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SIEPR UGRA Program-Academic Year

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The UGRA program aims to offer dynamic research opportunities for Stanford undergraduates during the academic year. The UGRA program continues to focus on enriching the student research experience, and will also offer more opportunities for students to participate in the intellectual life of SIEPR. 

Program Structure 

Each quarter students and their faculty mentor will meet prior to the start of the quarter to agree on project goals and learning outcomes for a quarter-long research experience. The student time commitment is expected to be equivalent to a 3-unit course (approximately 9 hours per week). The fall quarter program will run from September 26 to December 9, 2022.

  • Students will be paid a fellowship stipend of $1500 each academic quarter
    • One-half of the stipend will be paid at the beginning of the quarter, and the other half at the end of the quarter once the faculty mentor confirms that the student has met the project goals or at least put in a good faith effort to do so.
  • Students are not held to a weekly work hour requirement
    • Faculty mentors will assess student progress at the middle and at the end of the quarter to make sure students are meeting expectations on their project. 
  • Students will attend a one-hour weekly working group meeting hosted by SIEPR
    • The meetings will offer peer-to-peer interaction, professional development opportunities, and skills training.
  • SIEPR will host monthly seminars/presentations for undergraduate students
  • Students will submit to SIEPR periodic research summaries throughout the quarter and a final slide summarizing their project outcomes around the end of the quarter

Eligibility

UGRAs must be enrolled as a full-time undergraduate student at Stanford. Coterm students who are interested in the program will need to hold undergraduate standing to be eligible for the SIEPR UGRA program.

How to Apply

To apply for the SIEPR UGRA program, fill out the online application using the link below. Please follow the instructions in the application portal. The application will ask you to answer a few general questions about your academic interests.

Please prepare to upload the materials listed below:

  1. A list of the current courses that you are enrolled in for the upcoming quarter. 

  2. Resume

  3. A cover letter that addresses the following:

    • Why are you interested in a SIEPR UGRA position?

    • What is your previous experience, if any, with research?

    • What are your personal research interests?

Questions?

If you have questions, please email siepr-fellowships@stanford.edu.

 

Open Position

Efficiency in deceased donor allocation

Faculty Mentor: Itai Ashlagi

Available positions: 1

Number of quarters: 3

About 25% of kidneys from deceased donors are discarded in the US despite an average waiting time of 3.5 years and about 22 patients dying every day on the waiting list. Some reasons include incentives for transplant centers, slow allocation process, misaligned incentives with patients' preferences, etc.

This project will seek to help identify the causes and build tools and better allocation mechanisms to increase efficiency and help doctors and patients make better decisions.

RA Responsibilities:

It will include a subset of the following (depending on students interests): data analysis, simulations, collecting data regarding the incentives identified by the government.

Qualifications:

Experience with Python, data analysis, basic statistics. Good to have some experience with visualizations or ability to quickly learn.

Open Position

Interview Match

Faculty Mentor: Itai Ashlagi

Available positions: 1

Number of quarters: 1

In many matching markets participants don't know their preferences. This project will help to design an "interviewing" recommender system that will help reduce the congestion that such markets exhibit.

RA Responsibilities:

Programming, data analysis, simulations, and visualizations

Qualifications:

Experience with programming, especially python Basic statistics Some experience with data

Open Position

Making Government More Effective and Affordable

Faculty Mentor: Michael J Boskin

Available positions: 2

Number of quarters: 3

A series of interrelated sub-projects focused on improving the functions of government, making it more effective and affordable. The subjects included ameliorating government failures from regulatory capture to waste and fraud, from mission creep to poor targeting. Examples include reforms to defense budgeting, welfare and entitlement programs, the tax code, and environment and energy programs.

RA Responsibilities:

Obtaining, evaluating, prioritizing, and where possible quantifying information from public and private sources, databases, articles, etc.

Qualifications:

1. Interest in, and curiosity about, the subject matter. 2. Basic computer skills 3. Basic familiarity with Economics concepts, e.g. from Econ 1

Open Position

Digital Economy Lab: Determinants of the Value of Social Media Connections

Faculty Mentor: Erik Brynjolfsson

Availible positions: 2

Number of quarters: 3

This research is on the determinants of value that individuals get from social media.

RA Responsibilities:

The RA's first task will be to aid us in using the Twitter API to collect information on the social network of survey participants. The size of the data involved will be multiple terabytes, as we wish to get information on the network of about 1000 survey respondents at least two degrees out (e.g. followers of followers, followees of followees). We will then analyze the characteristics (e.g. Twitter usage and centrality) of these connections to see which alter attributes lead them to be valued by survey respondents.

Qualifications:

We are looking for an RA with a background in Computer Science or Economics to help us collect, organize, and analyze data from Twitter and other social networks. Applicants should be familiar with at least one of Python, Stata or R for API usage and network analysis, and familiarity with multiple is preferred.  Individuals with an interest in social media, technology regulation, big data, and scraping are preferred.

Open Position

Topics in Cross-Border Corporate Taxation and International Capital Flows

Faculty Mentor: Antonio Coppola

Availible positions: 2

Number of quarters: 2

Two different research streams are available, with matches based on the students' interests. A first project studies how firms reorganize their production activities in response to cross-border tax differences. The goal of the project is to use estimates from the data to quantify a model of the international corporate tax system, to better understand the tradeoffs implied by various policy proposals (such as a global minimum corporate income tax rate). A first step towards this analysis is compiling a database that documents the effective tax rates faced by US multinational firms in various foreign countries over time: the research assistant will be involved in using legal documents and other primary sources to compile this database, as well as in other aspects of the project.

The second research stream (joint with Chenzi Xu, Assistant Professor of Finance at Stanford GSB) examines the role of international capital flows on financial stability in a historical context. We are currently in the process of collecting and digitizing primary historical data on bank lending markets and sovereign debt markets, and the research assistant will be involved in curating and analyzing this material.

RA Responsibilities:

Data collection and analysis, reviews of historical and legal material, algorithms development for processing and digitizing primary sources, data visualization.

Qualifications:

Interest in finance, business taxation, and/or international macroeconomics. Some experience with Stata or other statistical software (such as R). Further programming experience (Python, Unix, parallel computing, computer vision) is preferred, particularly if the student would like to be involved in the more computing-intensive parts of the projects. Good writing and organizational skills, and comfort in reading and working with legal and historical sources.

Open Position

Data Science for Policy Analysis

Faculty Mentor: Thomas Dee

Availible positions: 2

Number of quarters: 3

This project will focus on data collection and analysis for two distinct policy-focused research initiatives. One will focus on education data available from state and local sources (e.g., enrollment counts) that provide leading information on the impact of the COVID-19 pandemic and the responses to it (e.g., see https://news.stanford.edu/2021/08/09/school-reopening-decisions-influenced-enrollment-drop/). The second project will focus on the study of innovative first-responder initiatives (e.g., see https://news.stanford.edu/2022/06/08/stanford-study-shows-benefits-reinventing-911-responses/). This research will be conducted in collaboration with staff at the John Gardner Center for Youth and Their Communities (https://gardnercenter.stanford.edu/) and the data journalists at Stanford's Big Local News (https://biglocalnews.org). For more information on these projects, see https://tom-dee.github.io.

RA Responsibilities:

The project RAs will participate in the collection, organization, and cleaning of data relevant to these two projects. The RAs will also have opportunities to participate in the analysis and interpretation of these data.

Qualifications:

The most critical qualification is a careful attention to detail in collecting, organizing, and conducting quality-control on data. Some familiarity with Stata and organizing data projects on GitHub (https://github.com/) is helpful but not necessary.

