2024 / This thesis empirically evaluates the impact of voluntary minimum wage changes to firm reputation using data from the hiring website Indeed.com. As a starting point, I show that when Target and Amazon unilaterally raised their minimum wages, their ratings on Indeed.com improved substantially across multiple dimensions: work-life balance, compensation, job security, management, and culture. Next, I examine the impact of a focal firm voluntarily raising its minimum wage on the ratings of similar firms in proximal locations. Using a differences-in-differences (DiD) design, I present preliminary evidence that competitors that are located near the focal firm may expe- rience a negative reputational shock relative to similar firms that are geographically distant. Additionally, this thesis applies novel sentiment analysis techniques to eval- uate minimum wage policies on review text. Using state-of-the-art NLP models such as Claude, ChatGPT, and RoBERTa, I identify and score two topics that are im- portant to job reviewers, but do not receive star ratings on Indeed.com: ”Scheduling and Hours,” and ”Workload and Compensation.” Finally, I use LLMs to perform zero-shot fine-grained sentiment analysis to investigate how a company’s reputation in regards to these topics is impacted by voluntary minimum wage policies. In these analyses, I am not able to refute the null hypothesis, though the method demostrates promise for further development.