Survey will open in a new window or redirect momentarily, please keep this tab open! If the survey does not open, please enable popups and refresh the page.



Customer Discrimination and Quality Signals: A Field Experiment with Healthcare Shoppers

Study ID sspp-2021-0025-v1

General Details

Project Customer Discrimination and Quality Signals
Study ID sspp-2021-0025-v1
Study Title Customer Discrimination and Quality Signals: A Field Experiment with Healthcare Shoppers
Authors Alex Chan
Completion Time 10 Minutes
Close Date Aug. 14, 2021
Discipline Economics
Field Health Economics, Labor Economics, Experimental Economics
Country United States, Online (many countries)
In this paper, I evaluate customer preferences in the field with an online platform where cash paying consumers can shop and book a provider for medical procedures. I address whether customers discriminate against doctors on the basis of race and to what extent is such discrimination statistical. Literature has suggested two fundamental mechanisms for discrimination: statistical discrimination and taste-based discrimination . Taste-based discrimination theory suggests that customers chooses as if there is a dis-utility of associating with a particular racial group. Even with perfect information, taste- based discrimination cannot be eliminated. Unlike taste-based discrimination, statistical discrimination can be eliminated when enough information is shared to signal quality and therefore the value of a prospective purchase to customers, because they can rely on information other than race to update their beliefs about the doctor. A critical test for whether discrimination is statistical in nature is to see whether the introduction of an economically relevant signal closes the racial gap. I seek to distinguish between these forms of discrimination by comparing the willingness to pay penalty for Black or Asian doctors in the case where no quality signals are provided against the case where quality signals are provided. (J71, I11, L15, L86, M31)

Forecast Distributions

When uploading forecasting surveys, authors are asked to select several key questions which are often the questions they think are the most important to the study.

View Key Question Response Distribution:

Alex Chan. 2021. "Customer Discrimination and Quality Signals: A Field Experiment with Healthcare Shoppers." Social Science Prediction Platform. July 15.