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We compare estimates of the effects of education on health and health behaviour using two different instrumental variables in the UK Biobank data. One is based on a conventional natural experiment while the other, known as Mendelian randomization (MR), is based on genetic variants. The natural...
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In a recent paper, Hausman et al. (2012) propose a new estimator, HFUL (Heteroscedasticity robust Fuller), for the linear model with endogeneity. This estimator is consistent and asymptotically normally distributed in the many instruments and many weak instruments asymptotics. Moreover, this...
Persistent link: https://www.econbiz.de/10009766695
This paper shows how a weighted average of a forward and reverse Jackknife IV estimator (JIVE) yields estimators that are robust against heteroscedasticity and many instruments. These estimators, called HFUL (Heteroscedasticity robust Fuller) and HLIM (Heteroskedasticity robust limited...
Persistent link: https://www.econbiz.de/10009766699
This paper examines a general class of inferential problems in semiparametric and nonparametric models defined by conditional moment restrictions. We construct tests for the hypothesis that at least one element of the identified set satisfies a conjectured (Banach space) "equality" and/or (a...
Persistent link: https://www.econbiz.de/10011337665
High-dimensional linear models with endogenous variables play an increasingly important role in recent econometric literature. In this work we allow for models with many endogenous variables and many instrument variables to achieve identification. Because of the high-dimensionality in the second...
Persistent link: https://www.econbiz.de/10011775296
Shape restrictions have played a central role in economics as both testable implications of theory and sufficient conditions for obtaining informative counterfactual predictions. In this paper we provide a general procedure for inference under shape restrictions in identified and partially...
Persistent link: https://www.econbiz.de/10013332218
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We consider the bias of the 2SLS estimator in the linear instrumental variables regression with one endogenous regressor only. By using asymptotic expansion techniques we approximate 2SLS coefficient estimation bias under various scenarios regarding the number and strength of instruments.
Persistent link: https://www.econbiz.de/10010326261