Discrimination in the health care market in India

Last registered on August 28, 2017

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Pre-Trial

Trial Information

General Information

Title

Discrimination in the health care market in India

RCT ID

AEARCTR-0002385

Initial registration date

August 26, 2017

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 28, 2017, 4:44 PM EDT

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

Locations

Country

India

Region

Primary Investigator

Name

Liang Choon Wang

Affiliation

Monash University

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Debayan Pakrashi

PI Affiliation

Indian Institute of Technology

Contact Investigator

PI Name

Asadul Islam

PI Affiliation

Monash University

Contact Investigator

Additional Trial Information

Status

In development

Start date

2017-09-04

End date

2017-10-31

Keywords

Health, Labor

Additional Keywords

Discrimination, affirmative action, taste-based discrimination, statistical discrimination, prejudice, preferences

JEL code(s)

Secondary IDs

Abstract

This study uses a field experiment that builds on the correspondence testing methodology to test for the presence and nature of patients' discrimination against physicians from different caste groups in India.

External Link(s)

Registration Citation

Citation

Islam, Asadul, Debayan Pakrashi and Liang Choon Wang. 2017. "Discrimination in the health care market in India." AEA RCT Registry. August 28. https://doi.org/10.1257/rct.2385-1.0

Former Citation

Islam, Asadul, Debayan Pakrashi and Liang Choon Wang. 2017. "Discrimination in the health care market in India." AEA RCT Registry. August 28. https://www.socialscienceregistry.org/trials/2385/history/20921

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Experimental Details

Interventions

Intervention(s)

We examine whether patients’ preferences for physicians differ by the physician's caste and the patient's caste. In collaboration with NGO-run mobile clinics in India, the experiment will invite residents in various localities to sign up for an upcoming health service event provided by one of four potential physicians with different caste-sounding family names and years of experience.

Intervention Start Date

2017-09-10

Intervention End Date

2017-10-31

Primary Outcomes

Primary Outcomes (end points)

Preference rankings of different doctors, rankings of doctors that are consistent with taste-based discrimination, rankings of doctors that are consistent with statistical discrimination, and money allocated to various opponents in dictator games.

Primary Outcomes (explanation)

Preference rankings of doctors (patients list doctors of different years of experience and caste backgrounds from most preferred to least preferred), altruism towards different groups of people (money allocated to individuals of different backgrounds in a dictator game).

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

There are two parts to our experimental design: (1) field experiment; and (2) lab-in-the-field experiment. The field experiment uses the corresponding testing methodology typically employed in studies of discrimination. The lab-in-the-field experiment uses experimental games that involve allocation of money to different individuals.

Experimental Design Details

We will target 40 clusters (district centres/villages) with 80-90 participants per cluster, giving a total sample of roughly 3,500 participants. Participants will be asked to rank the physicians based on their preferences. Participants will also provide us with their name, gender, date of birth, address, and contact information, so that we can contact them about the assignment before the date of visit by the mobile-clinic and also to conduct a follow-up survey and the lab-in-the-field experiment.

Randomization Method

Randomization done in office by a computer using STATA 14.

Randomization Unit

Randomization at the individual level. In the field experiment, the targeted sample is 3500 individuals. In the lab-in-the-field experiment, the targeted sample is 600 individuals, drawn randomly from the 3500 individuals.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

3500 individuals in the field experiment and 600 individuals in the lab-in-the-field experiment.

Sample size: planned number of observations

3500 individuals in the field experiment and 600 individuals in the lab-in-the-field experiment.

Sample size (or number of clusters) by treatment arms

The field experiment is not a typical randomised controlled experiment. It follows the correspondence testing methodology used in studies on discrimination, where all individuals are treated in the experiment. The doctors' names and years of experience (treatment) shown to patients are randomly assigned to everyone, where each patient gets four different types of doctors on the list. In the lab-in-the-field experiment, all individuals are also randomly matched with four different types of individuals. Thus, the sample size in the treatment arm in the field experiment is 3500 and the sample size in the treatment arm in the lab-in-the-field experiment is 600.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

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