Measuring Progress: STATEC Well-being Seminar Series

17:00 CET (11:00 AM Eastern) – 18:00 CET (12:00 PM Eastern)

23 November 2022

The Scientific Value of Numerical Measures of Human Feelings

Dr. Caspar Kaiser, University of Oxford

Abstract: Human feelings measured in integers (my happiness is an 8 out of 10, my pain 2 out of 6) have no objective scientific basis. They are ‘made up’ numbers on a scale that does not exist. Yet such data are extensively collected -- despite criticism from, especially, economists -- by governments and international organizations. We examine this paradox. We draw upon longitudinal information on the feelings and decisions of tens of thousands of randomly sampled citizens followed through time over four decades in three countries (N=700,000 approx). First, we show that a single feelings integer has greater predictive power than a combined set of economic and social variables. Second, there is a clear inverse relationship between feelings integers and subsequent get-me-out-of-here-actions (in the domain of neighbourhoods, partners, jobs, and hospital visits). Third, this feelings-to-actions relationship takes a generic form, is consistently replicable, and is fairly close to linear in structure. Therefore, it seems that human beings can successfully operationalize an integer scale for feelings even though there is no true scale. How individuals are able to achieve this is not currently known. The implied scientific puzzle -- an inherently cross-disciplinary one -- demands attention.

Dr. Caspar Kaiser is a Research Officer at the Institute for New Economic Thinking and a Research Fellow at the Wellbeing Research Centre, both of which are part of the University of Oxford. He is also a trustee of the Happier Lives Institute, which aims to find the most cost-effective ways to improve global wellbeing. Caspar’s research focuses on the measurement and determinants of wellbeing. Regarding measurement, he works on improving the comparability of survey data on people's feelings and analyses whether such data can measure welfare cardinally. Concerning determinants, he investigates how social comparisons and inequalities, particularly with respect to people's incomes, shape wellbeing. Beyond these foci, he is interested in the wider normative implications of using subjective data, questions of welfare measurement more generally, the determinants and consequences of social mobility, as well as developments in causal inference and machine learning. In December 2020, Caspar completed a DPhil in Social Policy at Nuffield College and the Department of Social Policy & Intervention under the supervision of Brian Nolan (INET, Oxford) and Maarten Vendrik (SBE, Maastricht).

The webinar will be held in English via Cisco Webex and recorded

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