In this paper nonparametric instrumental variable estimation of local average treatment effects (LATE) is extended to incorporate confounding covariates. Estimation of local average treatment effects is appealing since their identification relies on much weaker assumptions than the...

This paper provides an introduction into the estimation of Marginal Treatment Effects (MTE). Compared to the existing surveys on the subject, our paper is less technical and speaks to the applied economist with a solid basic understanding of econometric techniques who would like to use MTE...

I review recent work in the statistics literature on instrumental variables methods from an econometrics perspective. I discuss some of the older, economic, applications including supply and demand models and relate them to the recent applications in settings of randomized experiments with...

Instrumental variables (IV) is an indispensable tool for establishing causal relationships between variables. Recent work has focused on improving bounds for cases when an ideal instrument does not exist. We leverage a principle, "Intransitivity in Correlations," related to an under-utilized...

We develop a nonparametric instrumental variable approach for the estimation of average treatment effects on hazard rates and conditional survival probabilities, without model structure. We derive constructive identification proofs for average treatment effects under noncompliance and dynamic...

We investigate if, and under which conditions, the distinction between dictatorial and incentive-based policy interventions affects the capacity of Instrument Variable (IV) methods to estimate the relevant treatment effect parameter of an outcome equation. The analysis is set in a non-trivial...

We build on Rosenzweig and Wolpin (2000) and Keane (2010) and show that in order to fulfill the Instrumental variable (IV) identifying moment condition, a policy must be designed so that compliers and non-compliers either have the same average error term, or have an error term ratio equal to...

This paper proposes a novel instrumental variable method for program evaluation that only requires a single cross-section of data on the spatial intensity of programs and outcomes. The instruments are derived from a simple theoretical model of government decision-making in which governments are...

This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971, 1974), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance...