Summary Multi-dimensional heterogeneity and endogeneity are important features of models with multiple treatments. We consider a heterogeneous coefficients model where the outcome is a linear combination of dummy treatment variables, with each variable representing a different kind of treatment. We use control variables to give necessary and sufficient conditions for identification of average treatment effects. With mutually exclusive treatments we find that, provided the heterogeneous coefficients are mean independent from treatments given the controls, a simple identification condition is that the generalized propensity scores (Imbens, 2000) be bounded away from zero and that their sum be bounded away from one, with probab...
This paper considers identification of treatment effects when the outcome variables and covari-ates ...
Abstract. In this paper we study a binary treatment model where the outcome equation is of unre-stri...
The term multi-valued treatment effects refers to a collection of population parameters capturing th...
Multi-dimensional heterogeneity and endogeneity are important features of models with multiple treat...
We use the control function approach to identify the average treatment effect and the effect of tre...
This paper considers treatment effects under endogeneity with complex heterogeneity in the selection...
Abstract This paper provides a review of methodological advancements in the evaluatio...
We consider the identification of the average treatment effect in models with continuous endogenous ...
Assessing the heterogeneous causal effects of endogenous variables is of a strong interest in econom...
This paper discusses how to identify individual-specific causal effects of an ordered discrete endog...
Studies commonly focus on estimating a mean treatment effect in a population. However, in some appli...
A variety of identification strategies have a common cell structure, in which the observed heterogen...
Multivalued treatment models have only been studied so far under restrictive assumptions: ordered ch...
This paper examines the properties of instrumental variables (IV) applied to models with essential h...
This paper examines identification power of the instrument exogeneity assumption in the treatment ef...
This paper considers identification of treatment effects when the outcome variables and covari-ates ...
Abstract. In this paper we study a binary treatment model where the outcome equation is of unre-stri...
The term multi-valued treatment effects refers to a collection of population parameters capturing th...
Multi-dimensional heterogeneity and endogeneity are important features of models with multiple treat...
We use the control function approach to identify the average treatment effect and the effect of tre...
This paper considers treatment effects under endogeneity with complex heterogeneity in the selection...
Abstract This paper provides a review of methodological advancements in the evaluatio...
We consider the identification of the average treatment effect in models with continuous endogenous ...
Assessing the heterogeneous causal effects of endogenous variables is of a strong interest in econom...
This paper discusses how to identify individual-specific causal effects of an ordered discrete endog...
Studies commonly focus on estimating a mean treatment effect in a population. However, in some appli...
A variety of identification strategies have a common cell structure, in which the observed heterogen...
Multivalued treatment models have only been studied so far under restrictive assumptions: ordered ch...
This paper examines the properties of instrumental variables (IV) applied to models with essential h...
This paper examines identification power of the instrument exogeneity assumption in the treatment ef...
This paper considers identification of treatment effects when the outcome variables and covari-ates ...
Abstract. In this paper we study a binary treatment model where the outcome equation is of unre-stri...
The term multi-valued treatment effects refers to a collection of population parameters capturing th...