Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/170805
Authors: 
Heckman, James J.
Pinto, Rodrigo
Year of Publication: 
2017
Series/Report no.: 
IZA Discussion Papers 10821
Abstract: 
This paper presents a new monotonicity condition for unordered discrete choice models with multiple treatments. Unlike a less general version of monotonicity in binary and ordered choice models, monotonicity in unordered discrete choice models along with other standard assumptions does not necessarily identify causal effects defined by variation in instruments, although in some cases it does. Our condition implies and is implied by additive separability of the choice equations in terms of observables and unobservables. These results follow from properties of binary matrices developed in this paper. We investigate conditions under which Unordered Monotonicity arises as a consequence of choice behavior. We represent IV estimators of counterfactuals as solutions to discrete mixture problems.
Subjects: 
identification
selection bias
instrumental variables
monotonicity
revealed preference
Generalized Roy Model
binary matrices
discrete choice
discrete mixtures
JEL: 
I21
C93
J15
V16
Document Type: 
Working Paper

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