FW: Research Assistantships in Public Policy

The Penn Wharton Public Policy Initiative (PPI) sponsors public policy related research positions across the University. In order to strengthen opportunities for students to be involved in U.S. public policy research, Penn Wharton PPI connects students seeking part-time work as research assistants with Penn Wharton PPI faculty affiliates. Currently, there are three positions available. As other research assistant positions become available, they will be posted on the Penn Wharton Public Policy Initiative Job Board. We invite you to visit the Job Board in the future and hope you find it a valuable resource for securing policy related research work.

Research Assistant for Professor Laura Perna
Graduate School of Education
Assist Professor Perna with a project designed to identify the ideal characteristics of a “college promise” program. Proposed by President Obama in 2015, several states (e.g., TN) and local communities (e.g., Kalamazoo) have implemented some version of a “college promise program” or a program that “promises” free or reduced tuition for students who enroll in specified colleges and universities.


Senior Research Assistant for Professor Lynn Wu 
Operations, Information, and Decisions
The research assistant will be assisting with data analysis on two related projects. We plan to track how big data capabilities affect firm performance and earnings. We will be examining corporate earnings and use machine learning techniques such as deep learning on letters to stockholders, resumes of the C-level execs, as well as call transcripts to analysis. We aim to extract these variables that can help predict long term firm performance.


Research Assistant for Professor Pinar Yildirim
Marketing
Professor Pinar Yildirim seeks an RA to assist with data analysis for a project looking at how access to information from news sources affects the decision to participate in political protests and other forms of collective action. Candidates should have a background in math, statistics, and/or economics, and have proficiency in the use of R and Stata.

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