust to heteroskedasticity and autocorrelation. Equivalently, we extend the robust test of Montiel Olea and Pflueger...
Persistent link: https://www.econbiz.de/10014081836
Control variables provide an important means of controlling for endogeneity in econometric models with nonseparable and/or multidimensional heterogeneity. We allow for discrete instruments, giving identi cation results under a variety of restrictions on the way the endogenous variable and the...
Persistent link: https://www.econbiz.de/10011901534
This paper proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental variables which are independent of response given potential outcomes. A nonparametric testing procedure based on integrated squared distance is proposed. The statistic’s...
Persistent link: https://www.econbiz.de/10010503886
Persistent link: https://www.econbiz.de/10011646588
This paper proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental variables which are independent of response given potential outcomes. A nonparametric testing procedure based on integrated squared distance is proposed. The statistic’s...
Persistent link: https://www.econbiz.de/10011619523
This paper proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental variables which are independent of response given potential outcomes. A nonparametric testing procedure based on integrated squared distance is proposed. The statistic's...
Persistent link: https://www.econbiz.de/10011894725
Persistent link: https://www.econbiz.de/10012176614
We explore the validity of the 2-stage least squares estimator with l_{1}-regularization in both stages, for linear triangular models where the numbers of endogenous regressors in the main equation and instruments in the first-stage equations can exceed the sample size, and the regression...
Persistent link: https://www.econbiz.de/10012937114
Under treatment effect heterogeneity, an instrument identifies the instrument-specific local average treatment effect (LATE). If a regression model is estimated by the two-stage least squares (2SLS) using multiple instruments, then 2SLS is consistent for a weighted average of different LATEs. In...
Persistent link: https://www.econbiz.de/10013030149
Persistent link: https://www.econbiz.de/10013464568