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SIEPR Predoctoral Research Fellowship Opportunities

NOW ACCEPTING APPLICATIONS

The SIEPR/Economics Predoctoral Research Fellowship program is a full-time, one- to two-year post baccalaureate program designed to prepare individuals wishing to gain valuable training and experience toward a career in academic research in economics or public policy. Fellows are appointed as non-matriculated graduate students and will be expected to fully engage in the intellectual life at Stanford University. They dedicate a significant portion of their time to an empirical research project and can take graduate-level courses at Stanford University for credit (up to one course per quarter). The fellowship offers tuition, health insurance, and a living stipend ($49,600 in 2019-2020). 

We seek highly skilled and motivated individuals to join our full-time Predoctoral Research Fellows position for a period of at least one year. The positions are based at the Institute for Economic Policy Research at Stanford University. Fellows start in June or July, although a September start date may be negotiable. International applicants are welcome to apply.

Ideal candidates will have:

  • Completed a 4-year undergraduate degree (bachelors or foreign equivalent) in economics, statistics, applied mathematics, or a related field;
  • A strong quantitative background and interest in learning cutting-edge research methods;
  • Creative and independent problem solving skills;
  • Experience programming in Stata and R, and may have experience with GIS, Matlab, and other statistical packages; and
  • An interest in pursuing a PhD in Economics or a related field.

Please review our Frequently Asked Questions before contacting SIEPR about this program.

Stanford Faculty interested in mentoring students through the program should consult our Information for Faculty.

Open Positions:

Application Period: January 31-March 31, 2020

Applications will be reviewed on a rolling basis and you are encouraged to apply early for full consideration.

SIEPR is now recruiting for open positions to start in Summer 2020. Initial appointments are for one year with the possibility of a second year based on performance. Given the high volume of applications we receive, we are not able to provide application feedback or individual responses to all candidates. SIEPR staff or faculty will contact candidates who are advanced to the next round by email. Please do not submit recommendation letters unless they are solicited. Potential applicants should be prepared to submit a CV, cover letter and unofficial transcript(s) and be willing to complete a coding task upon request.

APPLICATION FORM

SIEPR Predoctoral Research Fellowships:

The Incidence of Recessions: Evidence and Macroeconomic Implications

Professors Adrien Auclert and Issac Sorkin

Professors Auclert and Sorkin are looking for a predoctoral research fellow to work on a project aimed at understanding the impact of recessions on different workers in the data, as well as the macroeconomic implications of these patterns. The project will combine administrative labor earnings data from the United States and a general equilibrium macroeconomic model with heterogeneous agents. The fellow will get exposure to the cutting-edge of methods and concepts in applied micro- and macro-economics. Programming skills are a must, as well as a willingness to learn and enthusiasm for economics.

Changing Markets for Health Care and Health Insurance

Professor Kate Bundorf

Professor Kate Bundorf seeks a highly skilled individual to work as a Predoctoral Research Fellow for a two-year term, to begin no later than September 15, 2018. The position will involve research assistance for several projects on topics related to the U.S. health care system including studies of provider markets and public and private health insurance systems. The projects use large-scale administrative data sets, primarily public and private health insurance claims, from the United States to examine timely and policy-relevant research questions. The fellow will be exposed to a broad set of applied microeconomics research methods, will gain experience analyzing large, complex data sets and will become knowledgeable about the functioning of the U.S. health care system. Prior programming experience using SAS and/or Stata is desirable.

Consumer and Firm Behavior; and the Role of Public Policies in Dealing with Market Failures

Jose Ignacio Cuesta and Shosh Vasserman

Jose Ignacio Cuesta and Shosh Vasserman are looking for a highly skilled individual to work on projects with a strong emphasis on using data to study consumer and firm behavior and to analyze the role of public policies in dealing with market failures. José Ignacio Cuesta's is working on a set of projects that analyze the regulation of health and credit markets, including the effects of price regulation in credit markets, quality regulation in pharmaceutical markets and the effects of vertical integration in health care markets. Examples include exploiting quasi-experimental policy variation to study the effects of the policy on market outcomes, to estimating structural models of consumer and firm behavior to study the effects of counterfactual policy and measure welfare effects.

Shoshana Vasserman's work combines individual/group-level data on consumption and communication choices with rich characteristics data and economic theory to empirically evaluate large public policies and proposals. Examples include policies to constrain price-setting for drugs in the US, congestion pricing mechanisms for highways, and a la carte pricing for investigative local news stories. The work involves constructing novel datasets (often) in collaboration with government and industry partners, sophisticated processing (e.g. natural language processing and statistical modeling of non-economic variables) and visualization/story-telling, in addition to econometric analysis and structural modeling. The fellow will work on different stages of these projects. In early-stage projects, the fellow will help the team collect, clean, process, and analyze the data. In more advanced-stage projects, the fellow will work on analyzing the data, which will expose her/him to a variety of methods commonly used in applied microeconomics, and obtaining experience employing them in practice. Familiarity with data management and analysis is required and can further be developed, including Stata and R or Python. Familiarity with statistical analysis and machine learning is preferred, but interest and ambition to learn are sufficient. Enthusiasm for learning and developing computational and econometric skills will be valued.

Improving the Social Impact of US Housing Policy

Professor Rebecca Diamond

This project will evaluate the impacts of a large variety of current housing policies and regulations to better understand the mechanisms through which they impact the economic lives of households across the income distribution. Policies the pre-doc will analyze include affordable housing development subsidies, inclusionary zoning, local land-use regulation, housing choice vouchers, and rent control. Using the results from how our current housing policies do and do not improve the economic lives of households, we will then develop new policy recommendations to optimally provide housing benefits, minimizing distortions and directly targeting market failures in housing markets. This project will use large-scale government administrative data tracking the details of a large variety of housing policies, linked to private sector data tracking migration and key economic outcomes of households. Most programming will be in SQL and Stata. The ideal candidate has keen attention to detail, prior experience working with large, computational difficult datasets, and some prior research experience.

Evidence on the Efficiency and Incidence of Government Old-age Support

Professor Daniel Fetter
Daniel Fetter, Assistant Professor of Economics at Stanford, is accepting applications for a pre-doctoral research fellow as part of his research team. The position will entail close collaboration and assistance with all stages of various empirical research projects in the field of economic history, with a focus on the effects of government old-age support. The fellow will work with a variety of datasets ranging from the historical complete-count US individual census data to historical survey and administrative datasets. This position is ideal for candidates looking to develop their empirical research skills in preparation for applying to PhD programs in economics or related fields, but may also be a good fit for students planning to apply to other types of graduate programs such as law school. Preference will be given to detail-oriented applicants with previous programming experience, particularly in working with large datasets in software such as Stata.

Current Issues in Household Finance

Professors Gopi Shah Goda and Colleen Honigsberg

Professors Goda and Honigsberg seek a highly skilled individual to work as a predoctoral research fellow. The position will involve research assistance for several projects related to household finance. Professor Goda’s work focuses on consumption and distribution decisions nearing retirement, the effects of long-term care insurance on family decisions, retirement incentives for public sector workers and other topics related to the economics of aging in the United States. Professor Honigsberg’s work focuses on the consumer welfare implications of non-bank financing and US regulation of financial advisors. All projects use large-scale survey and administrative data sources. The fellow will receive exposure to and training in a broad set of applied microeconomics research methods. The fellow will become knowledgeable about the current regulatory regime for non-bank lenders and the well-being of the elderly in the US. The candidate must have experience coding in Stata. The ideal candidate will also have experience in GitHub, LaTeX, and Python (and/or be willing to learn).

Using Administrative Data to Understand Who Our Politicians Are

Professor Andrew Hall

Professor Hall seeks a highly driven, computationally skilled research fellow. This position will focus on using large-scale administrative and election data, both historical and contemporary, to study the backgrounds of American politicians and to understand how different institutional policies encourage different kinds of people to become politicians. The ideal candidate has experience writing code (ideally in Stata, Python and/or R), working with data hosted on remote servers, and building databases, but it is more important that the candidate is willing to learn than that the candidate already knows these things. The research fellow will gain practical research experience in political economy, will learn about fundamental questions in the study of political economy, will get to study practical policy questions that could improve the functioning of democracy, and will have the opportunity to participate in the Democracy and Polarization lab that Prof. Hall co-directs with Professor Grimmer. The position is particularly well suited for a student with an economics or related social science background who is considering an economics/political economy/political science Ph.D.

Occupational Licensing, Price Discrimination, and Kidney Markets

Professors Brad Larsen and Paulo Somaini

Professors Larsen and Somaini seek a highly skilled individual to work as a predoctoral research fellow for a one-year (or possibly two-year) term to begin summer of 2020 (the precise start date is flexible). The position will involve analyzing large datasets to study occupational licensing and price discrimination for Professor Larsen, and the market for dialysis treatments for Professor Somaini. The fellow will receive exposure to and training in a broad set of empirical methods, learn to write about and organize research findings, and become knowledgeable about current policies. The desired qualifications are formal training in statistics and econometrics and proficiency with programming languages and statistical software such as Stata, R, Matlab, and Python.

Urbanization, Public Transport, and Welfare

Professor Melanie Morten

Professor Melanie Morten seeks a predoctoral research assistant to help with research projects on migration and urbanization. The primary project will be a study analyzing the impact of public transportation in Dar es Salaam, Tanzania. The predoctoral research fellow will be expected to help with data analysis, solving spatial models, and potentially assisting in piloting and running field experiments. Programming skills, a willingness to learn, attention to detail, and enthusiasm about economics are all required.