Open Position

SIEPR Research and Policy Engagement

Faculty Mentor: Gopi Shah Goda

Availible positions: 2

Number of quarters: 3

SIEPR intends to expand on its efforts to promote faculty research in the policy process in a variety of SIEPR's focal research areas through synthesizing research and identifying opportunities for research to enter policy discussions. These positions will be integral to these new efforts.

Research assistants will also be involved in academic research projects including the role of health insurance in mortality outcomes during the Covid-19 pandemic, the impact of Covid-19 illness on labor market outcomes, and the investigation of long-term care programs around the world.

These positions are ideal for those who may be interested in similar roles at organizations like the Council of Economic Advisers or research organizations with a policy focus.

RA Responsibilities:

Research assistants will be responsible for conducting literature reviews, data collection, and statistical analysis, creating presentations, and supporting SIEPR's deputy director on research and policy engagement efforts in a wide variety of policy areas including but not limited to health policy, retirement, labor markets, and the broader effects of the Covid-19 pandemic.

Qualifications:

Qualified candidates will have a passion for ensuring that academic research is a part of the policy process. Research assistants must be detail-oriented, organized, and exhibit excellent writing and communication skills. Experience with data analysis using statistical software such as Stata is a plus but not required.

Open Position

Improving Economic Opportunities and Access to Justice for Individuals with Intellectual & Developmental Disabilities

Faculty Mentor: Alison Morantz

Available positions: 2

Number of quarters: 3

The mission of the Stanford Intellectual and Developmental Disabilities Law and Policy Project (SIDDLAPP) is to generate innovative research and public-facing materials to help strengthen the civil rights and economic opportunities available to individuals with intellectual and developmental disabilities (I/DD), especially those from underserved communities. In 2021-22, SIDDLAPP partnered with other disability rights organizations in a successful effort to reform state law to improve access to justice among individuals who appeal service denials at hearings conducted by administrative law judges (ALJs). In 2022-23, SIDDLAPP be conducting several follow-up projects to build on these recent reforms. These projects include collecting data on the extent to which the ALJs who conduct hearings are following the new statutory requirements; creating a searchable database of past hearing decisions to help consumers better prepare for hearings; and analyzing whether the private entities that dispense state funds to individuals with IDD are complying with legally mandated transparency and reporting requirements.

RA Responsibilities:

The RAs will collaborate with the faculty mentor, SIDDLAPP staff, Stanford Law School's Racial and Disability Justice Pro Bono Project (RAD Justice), and/or other disability rights organizations to carry out one or more of the policy-related project(s) described above or other project(s) designed to strengthen the civil rights and economic opportunities available to individuals with I/DD.

Qualifications:

High attention to detail, the capacity to complete work in a timely fashion, and an interest in economic inequality are essential. An interest in disability rights and social service programs (such as Medicaid) is preferred but not required. Although some tasks for some projects require technical expertise in econometrics or machine learning (e.g., natural language processing), applicants who do not have these skills will still be considered.

Open Position

State and Local Fiscal Policy Research

Faculty Mentor: Joshua Rauh

Availible positions: 2

Number of quarters: 3

Cities and states across America face a wide variety of challenges, ranging from debt management to infrastructure financing to attracting and retaining businesses and productive workers. Under the direction of SIEPR and Hoover Institution Senior Fellow Joshua Rauh and other initiative staff, undergraduate RAs will have the opportunity to explore these and other critical issues.

RA Responsibilities: 

Undergraduate RAs will perform both quantitative and qualitative research relating to the policy topics described above. This will include performing literature reviews and assisting with data collection, analysis, and presentation.

Qualifications:

Undergraduates with a strong interest in economics and public policy will excel, as will those with a strong background in statistics and in using R and Stata.

Open Position

Procurement Contracts for Small Businesses: A Blessing or A Curse?

