Applied Economics of Healthcare

Faculty Sponsor(s): 
Jason Abaluck

Project Description(s):

Professor Abaluck is recruiting one Fellow to work on the following projects:

The candidate will perform research and data analysis for several projects investigating whether consumers make informed choice and how best to design healthcare markets in light of the complexity of decision-making in this sector. For example, can consumers identify which insurers will make them healthier? If not, what might be the benefits of additional information, and how might insurers respond if consumers could determine which insurers would improve their health? These questions will be investigated using data on actual choices from large-scale administrative databases.

This position is intended to provide training in the field of economics research to prepare a candidate for doctoral studies in graduate school. This position presents an opportunity for recent graduates to begin training for a career in research and will serve as a stepping stone to doctoral studies. The successful applicant will work closely with several faculty in the Economics Group at the Yale School of Management, including: Jason Abaluck (primarily), Barbara Biasi, Rob Jensen, Fiona Scott Morton, Michael Sinkinson, and Kevin Williams. This will allow the trainee to be exposed to rigorous economic research covering a broad range of topics, such as health economics, labor economics, and industrial organization.

The trainee will be trained in how to turn the goal of the research into a detailed research design plan. The trainee will then be expected to complete detail-oriented tasks using large datasets, as well as learning to present interim results concisely while explaining the economic mechanism lying behind the results. Specific tasks requested will involve data collection, big data statistical analysis, model estimation, model simulations, and analytical derivations.

Requisite Skills and Qualifications:

Applicants must have completed a bachelor’s or master’s degree, have a strong quantitative background, and possess strong programming skills. Preference will be given to detail-oriented applicants with previous research and programming experience, particularly in working with large datasets and using Stata, Python, R, GIS and/or MatLab. Experience with Stata is especially essential.

Special Application Instructions:

Visit: . Interested applicants should submit a C.V., a cover letter describing research background and interests. You should submit a sample of code you have written. Also provide the contact information for two academic references. As part of the application review process, finalists will also be asked to complete a Stata training exercise task.

The preferred start date is January 2020, although there is some flexibility. 

Sponsor Name: