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Representative Evidence on Social Mobility and Distributional Preferences

Last registered on February 22, 2021
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Pre-Trial

Trial Information

General Information

Title
Representative Evidence on Social Mobility and Distributional Preferences
RCT ID
AEARCTR-0002764
Initial registration date
March 06, 2018

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
March 07, 2018, 2:54 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
February 22, 2021, 3:19 AM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country
Germany
Region

Primary Investigator

Name
Dietmar Fehr
Affiliation
University of Heidelberg
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Other Primary Investigator(s)

PI Name
Daniel Muller
PI Affiliation
University of Innsbruck
Contact Investigator
PI Name
Marcel Preuss
PI Affiliation
University of Mannheim
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Additional Trial Information

Status
Completed
Start date
2018-01-01
End date
2021-02-21
Keywords
Welfare
Additional Keywords
Distributional preferences, intergenerational mobility, redistribution, equality of opportunity, fairness
JEL code(s)
C93, D63, D31, H23, J62
Secondary IDs
Abstract
The recent surge in income and wealth inequality has rekindled the public and economic debates about the causes and consequences of inequality. While inequality is to some extent inevitable, its acceptance critically hinges on individuals’ views about the fairness of inequality. An important aspect of individuals’ tolerance for inequality is their perception of social mobility. If people believe that they face ex-ante equal prospects and that they can move up the social ladder, they may be willing to accept more inequality.
In this project, we investigate the relationship between intergenerational mobility and distributional preferences, which are key inputs into social policy measures and individual decision‐making. We implemented a survey module in a representative panel study of Germans. This survey module allows us to present a randomly selected subgroup information about actual mobility rates in Germany and subsequently measure participants’ distributional preferences in an incentivized way.
External Link(s)

Registration Citation

Citation
Fehr, Dietmar, Daniel Muller and Marcel Preuss. 2021. "Representative Evidence on Social Mobility and Distributional Preferences." AEA RCT Registry. February 22. https://doi.org/10.1257/rct.2764-1.3
Former Citation
Fehr, Dietmar, Daniel Muller and Marcel Preuss. 2021. "Representative Evidence on Social Mobility and Distributional Preferences." AEA RCT Registry. February 22. https://www.socialscienceregistry.org/trials/2764/history/200118
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention (Hidden)
Intervention Start Date
2018-01-01
Intervention End Date
2018-03-07

Primary Outcomes

Primary Outcomes (end points)
x,y score (based on incentivized Equality Equivalence Test - EET)
Preference for redistribution (survey question 11-point scale)
Educational expenditures (survey question 5-point scale)
Primary Outcomes (explanation)
x,y scores will be constructed as proposed by Kerschbamer, 2015 and Kerschbamer and Muller, 2017.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We run our experiment on a representative sample of Germans. We present a random subsample or respondents with information on social mobility in Germany and subsequently measure all respondents' other-regarding preferences using an incentivized elicitation method. The panel structure of the survey allows us to draw on rich information about socio-economic characteristics of respondents as well as their attitudes toward redistribution, social policies, health, education, etc.
Experimental Design Details
Randomization Method
Randomization at individual level through survey software.
Randomization Unit
At individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
About 3,000
Sample size: planned number of observations
About 3,000
Sample size (or number of clusters) by treatment arms
750 EET neutral control, 375 EET rich control, 375 EET poor control
750 EET neutral treatment, 375 EET rich treatment, 375 EET poor treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

Documents

Document Name
Survey Module
Document Type
survey_instrument
Document Description
Survey
File
Survey Module

MD5: 5a5bde32c59f1c85190377cbeb18bb44

SHA1: be4103404228323c94d2b4f922faf5b2aa12090f

Uploaded At: March 06, 2018

IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
January 31, 2018, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
January 31, 2018, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
1,332
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
2,664
Final Sample Size (or Number of Clusters) by Treatment Arms
1,332 control & 1,332 treatment
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials