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Statistical or Taste-Based Discrimination? Evidence on the Basis for Race and Gender Biases in Citizens’ Choice of Service Provider

Last registered on July 04, 2019
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Pre-Trial

Trial Information

General Information

Title
Statistical or Taste-Based Discrimination? Evidence on the Basis for Race and Gender Biases in Citizens’ Choice of Service Provider
RCT ID
AEARCTR-0004050
Initial registration date
March 25, 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
April 06, 2019, 3:20 PM EDT

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

Last updated
July 04, 2019, 3:35 AM EDT

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

Locations

Country
Denmark
Region

Primary Investigator

Name
Mogens Jin Pedersen
Affiliation
University of Copenhagen
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
Completed
Start date
2019-05-01
End date
2019-05-14
Keywords
Governance, Welfare
Additional Keywords
JEL code(s)
Secondary IDs
Abstract
Research finds evidence for race and gender biases in state-citizen interactions, public hiring and advancement, and citizens’ dealings with government and the public administration. What is the main determinant of these biases? On the one hand, statistical discrimination theory suggests that discrimination takes the form of stereotyping based on group membership that results from imperfect information. Discrimination results from a rational behavioral response to uncertainty (i.e., informational bias). On the other hand, taste-based discrimination theory suggests that discrimination results from some sort of animus towards members of an out‐group. Discrimination results from a cognitive bias.

The proposed study examines the relevance of statistical vs. taste-based models of discrimination in the context of citizens’ choice of service provider. Using a survey experiment design, we present 2,000 Danish citizens to three vignettes, each describing a scenario in which the respondents are asked to choose between two potential service providers. In each vignette, we manipulate the race/gender of the two service providers. Moreover, we manipulate provision of information suggesting that the two potential service providers are equally and highly competent and trustworthy (thus minimizing informational bias).
External Link(s)

Registration Citation

Citation
Pedersen, Mogens Jin. 2019. "Statistical or Taste-Based Discrimination? Evidence on the Basis for Race and Gender Biases in Citizens’ Choice of Service Provider." AEA RCT Registry. July 04. https://doi.org/10.1257/rct.4050-2.1
Former Citation
Pedersen, Mogens Jin. 2019. "Statistical or Taste-Based Discrimination? Evidence on the Basis for Race and Gender Biases in Citizens’ Choice of Service Provider." AEA RCT Registry. July 04. https://www.socialscienceregistry.org/trials/4050/history/202205
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
The intervention consists of manipulation of information about gender, race, and competence in a survey.
Intervention Start Date
2019-05-01
Intervention End Date
2019-05-14

Primary Outcomes

Primary Outcomes (end points)
Reported choice of service provider
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Reported beliefs about the service providers’ quality of service and trustworthiness
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The study involves a survey with three experimental vignettes. Respondents are citizens age 18-65 in Denmark.

Each of the three vignettes involve a distinct scenario in which the respondents are asked to choose between two potential service providers. Using a 4 x 2 factorial design, we manipulate both (a) the race or gender of the two potential service providers (e.g., male-male, female-female, male-female, or female-male) and (b) provision of an informational cue suggesting that the two potential service providers are equally and highly competent and trustworthy (i.e., information or no information).

The order of the vignettes is counterbalanced.
Experimental Design Details
The study involves a survey with three experimental vignettes. Respondents are citizens age 18-65 in Denmark.

Each of the three vignettes involve a distinct scenario in which the respondents are asked to choose between two potential service providers. Using a 4 x 2 factorial design, we manipulate both (a) the race or gender of the two potential service providers (e.g., male-male, female-female, male-female, or female-male) and (b) provision of an informational cue suggesting that the two potential service providers are equally and highly competent and trustworthy (i.e., information or no information).

Vignette 1: Describes a scenario involving choice of general practitioner. We manipulate the gender of the two potential general practitioners (e.g., male-male, female-female, male-female, or female-male) and provision of an informational cue suggesting that the two general practitioners are equally and highly competent and trustworthy (i.e., information or no information).

Version 2: Describes a scenario involving choice of a babysitter. We manipulate the gender of the two potential babysitters (e.g., male-male, female-female, male-female, or female-male) and provision of an informational cue suggesting that the two babysitters are equally and highly competent and trustworthy (i.e., information or no information).

Version 3: Describes a scenario involving choice of home cleaner. We manipulate the race of the two potential home cleaner s (e.g., Dane & Dane, non-Dane & non-Dane, Dane & non-Dane, or non-Dane & Dane) and provision of an informational cue suggesting that the two home cleaners are equally and highly competent and trustworthy (i.e., information or no information).

The order of the vignettes is counterbalanced.
Randomization Method
Randomization is carried out by simple randomization by computer
Randomization Unit
The individual survey respondent.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2,000 individuals
Sample size: planned number of observations
2,000 individuals
Sample size (or number of clusters) by treatment arms
2,000 individuals (250 in each treatment arm, cf. the 4 x 2 factorial design)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
May 14, 2019, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
May 14, 2019, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
2,024 individuals
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
2,024 individuals
Final Sample Size (or Number of Clusters) by Treatment Arms
2,024 individuals (app. 250 in each treatment arm, cf. the 4 x 2 factorial design)
Data Publication

Data Publication

Is public data available?
Yes
Public Data URL
https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/5EJ0FG

Program Files

Program Files
Yes
Program Files URL
https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/5EJ0FG
Reports, Papers & Other Materials

Relevant Paper(s)

Abstract
People experience discrimination across a variety of domains, including at work and in dealings with public institutions, but what makes some individuals discriminate against others? Two dominant scholarly approaches—“statistical” and “taste-based”—offer different explanations. Statistical discrimination models imply that discrimination occurs because of incomplete information (informational bias), whereas taste-based discrimination models emphasize more elusive and deep-rooted cognitive biases. Adding new insights into whether discrimination is “statistical” or “taste-based,” this article examines how providing information that reduces informational bias affects discrimination. Using a preregistered survey experimental design, a representative sample of Danish residents (n = 2,024) are exposed to three unique vignettes, each involving a choice of service provider (general practitioner, babysitter, and house cleaner). Relating to gender and nativity stereotypes, we manipulate the gender of the general practitioners and the babysitters, and the country of origin of the house cleaners. Moreover, we manipulate exposure to rating cues about the service providers’ task performance, thus mitigating informational bias to some extent. Contrasting the expectations of statistical discrimination models, the performance ratings cues do not mitigate discrimination. Across all three vignettes, the participants exhibit stereotypical preferences, and the performance rating cues do not affect these discriminatory biases.
Citation
Mogens Jin Pedersen, Vibeke Lehmann Nielsen, Understanding Discrimination: Outcome-Relevant Information Does Not Mitigate Discrimination, Social Problems, 2022;, spac006, https://doi.org/10.1093/socpro/spac006
URL
https://academic.oup.com/socpro/advance-article-abstract/doi/10.1093/socpro/spac006/6526667

Reports & Other Materials