Happy Times: Identification from Ordered Response Data

University of Zurich, Department of Economics, Working Paper No. 371, Revised version

44 Pages Posted: 13 Jan 2021 Last revised: 6 Jul 2021

See all articles by Shuo Liu

Shuo Liu

Peking University - Guanghua School of Management

Nick Netzer

University of Zurich

Date Written: June 2021

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.

Keywords: Surveys, ordinal data, response times, non-parametric identification

JEL Classification: C14, D60, D91, I31

Suggested Citation

Liu, Shuo and Netzer, Nick, Happy Times: Identification from Ordered Response Data (June 2021). University of Zurich, Department of Economics, Working Paper No. 371, Revised version, Available at SSRN: https://ssrn.com/abstract=3752581 or http://dx.doi.org/10.2139/ssrn.3752581

Shuo Liu (Contact Author)

Peking University - Guanghua School of Management ( email )

Peking University
Beijing, Beijing 100871
China

Nick Netzer

University of Zurich ( email )

Rämistrasse 71
Zürich, CH-8006
Switzerland

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