Predoctoral Fellowship Opportunities

SIEPR Predoc Projects

Building and Evaluating AI Products for Economic Applications (Susan Athey)

The Golub Capital Social Impact Lab (GC Lab) at Stanford Graduate School of Business focuses on developing, applying, and testing cutting-edge digital tools to improve the effectiveness of the social sector and catalyze innovation directed at social challenges. We are seeking a highly skilled and motivated individual to work on building and evaluating products built using Large Language Models (LLMs) that will be used to address social problems in domains such as early childhood education and post-secondary career counseling. Based on the successful candidate’s skills, the position will involve engineering Python pipelines that access LLM APIs, designing and analyzing experiments using advanced causal inference tools including machine learning, and working with large-scale data from partner organizations. Predoctoral scholars in the GC Lab are mentored to develop the skills needed for success in top PhD programs in economics, computer science, and related fields. 

Preferred qualifications: (i) strong quantitative background; (ii) programming skills in Python, including statistical analysis; (iii) excellent documentation habits and willingness to follow processes that ensure replicable and transparent science; (iv) interest in pursuing research-oriented graduate study in economics, computer science, or related fields. Preferred / bonus: (v) experience working with LLMs through APIs; (vi) experience with causal inference tools and/or machine learning.

Economics of Medical Care Delivery (Laurence Baker and Eric Sun)

The successful candidate will work on multiple projects related to the economics of health care delivery.  Projects may evaluate economic issues related to the size and organization of physician practices, hospital systems and hospital care, cost sharing for health care, the effects of changes in medical practice ownership (e.g. the role of private equity), and the ways that health insurance influences health care delivery.  Projects often evaluate the effects of these factors on the ways that medical care is provided, the prices of services, total cost of care, and quality of care.  Projects often focus on questions with implications for the design of government policies related to the health care system. The position will entail working with large restricted administrative datasets, particularly claims data from the US Medicare program, but also including data on care for Medicaid patients, privately insured patients, and others.  The primary activities associated with the position will be writing computer programs to manage and construct data sets and carry out econometric analyses such as event study models, and models using instrumental variables.  Analyses may also include creating reports and visualizing results of analyses.

Preferred qualifications:  Enthusiasm for research and strong quantitative background are required, with preference given to those with prior coding experience and knowledge of Stata. Interest in the topics being studied is valuable, though prior work in these areas is not required.

The Impact of Nonprofit Governance on Performance (Daniel Kessler) 

This project seeks to identify how the governance structure of nonprofit organizations, including hospital systems and universities, affect their performance.  Governance structure includes the characteristics of the board of directors, top management, and the legal form of the organization.  Performance includes the cost and quality of the services that the organization supplies.  The project matches data on boards of directors, top management, and legal form from IRS filings with data on performance from US government surveys (universities) and individual-level health care claims data from Medicare (hospital systems).  Duties:  Development of large data sets; statistical analysis; interpretation of results.  

Preferred qualifications: Experience with statistical programming languages, particularly Stata and/or R, is required. A background in economics is preferred, as is knowledge of (or interest in learning about) the US healthcare system.

Economic Policy Research (Neale Mahoney) 

This position will work on a broad portfolio of economic research and economic policy projects. This includes projects on U.S. healthcare, consumer finance, energy markets, housing, and childcare. Research assistants work on all aspects of projects from the generation of ideas, to cleaning and preparation of data, to quantitative analysis and structural estimation, to working with regulators to understand policy issues and develop possible solutions. 

Preferred qualifications: (i) strong quantitative and computer skills, including programming,  (ii) strong communication and interpersonal skills, (iii) the ability to work independently to solve problems sometimes on tight timelines, and (iv) a long-term interest in economic policy and economic research. Background in economics is a plus, but not necessary–I welcome candidates with strong backgrounds who are looking for more exposure to economics.

Healthcare Economics (Maria Polyakova)

The position will work on multiple projects in health economics that use large administrative datasets, including Medicare, Medicaid, tax data, and employer-employee matched labor market data. Topics will cover the relationship between health shocks and the family, labor markets for healthcare providers, and public funding in health insurance markets. The pre-doctoral fellow will be expected to write programming scripts to analyze and visualize the data, create research reports, and actively participate in regular team meetings. This position is ideal for a candidate interested in learning more about the health care systems of the US and Europe, although no prior knowledge is expected. 

Preferred qualifications: Attention to detail, willingness to learn to create effective visualizations, and fluency with Stata. Knowledge of SAS, R, and Python is a plus, but not required.

Public Policies and the Well-Being of Families (Petra Persson and Maya Rossin-Slater)

Our joint research agenda is centered around understanding how policies and other factors affect the health and well-being of families with children. We use large-scale administrative data together with natural experiment research designs to deliver causal estimates that are highly relevant to policy-makers. Examples of projects in progress include: (1) studies on the impacts of various healthcare interventions on maternal health and economic well-being; (2) estimating the causal impacts of access to reproductive healthcare on mental and physical health outcomes of low-income young women; (3) analyzing the impacts of exposure to violence on children's short- and long-term outcomes. The position will involve research assistance for several projects on topics related to maternal and child health, and family structure and well-being. The projects use large-scale administrative data sets, and deliver implications for current policy debates. The fellow will receive exposure to and training in a broad set of applied microeconomics research methods, analyzing large and complex data sets,, and will become knowledgeable about current policies targeting disadvantaged populations. Several of the projects require obtaining Special Sworn Status (SSS) from the U.S. Census Bureau in order to access and work with the data. Applicants are responsible for reviewing the eligibility requirements listed on the U.S. Census Bureau’s official website. Eligibility will be verified during the interview process.

Preferred qualifications: Experience using statistical software (Stata, R, or Python) with large-scale data, detail-oriented, interest in applied microeconomics research, excellent communication skills, ability to work independently, strong time management skills.