This paper analyzes the conditions under which consistent estimation can be achieved in instrumental Variables (IV) regression when the available instruments are weak, in the local-to-zero sense of Staiger and Stock (1997) and using the many-instrument framework of Morimune (1983) and Bekker...

Health scientists often use observational data to estimate treatment effects when controlled experiments are not feasible. A limitation of observational research is non-random selection of subjects into different treatments, potentially leading to selection bias. The 2 commonly used solutions to...

Using a rich Italian cross-sectional data set, we estimate the effect of a neighborhood quality index based on pollution, crime, and noise on self-assessed health, presence of chronic conditions and limitations in daily activities. We address the self-selection of the residents in their...

Unconditional quantile treatment effects are difficult to estimate in the presence of fixed effects. Panel data are frequently used because fixed effects or differences are necessary to identify the parameters of interest. The inclusion of fixed effects or differencing of data, however,...

This paper introduces an unconditional quantile regression (UQR) estimator that can be used for exogenous or endogenous treatment variables. Traditional quantile estimators provide conditional treatment effects. Typically, we are interested in unconditional quantiles, characterizing the...

The validity of existing empirical tests of the Pollution Haven Hypothesis (PHH) is constantly under scrutiny due to two shortcomings. First, the issues of unobserved heterogeneity and measurement error in environmental regulation are typically ignored due to the lack of a credible, traditional...

This paper shows that instrumental variables estimators currently in use, require strong but neglected auxiliary assumptions to be consistent in situations with partially missing instruments. We introduce an alternative instrumental variables estimator that does not require auxiliary assumptions.

We study the scope of local indirect least squares (LILS) methods for nonparametrically estimating average marginal effects of an endogenous cause X on a response Y in triangular structural systems that need not exhibit linearity, separability, or monotonicity in scalar unobservables. One main...

The implementation of the 1950 Swedish comprehensive school reform was preceded by a unique social experiment. During this experiment between 1949 and 1962 the new school system was implemented in stages. This allows us to study the same cohort of individuals going through two different school...

This paper conducts a general analysis of the conditions under which consistent estimation can be achieved in instrumental variables regression when the available instruments are weak in the local-to-zero sense. More precisely, the approach adopted in this paper combines key features of the...