Call for Research Assistants – Policy Research Laboratory Fall 2023

The Salem Center for Policy at McCombs is looking for outstanding, curious, and driven students to participate in the Policy Research Laboratory (PRL) in Fall 2023. Students will take a semester long course in statistics, econometrics, and data science to learn the tools necessary for policy and social science research. In parallel, the students will apply these tools to real-world data and answer crucial policy questions. Policy research is important, and appropriately using data, cutting-edge statistical tools and remaining skeptical are equally important. Students can expect to leave this class with a deep understanding of policy questions and a toolbox for evaluating them. After the semester, the research assistantship begins. Students will be matched with policy projects within the center and/or with faculty. They will have the opportunity to immediately use their skills learned in PRL to work on exciting research that culminates in journal submission and publication. The research projects will be high impact and could elucidate cause-and-effect and tradeoffs of policies being discussed in the global arena.

Course information: FIN 373, Tues/Thurs, 9:30a-11a.

Important note: During the course, students will be paid RAs for the Salem Center at 20 hours
per week. Therefore, students must end other paid university positions prior to starting class.

Example Projects
Please visit our main webpage to see complete information about our program and research.

COVID-19: Current research assistants’ have been studying the policy responses to COVID-19. The mission of this project is to gather information about large areas of economic activity and public health in Texas in order to make policy recommendations about reopening the economy with the trade-offs of public health (i.e., currently COVID-19) in mind. We started with Austin and then expanded to the rest of the top 20 MSAs, overall state indicators, and national indicators. To see the current state of our research, see the Salem Center’s COVID-19 Site.

Machine Learning and Causal Inference: Several faculty at UT Austin have developed new tools for measuring causal effects of interventions (e.g., a policy) on complex systems (e.g., the economy). The research assistant will work with faculty on applying these tools to never-before analyzed observational and experimental data. The goal will be to write about and publish the

How to Apply
If you would like to apply for this job/research opportunity, please visit the following link and fill
out the application. The following information will be required.
• Cover letter explaining why you want to join the program
• Resume
• If you have previous research, you may include one sample or link to your website/data blog
• Deadline: April 14, 2023

Please email with any questions.