Towards a Universal Strategy for Estimating and Reducing Waste in Public Health Insurance Programs

Faculty Supervisor(s):

Chima Ndumele and Jacob Wallace


Project Description:

We are seeking a pre-doctoral fellow to work with us on a research project that examines the drivers of waste and inefficiency in the US Health Care System. The project leverages a natural experiment, wherein near-elderly Medicaid recipients age into Medicare, to estimate how distinct insurance program incentives shape the behavior of recipients and providers.

The aims of the project are to: (1) estimate the extent of waste in the Medicaid and Medicare programs; (2) measure the causal impact of changes in insurance on the use of wasteful services; and (3) identify the tradeoffs between the use of wasteful and effective care services. The project will involve analysis of large Medicaid and Medicare claims databases, estimating models, creating presentations, and helping to prepare manuscripts. Fellows may have the opportunity to co-author papers with the research team and will regularly interact with faculty inside and outside of Yale. We encourage our fellow to take classes while they are at Yale and participate in various economics seminars happening across campus. The fellow will also receive dedicated research training and career development skills with their Tobin pre-doctoral fellow cohort.


Requisite Skills and Qualifications:

Candidates should have a long-term interest in pursuing economics-related research and be completing or have completed a Bachelors or Master’s degree. The ideal applicant will have strong programming skills. Preference will be given to detail-oriented applicants with previous research and programming experience, particularly in working with large datasets, in either Python, R, or Stata. We also encourage individuals with previous experience in economic consulting to apply. 


Special Application Instructions:

None.

LINK TO APPLICATION PAGE:

https://tobin.yale.edu/fellowships/pre-doctoral-fellows-program/apply