Preferences for Redistribution and Social Mobility: The Role of Motivated Beliefs.

Last registered on August 09, 2022

Pre-Trial

Trial Information

General Information

Title
Preferences for Redistribution and Social Mobility: The Role of Motivated Beliefs.
RCT ID
AEARCTR-0009833
Initial registration date
August 05, 2022

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
August 09, 2022, 4:27 PM EDT

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

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Primary Investigator

Affiliation
Technical University Munich

Other Primary Investigator(s)

PI Affiliation

Additional Trial Information

Status
In development
Start date
2022-08-15
End date
2022-10-14
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
People who believe to live in a society with high social mobility generally prefer significantly less redistribution. However, people hold highly inaccurate beliefs about the amount of social mobility. A plausible reason why these beliefs are so inaccurate is that people do not only form beliefs with the intention to maximize accuracy, but rather they might also hold motivated beliefs. With our study we aim to understand (i) whether people hold motivated beliefs with regards to social mobility and, if they do, (ii) which kinds of motivated beliefs are most important in influencing their redistribution preferences.
We study two types of motivated beliefs about social mobility that relate to preferences for redistribution. For one, people might be overconfident with respect to the degree of upward mobility that they will experience, which leads them to prefer less redistribution. Apart from that, people may hold a specific redistribution preference in the first place and then form their beliefs about social mobility in order to justify their redistribution preferences.
We test for (i) the existence of overconfidence and/or "justifying beliefs" with regards to social mobility as well as (ii) their relative importance for the redistribution preferences in an online experiment on Prolific.
In the control group, subjects perform an effort task and indicate their belief about their rank in the effort task. A subject’s payoff is either determined by her rank in the effort task or by sheer luck. We tell subjects about their payoff, but not whether it was their effort or luck that determined this payoff. We then ask subjects about how likely they think it is that their payoff was determined by effort rather than luck. After that, subjects get to vote on the amount of a redistributional tax which comes at an efficiency cost. In the control group, neither overconfidence nor justifying beliefs matter for the preferences for redistribution by design.
In our overconfidence treatment, we allow overconfidence to affect the redistribution preferences by not telling subjects about their payoff before the vote for their preferred tax rates, thereby giving overconfident subjects room to state a lower preferred tax rate compared to the absence of overconfidence. In our justifying beliefs treatment, subjects are aware of the subsequent tax voting when they are asked about their beliefs regarding the role of effort vs luck. Thus, they can potentially report higher (lower) beliefs about the importance of effort in determining payoffs in order to justify a low (high) redistribution preference.
We compare differences in beliefs and preferred tax rates across treatments in order to assess whether or not motivated beliefs about social mobility exist in our setting at all and, if they do, in order to assess their impact on preferences for redistribution.

External Link(s)

Registration Citation

Citation
Kurschilgen, Michael and Gabriel Vollert. 2022. "Preferences for Redistribution and Social Mobility: The Role of Motivated Beliefs.." AEA RCT Registry. August 09. https://doi.org/10.1257/rct.9833
Experimental Details

Interventions

Intervention(s)
We study two types of motivated beliefs about social mobility that relate to preferences for redistribution. For one, people might be overconfident with respect to the degree of upward mobility that they will experience, which leads them to prefer less redistribution. Apart from that, people may hold a specific redistribution preference in the first place and then form their beliefs about social mobility in order to justify their redistribution preferences. We test for (i) the existence of overconfidence and/or "justifying beliefs" with regards to social mobility as well as (ii) their relative importance for the redistribution preferences in an online experiment on Prolific.

In our experiment, subjects perform an effort task and receive a payoff which may or may not depend on their performance in the effort task. We interpret the degree to which subjects can actually influence their own payoff via effort provision as the amount of social mobility in our setting. After the effort task subjects enter a redistribution stage, where they vote on a preferred redistributive tax to determine the final payoffs for everyone. In our control treatment we ask subjects without them knowing of the redistribution stage about their belief that effort rather than luck was deterministic for their pre-tax payoff payments. In our justifying beliefs treatment we ask subjects the same question, but inform them about the existence of a redistribution stage prior to the question. With this information they can potentially form their beliefs in order to justify their preferred redistribution demand. Our overconfidence treatment is also similar to our control treatment, the difference here being that we do not inform subjects about their pre-tax payoff in the overconfidence treatment. Thus, overconfidence matters for the decision on the preferred tax rate in our overconfidence treatment, but not in our control treatment, since subjects already know their own payoffs in the control treatment. Across all our treatments we additionally vary the probability with which effort rather than luck determines payoffs. We do this in order to gain an understanding of how motivated beliefs are formed under different levels of social mobility.
Intervention Start Date
2022-08-19
Intervention End Date
2022-08-26

Primary Outcomes

Primary Outcomes (end points)
We have two types of primary outcomes: Beliefs and the preferred tax rate.

