Â鶹app

ABSTRACT:

The rapid advancement of artificial intelligence (AI) is creating uncertainty about who is likely to benefit from these changes and who may be harmed by them. This research project examined the relationship between wages and AI exposure across different occupations. In particular, I considered whether that relationship is different for people who majored in economics compared with non-economics majors, and whether it has changed since 2022, when consumer-facing AI tools like ChatGPT became widely available. 

My main research objective was to determine whether economics majors receive a higher or lower wage premium than non-economics majors in jobs more exposed to AI. In this context, jobs with higher AI exposure are occupations where AI tools may be especially relevant to the tasks workers perform, such as analysis, writing, forecasting, research, and decision-making. Examples include jobs such as financial analysts, market research analysts, economists, and management analysts. I gathered American Community Survey data on incomes, occupations, college majors, and other factors that influence wages, then combined it with an existing dataset that assigns each occupation an AI-exposure score. I used a log-linear wage model, which is a statistical model that estimates percentage differences in wages while accounting for other factors that also affect pay. The model allowed me to test whether the relationship between AI exposure and wages differs for economics majors and whether that relationship changed after 2022. I found that people in jobs more exposed to AI tend to have higher wages overall, and that this relationship is even stronger for economics majors. The estimated post-2022 change was positive, but not statistically significant, which may be because wages take time to adjust or because only limited post-2022 data is currently available. Overall, the results suggest that economics majors may be well-positioned in occupations more exposed to AI, though more time and data would be useful for understanding how this relationship develops. 

POSTER

This project was completed with support from Ryan Vogel, who contributed to the development of the research poster and the broader project.

Author and Mentor Bios

Jesse Harriott, from Peterborough, NH, is majoring in analytical economics at the Â鶹app. His academic interests include behavioral economics, labor economics, and innovation economics, particularly questions related to artificial intelligence and the labor market. He is a member of Omicron Delta Epsilon, the international economics honor society, and plans to pursue a PhD in economics with the goal of becoming a professor.

Aziz Saglam is a senior lecturer in the Department of Economics at the Â鶹app where he has taught since 2006. Each year, he supervises around twenty senior economics students who participate in UNH’s Undergraduate Research Conference. His research interests are game theory and mathematical economics.