Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/228871 
Autor:innen: 
Erscheinungsjahr: 
2020
Schriftenreihe/Nr.: 
Working Paper No. 371
Verlag: 
University of Zurich, Department of Economics, Zurich
Zusammenfassung: 
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.
Schlagwörter: 
Surveys
ordinal data
response times
non-parametric identification
JEL: 
C14
D60
D91
I31
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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