1.) Beliefs:
1.1: Effort Performance Beliefs: We measure the beliefs about subjects' own rank in the effort task. This allows us to estimate the degree of overconfidence for each subject.
1.2: Payoff Determination Belief: We also measure the beliefs that subjects state regarding the probability that their payoff was determined by effort rather than luck. We compare these beliefs between the justifying beliefs treatment and the control treatment conditional on the payoff of each subject.

The measurement of beliefs allows us to assess, whether or not / to what degree overconfidence and justifying beliefs exist in our setting. While this is of interest for us, we further want to understand whether and to which extent the existence of such motivational beliefs influences preferences for redistribution. Therefore, we measure the preferred tax rates.

2.) Preferred tax rate: We measure the tax rate (in %) that subjects indicate as their preferred tax rate in the experiment. We compare this tax rate between our treatments.

Regarding the justifying beliefs treatment, we compare the preferred tax rate to the preferred tax rates in the control treatment conditional on the pre-tax payoff. According to our null hypothesis we expect subjects with a high (low) pre-tax payoff to vote for lower (higher) taxes in the justifying beliefs treatment relative to the control treatment due to the possibility to justify their preferred redistribution preference. We also compare preferred tax rates for different effort/luck combinations in determining the payoffs between the justifying beliefs and the control treatment. We hypothesize similar differences in preferred taxes between the justifying beliefs and the control treatment (in contrast to the comparison of the overconfidence and control treatment, see below).

Regarding the overconfidence treatment we compare the preferred tax rates between our overconfidence treatment with the preferred tax rates in our control treatment. We expect the preferred tax rates to be relatively lower on average in the overconfidence treatment. We also compare preferred tax rates for different effort/luck combinations in determining the payoffs between the overconfidence and the control treatment. We hypothesize that a possible gap in preferred taxes between the overconfidence and the control treatment reduces with stronger luck dependence.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
As secondary outcomes we measure risk preferences of subjects. Besides, standard data on subjects' demographic background will be provided to us by Prolific. The measurement of risk preferences is important, because in our overconfidence treatment subjects make their tax choice without knowing their own payoffs, which makes risk preferences relevant for their decision. By controlling for risk preferences we can eliminate the effect of risk preferences in our analyses.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
At the start of our experiment subjects perform an effort task, more specifically the slider task of Gill and Prowse (2012). We ask subjects to indicate their belief regarding their own performance in the effort task relative to others. Afterwards, subjects receive a payoff which is either determined on the basis of their performance in the effort task or determined by sheer luck. Whether a subject's payoff is determined by effort or luck is random: With a specific probability p, effort is deterministic for the payoff. We vary this probability p across all our treatments using three different values for p, which are 0.8, 0.5 and 0.2. After subjects have learnt their payoff, we ask them to state how likely it is that their payoff was determined by effort rather than luck. Finally, subjects vote upon a redistributive tax with efficiency losses, which influences their own and other subjects' payoffs. We also record subjects' risk preferences and other demographic variables in a questionnaire after the experiment.

The above mentioned design is exactly the design in our control group.
In our justifying beliefs treatment we tell subjects about the existence of a redistribution stage before they indicate their beliefs regarding whether it was effort or luck which determined their pre-tax payoffs. Thus, subjects can possibly alter their belief report in order to justify a specific redistribution preference, a behavior which is impossible in our control treatment due to the unawareness of a redistribution stage being played later.
In our overconfidence treatment we also stick to the above mentioned design of the control group, except for the fact that we do not tell subjects about their pre-tax payoffs. Thus, overconfidence can potentially affect their preferred tax rates.
Experimental Design Details
Not available
Randomization Method
We run the experiment online via Prolific. We embed our experiment in Prolific such that an individual is randomly allocated to a treatment group when participating in our experiment. The exact randomization method will be chosen according to Prolific's standard method for RCTs.
Randomization Unit
We randomize on the individual level i.e. every individual is randomly allocated to exactly one treatment. No individual can be in two treatments.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
No clustering.
Sample size: planned number of observations
About 450 subjects from the online Platform Prolific. The exact feasible sample size will depend on the completion time that subjects need for the experiment, as subjects are paid per hour on Prolific. We can only estimate a rough completion time of our experiment at this point, which is why the estimated 450 participants should be considered a rough estimate.
Sample size (or number of clusters) by treatment arms
50 per treatment.
Explanation: We have one control group, the justifying belief treatment and the overconfidence treatment. Across these three treatment groups we vary the amount of effort versus luck which determines payoffs. We use three different effort versus luck parameter constellations: High effort importance, medium effort importance, and low effort importance. Thus, we have a 3x3 treatment design yielding 9 different treatments.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number