Faculty Mentors: Claudia Robles-Garcia and Greg Buchak

Availible positions: 2

Number of quarters: 3

We evaluate the implications of procurement contracts for small businesses and their effects on sales, employment, and access to credit. In bad times, procurement contracts can act as insurance for demand uncertainty and sales volatility. However, in inflationary periods, procurement contracts can reduce firm revenue if agreed prices are not adjusted accordingly (as is often the case). We study these forces for US small businesses during the last 15 years.

RA Responsibilities:

The RA will be in charge of collecting, merging, and cleaning data for procurement contracts at the federal, state, and local levels. The RA will also do analysis to ensure data quality and initial summary statistics.

Qualifications: 

Coding. Some finance or economics background (preferable).

Open Position

Analyzing text outcomes in randomized controlled trials

Faculty Mentor: Jann Spiess

Availible positions: 1

Number of quarters: 2

This project explores the value of analyzing text using machine learning in data from randomized controlled trials. It aims to catalog existing experiments that include text, evaluate the utility of analyzing text in a selected set of experiments, and discuss how much value tools from machine learning/natural language processing can add to policy analysis.

RA Responsibilities:

- Catalog randomized experiments that include text data 

- Survey existing approaches towards analyzing text in randomized experiments

- Provide basic descriptive statistics of text data in selected experiments

- Potentially contribute to implementing topic models on text data from experiments

-Potentially contributing to setting up and analyzing an online experiment with text data

Qualifications:

Required: Basic familiarity with simple descriptive statistical analysis in Stata, R, Python, Matlab, or Julia

Optional: Familiarity with tor interest to learn about text analysis tools in R, Python, or Julia

Open Position

How do non-profits compete? Efficiency and scale in charitable work

Faculty Mentor: Benjamin Vatter

Availible posistons: 2

Number of quarters: 3

In for-profit markets, economists view competition as positively affecting efficiency and prices. Competition is, in general, considered to be beneficial for welfare, and therefore regulation is often structured to enhance it. Do these ideas carry over to non-profit markets?

Non-profit organizations that rely on charitable donations to operate must compete for funds and, later on, the projects they engage in. More competition for funds might attract more donors but may also result in wasteful duplication of efforts. It can also result in fewer successful projects, as limited funds are spread too thinly. Competition on projects can result in similar inefficiencies. How then should we view competition in this sector?

In this work, we seek to answer these questions to inform policymaking for this multi-billion-dollar sector.

RA Responsibilities:

We are looking for a motivated RA to analyze a novel dataset about charity firms and the literature on non-profit markets. The tasks will include organizing and cleaning up data, reviewing mission statements of non-profits, and executing descriptive evidence analyses.

Qualifications:

Necessary skill sets:

- Data analysis in either R, Stata, or Python.

- Basic statistics and econometrics.

- Introductory level economics and above.

Desired skill sets:

- Previous experience as RA

- Interest in Industrial Organization and Applied Microeconomics

- Interest in the non-profit sectors or experience in charities

- Strong documentation and communication skills

Open Position

How Female Representation Changes Science: Evidence from College Coeducation

Faculty Mentor: Ashley Wong

Available positions: 2

Number of quarters: 1

What is the effect of increasing female representation on scientific innovation and the direction of research? Between 1960 and 1990, 76 all-male US universities, including many elite and prominent research institutions, transitioned to coeducation. How do researchers modify their research when they are exposed to more female students at their universities? Which scientific fields grew and declined as a result of women's entrance in higher education? How did these changes affect the careers of female scientists and the recognition for their work?

RA Responsibilities: 

There are two positions. One RA will focus on the topics analysis and apply NLP and topic modeling techniques to a large scientific publications database (over 1M papers) to investigate shifts in research topics and innovation. The other will focus on constructing, digitizing, and analyzing new data on the careers of female faculty and scientists.

Qualifications:

- Interest in the topic

- Experience working with data in Stata or Python

- Knowledge or willingness to learn NLP, machine learning, text analysis