This paper examines identification power of the instrument exogeneity assumption in the treatment effect model. We derive the identification region: The set of potential outcome distributions that are compatible with data and the model restriction. The model restrictions whose identifying power...

We develop and analyze a tractable empirical model for strategic network formation that can be estimated with data from a single network at a single point in time. We model the network formation as a sequential process where in each period a single randomly selected pair of agents has the...

This paper provides new estimates of the medium and long-term impacts of Head Start on the health and behavioral problems of its participants. We identify these impacts using discontinuities in the probability of participation induced by program eligibility rules. Our strategy allows us to...

This paper develops inference and statistical decision for set-identified parameters from the robust Bayes perspective. When a model is set-identified, prior knowledge for model parameters is decomposed into two parts: the one that can be updated by data (revisable prior knowledge) and the one...

In this paper, we investigate what can be learned about average counterfactual outcomes when it is assumed that treatment response functions are smooth. The smoothness conditions in this paper amount to assuming that the differences in average counterfactual outcomes are bounded under different...

In nonparametric instrumental variables estimation, the mapping that identifies the function of interest, g say, is discontinuous and must be regularised (that is, modified) to make consistent estimation possible. The amount of modification is contolled by a regularisation parameter. The optimal...

This paper develops a specification test for the instrument validity conditions in the heterogeneous treatment effect model with a binary treatment and a discrete instrument. A necessary testable implication for the joint restriction of instrument exogeneity and instrument monotonicity is given...

This paper provides tools for partial identification inference and sensistivity analysis in a general class of semiparametric models. The main working assumption is that the finite-dimensional parameter of interest and the possibility infinite-dimensional nuisance parameter are identified...

This paper develops a specification test for instrument validity in the heterogeneous treatment effect model with a binary treatment and a discrete instrument. The strongest testable implication for instrument validity is given by the condition for nonnegativity of point-identifiable complier's...

This paper discusses the nonparametric identi.cation of causal direct and indirect effects of a binary treatment based on instrumental variables. We identify the indirect effect, which operates through a mediator (i.e. intermediate variable) that is situated on the causal path between the...