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Experience of social mobility and support for redistribution: Beating the odds or blaming the system?
Last registered on April 20, 2021

Pre-Trial

Trial Information
General Information
Title
Experience of social mobility and support for redistribution: Beating the odds or blaming the system?
RCT ID
AEARCTR-0007580
Initial registration date
April 19, 2021
Last updated
April 20, 2021 6:29 AM EDT
Location(s)

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Primary Investigator
Affiliation
King's College London
Other Primary Investigator(s)
Additional Trial Information
Status
In development
Start date
2021-04-21
End date
2021-06-30
Secondary IDs
Abstract
Perceptions of social mobility in society are one of the most important determinants of individuals’ preferences for redistribution and tolerance for economic inequalities. How the experience of social mobility affects people’s redistributive preferences is however so far little understood. Using cross-country survey data, a newly generated dataset on social mobility and a survey experiment, I examine the effects of experienced social mobility on support for redistribution at the individual level. The survey data, including respondents from 27 countries questioned across three decades, indicates a divide between people who experienced downward mobility as opposed to upward mobility – experiencing downward mobility increases support for redistribution while experiencing upward mobility does not affect redistributive preferences. This finding can be explained by how people’s own mobility experience affects their perceptions of opportunities within society. In line with the self-serving bias, those with negative mobility experiences ‘blame the system’ and extrapolate from their negative experience onto society at large, which increases their demand for redistribution. Conversely, those who experienced positive mobility believe they ‘beat the odds’ and, therefore, do not extrapolate from their experience onto perceptions of societal mobility, leading to no less support for redistribution. This relationship suggests significant implications at the aggregate: As overall absolute mobility increases, ceteris paribus, demand for redistribution rises. In an online survey experiment I test the causality of this mechanism.
External Link(s)
Registration Citation
Citation
Weber, Nina. 2021. "Experience of social mobility and support for redistribution: Beating the odds or blaming the system?." AEA RCT Registry. April 20. https://doi.org/10.1257/rct.7580-1.0.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2021-04-21
Intervention End Date
2021-06-30
Primary Outcomes
Primary Outcomes (end points)
Support for redistribution measured as agreement with a set of four different statements on governmental redistribution as well as an additional question on support for an increase in the top income tax share (based on the ISSP Social Inequality Module).
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Perceptions of social mobility in society and perceived personal benefits from governmental redistribution.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The experiment will be coded in Qualtrics with a representative subject pool of the United States population recruited via Prolific Academic. I will provide respondents with information on their personal intergenerational mobility experience and test how this information, if contradictory to their previously held beliefs, changes their support for redistribution.
Experimental Design Details
Not available
Randomization Method
Simple randomization done automatically via Qualtrics.
Randomization Unit
Individual randomization
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
900 subjects in a first experiment and, depending on the available funding, a second experiment with 3,200 additional subjects.
Sample size: planned number of observations
900 subjects in a first experiment and, depending on the available funding, a second experiment with 3,200 additional subjects.
Sample size (or number of clusters) by treatment arms
450 subjects in treatment and control in the first experiment, respectively. 1,600 in treatment and control, respectively, in a potential second experiment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
King's College London
IRB Approval Date
2020-09-23
IRB Approval Number
MRSP-19/20-21021
Analysis Plan

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