.png){kind=icon}
.png){kind=icon}
Return
Unordered Monotonicity
.png){kind=icon}
OA
AI
DOI：10.3982/ECTA13777.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper defines and analyzes a new monotonicity condition for the identification of counterfactuals and treatment effects in unordered discrete choice models with multiple treatments, heterogeneous agents, and discrete-valued instruments. Unordered monotonicity implies and is implied by additive separability of choice of treatment equations in terms of observed and unobserved variables. 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 characterize IV estimators of counterfactuals as solutions to discrete mixture problems.
Keywords:
Instrumental variables
monotonicity
revealed preference
Generalized Roy model
binary matrices
discrete choice
selection bias
identification
discrete mixtures
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.1
Papers:
3.0K
Citations:
4.3W
