Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/76184
Authors: 
Year of Publication: 
2007
Series/Report no.: 
Working Paper No. 0709
Publisher: 
University of Zurich, Socioeconomic Institute, Zurich
Abstract: 
This paper deals with the identification of treatment effects when the outcome variable is ordered. If outcomes are measured ordinally, previously developed methods to investigate the impact of an endogenous binary regressor on average outcomes cannot be applied as the expectation of an ordered variable, in its strict sense, does not exist, and a shift in focus to distributional effects is indispensable. Without imposing a fully fledged parametric model the treatment effects are generally not point-identified. Assuming a threshold crossing model on both the ordered potential outcomes and the binary treatment variable leaving the distribution of error terms and functional forms unspecified, it is discussed how the treatment effects can be bounded and inference on the bounds can be conducted.
Subjects: 
nonparametric bounds
causal effects
potential outcomes
latent variables
JEL: 
C14
C25
C35
Document Type: 
Working Paper

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