Public Policies in Health Insurance and Health Care

Professor Maria Polyakova

Professor Polyakova is seeking a highly skilled individual to work as a predoctoral research fellow beginning summer of 2020. The fellow will work on multiple projects in health economics that use large administrative datasets, including Medicare, Medicaid, US tax data, and German labor market data, to examine questions around US health insurance policy, consumer behavior in health insurance and healthcare markets, as well as the labor market for healthcare providers. The first project that the fellow will assist on uses US administrative tax data to study the financial returns to high human capital investments on the example of medical doctors - the most common occupation among the top 1% of income earners in the United States. The pre-doctoral fellow will be expected to to write programming scripts to analyze the data and actively participate in regular research 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. The position requires attention to detail and fluency with Stata. Knowledge of SAS, R, and Python is a plus but not required.

The Roots of Health Inequality and The Value of Intra-Family Expertise

Professors Maria Polyakova and Petra Persson

Professors Polyakova and Persson are accepting application for a predoctoral research fellow. The position will involve research assistance for several projects on topics related to the causes and consequences of health inequality, including the family roots of inequality, role of health-related expertise in the family, and adoption of medical technologies. The projects use large-scale administrative data sets from the United States and Scandinavian countries, and deliver implications for current policy debates. The fellow will receive exposure to and training in a broad set of applied microeconomics research methods, and experience analyzing large and complex data sets, working with programs such as Stata, R, Python and GIS, and will become knowledgeable about policies targeting current and future health inequality in the US and in other countries. The position requires fluency with Stata. Knowledge of SAS, R, and Python is a plus but not required.

Families, Health, and Big Data

Professors Maya Rossin-Slater and Petra Persson

Professors Maya Rossin-Slater and Petra Persson seek a highly skilled individual to work as a predoctoral research fellow. 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 from the United States, Denmark, and Sweden, and deliver implications for current policy debates. A successful applicant should be detail-oriented and have experience in working with large data sets using Stata software. The fellow will receive exposure to and training in a broad set of applied microeconomics research methods, and experience analyzing large and complex data sets, working with programs such as Stata, SAS, and GIS, and will become knowledgeable about current policies targeting disadvantaged populations in the US and in other countries.

Consumer Finance, Fintech, and Regulation

Professor Amit Seru

Professor Seru researches several topics in household finance and financial regulation, including the rising role of fin-tech and big-tech firms, financial advertising, intermediation, and the sources and measurement of technological innovation. These projects will use large-scale data sets primarily from the United States, and the analysis will deliver implications for current policy debates. The fellow will help the team clean, process, and analyze the data towards these goals using programs such as Stata, Python, R, or SAS. The ideal candidate brings both enthusiasm for research and coding experience, with some preference given to those with prior knowledge of either Stata, R, or Python. This position will be administered by the Stanford Graduate School of Business. The appointment is for one year with possibility of renewal, and will begin in Summer 2020.

Frequently Asked Questions:

  • When should we expect to hear about our admissions decision?
    We will make every effort to notify all candidates by April 30.
  • What is the start date?
    Start dates are somewhat negotiable but must be no earlier than June 1 and no later than September 15. Orientation is tentatively scheduled for the week of July 20, 2020, and we encourage predocs to arrive in time for this.
  • Do you accept international applicants?
    Yes, we accept international applicants. International applicants will be sponsored on a J-1 visa. Students eligible for OPT are encouraged to use that during the fellowship.
  • Do we need to provide test scores for the program (GRE/GMAT/TOEFL)?
    No, we do not require test scores.
  • I am not an Economics major. Can I still apply?
    Yes, we consider non-economics majors for these positions. However, applicants should have strong statistics backgrounds and an expressed interest in economics.
  • Do you accept application material by email?
    No, we are unable to review applications received by email. All application material should be submitted via the application portal. If you have difficulty accessing Google, please contact us.
  • How do you match applicants to faculty?
    Faculty interested in mentoring a predoc will list their projects above. Applicants rank the projects they are most interested in. Faculty will select a specific candidate to mentor for 1-2 years. 
  • My advisor would like to submit a recommendation letter. How do I do that?
    We do not accept unsolicited recommendation letters on behalf of candidates. They will not be read. If candidates are selected for interviews, we will request references and contact those references directly. 
  • You provide the option of including a writing sample. What should I include?
    The Writing Sample is optional but encouraged. It should be roughly five pages in length and should demonstrate your academic writing skills. The paper must be in English. An excerpt of an undergraduate thesis or term paper, or an excerpt of a masters dissertation (including abstract) are acceptable examples.
  • What can I do to make my application more competitive for the Predoc Fellowship?
    Our faculty look for strong academic records (GPA, high grades in quantitative courses), experience with Stata, R, or Python, and clear writing skills. Double check your application material for completeness and make sure there are no typos or mistakes in your cover letter, resume, or writing sample, as our faculty also value attention to detail. 
  • Is it an advantage to have a masters degree when applying for the fellowship?
    It is not required to have a masters degree for admission to the predoctoral research fellows program. Approximately 1/3 of our fellows complete a masters degree prior to entry into the program. A strong masters transcript may be helpful if you believe your undergraduate coursework does not adequately reflect your abilities in quantitative courses, but is not guaranteed to give you an edge above other applicants.
  • How many students apply to your program?
    We are not releasing our application numbers at this time.

For further questions, please email siepr-fellowships@stanford.edu.