It was a wonderful summer working with Prof. Sarah Pearlman as her Ford Scholar. Her research explores migration and its influence on voting behavior in the United States. Thus, our project’s focus was to create a comprehensive dataset of U.S. population demographics and state legislatures; using this dataset, we made it our objective to draw correlations between the fluctuations in migration and electoral outcomes across states. 

Collating the master dataset was no simple task, however: it necessitated weeks’ worth of searching for data, coding, and literature review to get to the right sources. The first couple of weeks I spent reading publications from peer-reviewed journals in Economics, think tanks, and legal reports. These sources commented on the most recent trends in immigration and the role of naturalized citizens on electoral outcomes. Moving forward, I began with preliminary cleaning of Census Bureau data (derived mostly from the American Community Survey) to visualize demographic trends of naturalized citizens across the past twenty years. Furthermore, I was able to pull more data and model the voter registration and turnout rates for naturalized citizens and link my findings to federal and state electoral outcomes. Once I gained more exposure to handling large data, I proceeded to work with a dataset containing information on state legislative election returns and their party composition. 

In the end, I successfully created a master dataset and ran several regressions. While some of our findings were inconclusive due to inconsistent availability of most recent data, working on this project was greatly rewarding for me. I am incredibly glad that I got the opportunity to improve several crucial skills such as coding, handling large datasets, and combining literature review with quantitative research. It was truly a transformative experience.