In parametric, nonlinear structural models, a classical sufficient condition for local
identification, like Fisher (1966) and Rothenberg (1971), is that the vector of moment …

Instrumental variable models allow us to identify a causal function between covariates $ X $
and a response $ Y $, even in the presence of unobserved confounding. Most of the existing …

Exogenous heterogeneity, for example, in the form of instrumental variables can help us
learn a system's underlying causal structure and predict the outcome of unseen intervention …

The paper investigates endogeneity issues in nonparametric frontier models. It considers a
nonseparable model for a cost function C= φ (Y, U) where C and Y are the cost and the …

This article analyzes the effect of a discrete treatment Z on a duration T. The treatment is not
randomly assigned. The confounding issue is treated using a discrete instrumental variable …

This paper studies nonparametric identification in market level demand models for
differentiated products with heterogeneous consumers. We consider a general class of …

We consider nonparametric estimation of an accelerated failure-time model when the
response variable is randomly censored on the right, and regressors are not mean …

This paper proposes a new strategy for the identification of the marginal effects of an
endogenous multivalued variable (which can be continuous, or a vector) in a model with an …

The problem of endogeneity in statistics and econometrics is often handled by introducing
instrumental variables (IV) which fulfill the mean independence assumption, ie the …

In this paper we present nonparametric estimators for coefficients in stochastic differential
equations if the data are described by independent, identically distributed random variables …