Arbeitspapier
Happy times: Identification from ordered response data
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 371
- Klassifikation
-
Wirtschaft
Semiparametric and Nonparametric Methods: General
Welfare Economics: General
Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making‡
General Welfare; Well-Being
- Thema
-
Surveys
ordinal data
response times
non-parametric identification
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Liu, Shuo
Netzer, Nick
- Ereignis
-
Veröffentlichung
- (wer)
-
University of Zurich, Department of Economics
- (wo)
-
Zurich
- (wann)
-
2020
- DOI
-
doi:10.5167/uzh-194139
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Liu, Shuo
- Netzer, Nick
- University of Zurich, Department of Economics
Entstanden
- 2020
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