Immigration and Political Selection

Last registered on August 07, 2019

Pre-Trial

Trial Information

General Information

Title
Immigration and Political Selection
RCT ID
AEARCTR-0004466
Initial registration date
August 07, 2019

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 07, 2019, 5:34 PM EDT

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

Locations

Region

Primary Investigator

Affiliation
UC Berkeley

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2019-08-08
End date
2019-08-23
Secondary IDs
Abstract
In this project I study how immigration and economic information shocks affect political preferences. After viewing a projection of either future immigration or job automation, subjects are asked to choose between fictional political candidates. The candidates' social background, stances on immigration and redistribution are cross-randomized. This allows me to study whether (1) immigration and economic shocks change subjects' choice over political candidates, and (2) whether the change can be attributed to social background or preferred policy.
External Link(s)

Registration Citation

Citation
Jensen, Katarina. 2019. "Immigration and Political Selection." AEA RCT Registry. August 07. https://doi.org/10.1257/rct.4466-1.0
Former Citation
Jensen, Katarina. 2019. "Immigration and Political Selection." AEA RCT Registry. August 07. https://www.socialscienceregistry.org/trials/4466/history/51420
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
The study has three treatment arms. In each of the treatment arms, subjects are first informed that they are about the view a projection conducted by a panel of experts, and that they will be asked follow-up questions about the information.

After the first page, subjects view a 30 second animation that shows information about immigration, automation, or population growth in Denmark. In the immigration treatment arm, subjects view a projection of immigration in Denmark until 2050 from Statistics Denmark. In the automation treatment arm, subjects view a projection of the number of current jobs that will be automated by 2040 in Denmark based on estimates from the automation literature. Finally, in the control arm subjects view a projection of the Danish population until 2050 from Statistics Denmark.

In all three treatment arms, the animation page is followed by a page where subjects are asked follow-up questions. This is to check if they can recall the information shown to them.
Intervention Start Date
2019-08-08
Intervention End Date
2019-08-23

Primary Outcomes

Primary Outcomes (end points)
Preferences over political candidates; specifically, whether subjects prefer low SES, anti-immigration, and/or anti-redistribution candidates.
Primary Outcomes (explanation)
Preferences over political candidates is an outcome constructed by looking at 4 pairs of fictional candidates, or "Vignettes". For each candidate I include information on their name, education, job, stance on immigration, stance on redistribution, marital status and hobbies. Name, education, job, and hobbies are clustered to indicate socioeconomic status, either high SES (e.g. master's degree, chief economist, likes sailing) or low SES (e.g. professional training, mechanic, watches champion's league). Immigration stance is either for or against accepting new refugees, and redistribution stance is either for or against increasing the demands on cash benefit recipients.

The three dimensions of interest are SES, immigration stance and redistribution stance. In three of the Vignettes, candidates vary on one of the dimensions and are identical on the other two. As an example, in one Vignette on candidate is for increased immigration and the other is against, but they are both for (against) increased demands on cash benefit recipients and both high (low) SES. In the 4th Vignette, one candidate is low SES and the other is high SES, and the policy stances are identical. However, their language varies, so that the low SES criticizes the state of affairs while the high SES candidate uses more neutral language. These four Vignettes allow me to look at the effects of treatment on preferring (1) an anti-immigration candidate (2) an anti-redistribution candidate, (3) a low SES candidate (in the case where the language of the low and high SES candidate is the same, as well as in the case where the language differs). Because I hold the other two dimensions constant I consider only the effect of e.g. SES, and not SES as a possible proxy for immigration/redistribution stance.

Secondary Outcomes

Secondary Outcomes (end points)
Policy preferences over immigration and redistribution, and trust in politicians.
Secondary Outcomes (explanation)
In these questions we ask respondents about their views on certain policies, e.g. financial aid, cash benefits, benefits to refugees, and trust that politicians do what is right.

Experimental Design

Experimental Design
First, we collect basic covariates, such as income, urbanization, and party ID. Respondents are then randomized, in equal proportion, into three treatment arms. These treatment arms are described under "intervention". Then we show the fictional candidates described under "primary outcomes", ask subjects to rank the three policies that they care most about. We then ask questions about beliefs about e.g. Denmark's future economy and number of immigrants. Then we ask the questions described under "secondary outcomes". Finally, we ask which proportion of different groups the responds believe that immigrants make up (e.g. financial aid recipients and cash benefit recipients).
Experimental Design Details
Randomization Method
Randomization is done by a computer, using YouGov's algorithm.
Randomization Unit
Individual randomization
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2000 individuals
Sample size: planned number of observations
2000 individuals
Sample size (or number of clusters) by treatment arms
About 640 individuals in control and each of the two treatment arms. 70 individuals answer a supplementary survey, and do not participate in the experiment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
UC Berkeley Committee for Protection of Human Subjects
IRB Approval Date
2019-07-05
IRB Approval Number
2019-03-11990

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials