We propose a procedure for testing simple hypotheses on a subset of the structural parameters in linear instrumental variables models. Our test is valid uniformly over a large class of distributions allowing for identification failure and heteroskedasticity. The large-sample distribution of our...

The mean squared prediction error of the linear regression model is examined when estimation is performed with instrumental variables. It is shown that increasing the number of instruments in the estimation procedure, can reduce the mean squared prediction error of the model through more...

We examine how trade openness influences income inequality within countries. The sample includes 139 countries over the period 1970-2014. We employ predicted openness as instrument to deal with the endogeneity of trade openness. The effect of trade openness on income inequality differs across...

This paper proposes new jackknife IV estimators that are robust to the effectsof many weak instruments and error heteroskedasticity in a cluster sample settingwith cluster-specific effects and possibly many included exogenous regressors. Theestimators that we propose are designed to properly...

In this paper we study the finite sample and asymptotic properties of various weighting estimators of the local average treatment effect (LATE), several of which are based on Abadie (2003)’s kappa theorem. Our framework presumes a binary endogenous explanatory variable (“treatment”) and a...

The instrumental variable model is one of the central tools for the analysis of causal relationships in observational data. The Anderson and Rubin (1949) test is an important method that allows for reliable inference in the instrumental variable model when the instruments are weak. Yet, the...

How strongly does ESG (environmental, social and governance) performance affect stock returns? Answering this question is difficult because existing measures of performance, ESG ratings, are noisy. To tackle the bias, we propose a noise-correction procedure, in which we instrument ESG ratings...

We develop non-parametric instrumental variable estimation and inferential theory for econometric models with possibly endogenous regressors whose coefficients can vary over time either deterministically or stochastically, and the time-varying and uniform versions of the standard Hausman...

It is customary to assume that an indicator of a latent variable is driven by the latent variable and some random noise. In contrast, a background indicator is also systematically influenced by variables outside the structural model of interest. Background indicators deserve attention because in...