Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/235607 
Year of Publication: 
2021
Series/Report no.: 
Working Paper No. 371
Version Description: 
This version: June 2021
Publisher: 
University of Zurich, Department of Economics, Zurich
Abstract: 
Surveys that are designed to measure subjective states (e.g., happiness) typically generate ordinal data. A fundamental problem is that methods used to analyse ordinal data (e.g., ordered probit) rely on strong and often unjustified distributional assumptions. In this paper, we propose using survey response times to solve that problem. The key assumption of our approach is that individual response time is decreasing in the distance between the value of the latent variable and an indecision threshold. This assumption is supported by a large body of evidence on chronometric effects in psychology, neuroscience and economics. We provide conditions under which the expected value of the latent variable (e.g., average happiness) can be compared across groups, even without making distributional assumptions. We apply our method to an online survey experiment and obtain some evidence that happiness follows distributions for which traditional regression analysis is valid.
Subjects: 
surveys
ordinal data
response times
non-parametric identification
JEL: 
C14
D60
D91
I31
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
869.97 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.