.png){kind=icon}
Return
Changes-in-Changes for Ordered Choice Models with Underreporting
.png){kind=icon}
OA
AI
DOI：10.1080/07350015.2026.2732285.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We develop a Difference-in-Differences framework for discrete, ordered outcomes subject to underreporting. Such outcomes commonly arise in self-reported surveys on socially undesirable or stigmatized behaviors, where respondents may conceal their true behavior. For a discrete Changes-in-Changes model that is shown to admit an equivalent threshold-crossing representation, we derive nonparametric bounds for the counterfactual and factual outcome distributions as well as for the associated quantile treatment effects when outcomes are underreported. These bounds are shown to be sharp uniformly across outcome levels under additional support conditions, and we propose suitable estimation and bootstrap inference procedures. In an extension, we also consider a semiparametric underreporting model that allows to point identify and estimate distributional treatment effects. As an application, we investigate the impact of recreational marijuana legalization on the consumption behavior of 8th-grade students in several U.S. states.
Keywords:
C21
C25
C31
C51
Partially Observable Outcomes
Identification
Treatment Effects
Measurement Error
Journal
J
IF:
2.5
Papers:
119
Citations:
0
Organization
Cited Papers
No cited papers available