Research Assistant for Professor Ben Lockwood
Professor Ben Lockwood is seeking a computer science or economics undergrad to provide RA assistance on a project at the intersection of machine learning and economics. The goal of the project is to build an algorithm for identifying tax code complexity, using techniques from natural language processing.
The position has opportunities for extension to a yearlong RA-ship, and to work on other related projects.
This RA role would be ideal for a sophomore, junior, or senior with an interest in pursuing graduate school and/or research at a tech company.
Required Statistical or Data Management Skills
- Strong experience programming with Python and Stata
- Experience web scraping from XML documents
- No formal course requirements, but a basic understanding of economics, and the computer science skills described above, are prerequisites
How to Apply
Example Research Previously Conducted with an RA
Professor Lockwood works in Behavioral Public Finance, meaning he asks key questions about tax systems, tax credits, and other fiscal levers and tries to determine how consumers’ and taxpayers’ decision-making impacts their efficiency. I came to Professor Lockwood because his work provided me an opportunity to combine my interests in economics and public policy with my passion for data-driven conclusions. We started off with a highly technical project where my job was to scrape Treasury forms off of the website of the Office of Management and Budget and develop a natural language processing initial analysis to determine a measure of tax form complexity. I’ve since dived deeper into some of the optimal taxation theory. For example, we developed a model in Matlab which allows calculation of consumption behavior for present-biased consumers. We can use this model to predict how consumers during the Great Recession responded to an increased Earned Income Tax Credit - do they spend it immediately or are they using it to supplement income over time? Working with Professor Lockwood has given me the opportunity to explore new methodologies, scrape together literature reviews on topics I don’t explore in class (like a weeklong deep dive into soda taxes earlier last Fall), and develop extremely extensible and modular coding practices. ~Prakash Mishra, W’19