Data and Code for "Gender Differences in Medical Evaluations: Evidence from Randomly Assigned Doctors"
Principal Investigator(s): View help for Principal Investigator(s) Marika Cabral, University of Texas-Austin; Marcus Dillender, Vanderbilt University
Version: View help for Version V1
| Name | File Type | Size | Last Modified |
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| code | 10/10/2023 10:12:AM | ||
| data | 04/10/2023 09:04:AM | ||
| output | 04/10/2023 09:04:AM | ||
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text/plain | 16.7 KB | 04/12/2023 07:24:AM |
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application/pdf | 257.1 KB | 10/11/2023 07:30:AM |
Project Citation:
Cabral, Marika, and Dillender, Marcus. Data and Code for “Gender Differences in Medical Evaluations: Evidence from Randomly Assigned Doctors.” Nashville, TN: American Economic Association [publisher], 2024. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-01-29. https://doi.org/10.3886/E188361V1
Project Description
Summary:
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Little is known about what drives gender disparities in health care and related social insurance benefits. Using data and variation from the Texas workers’ compensation program, we study the impact of gender match between doctors and patients on medical evaluations and associated disability benefits. Compared to differences among their male patient counterparts, female patients randomly assigned a female doctor rather than a male doctor are 5.2% more likely to be evaluated as disabled and receive 8.6% more subsequent cash benefits on average. There is no analogous gender-match effect for male patients. Our estimates indicate that increasing the share of female patients evaluated by female doctors may substantially shrink gender gaps in medical evaluations and associated outcomes.
Funding Sources:
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National Science Foundation (CAREER Award 1845190);
United States Social Security Administration (RDR18000003 through the Retirement and Disability Research Consortium)
Scope of Project
JEL Classification:
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I10 Health: General
I10 Health: General
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