Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/228871 
Year of Publication: 
2020
Series/Report no.: 
Working Paper No. 371
Publisher: 
University of Zurich, Department of Economics, Zurich
Abstract: 
Surveys are an important tool in economics and in the social sciences more broadly. However, methods used to analyse ordinal survey 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. Our main identifying assumption 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 and neuroscience. 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. By applying it to an online survey experiment, we show how our method can be implemented in practice and gives rise to new insights.
Subjects: 
Surveys
ordinal data
response times
non-parametric identification
JEL: 
C14
D60
D91
I31
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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