Thesis advisor: Thomas Chemmanur / My Ph.D. dissertation consists of three essays. The first essay studies the economic consequence of the current patent screening process on firm performance using a machine-learning approach. Using USPTO patent application data, I apply a machine-learning algorithm to analyze how the current patent examination process in the U.S. can be improved in terms of granting higher quality patents. I make use of the quasi-random assignment of patent applications to examiners to show that screening decisions aided by a machine learning algorithm lead to a 15.5% gain in patent generality. To analyze the economic consequences of current patent screening on both public and private firms, I construct an ex-ante measure of past false acceptance rate for each examiner by exploiting the disagreement in patent screening decisions between the algorithm and current patent examiner. I first show that patents granted by examiners with higher false acceptance rates have lower announcement returns around patent grant news. Moreover, these patents are more likely to expire early. Next, I find that public firms whose patents are granted by such examiners are more likely to get sued in patent litigation cases. Consequently, these firms cut R&D investments and have worse operating performance. Lastly, I find that private firms whose patents are granted by such examiners are less likely to exit successfully by an IPO or an M&A. Overall, this study suggests that the social and economic cost of an inefficient patent screening system is large and can be mitigated with the help of a machine learning algorithm. The second essay studies how investor attention affects various aspects of SEOs. Models of seasoned equity offerings (SEOs) such as Myers and Majluf (1984) assume that all investors in the economy pay immediate attention to SEO announcements and the pricing of SEOs. In this paper, we analyze, theoretically and empirically, the implications of only a fraction of investors in the equity market paying immediate attention to SEO announcements. We first show theoretically that, in the above setting, the announcement effect of an SEO will be positively related to the fraction of investors paying attention to the announcement and that there will be a post-announcement stock-return drift that is negatively related to investor attention. In the second part of the paper, we test the above predictions using the media coverage of firms announcing SEOs as our main proxy for investor attention, and find evidence consistent with the above predictions. In the third part of the paper, we develop and test various hypotheses relating investor attention paid to an issuing firm to various SEO characteristics. We empirically show that institutional investor participation in SEOs, the post-SEO equity market valuation of firms, SEO underpricing, and SEO valuation are all positively related to investor attention. Lastly, we also use the number of SEC EDGAR file downloads as an alternative proxy for investor attention, and our findings are robust to this alternative investor attention measure. The results of our identification tests show that the above results are causal. The third essay studies how the location of a lead underwriter in its network of investment banks affects various aspects of seasoned equity offerings (SEOs). We hypothesize that investment banking networks perform an important economic role in the SEO underwriting process for SEOs, namely, that of information dissemination, where the lead underwriter uses its investment banking network to disseminate information about the SEO firm to institutional investors. Consistent with the above information dissemination role, we show that firms whose SEOs are underwritten by more central lead underwriters are associated with a smaller extent of information asymmetry in the equity market. We then develop testable hypotheses based on the information dissemination role of underwriter networks for the relationship between SEO underwriter centrality and various SEO characteristics, which we test in our empirical analysis. Consistent with the above hypotheses, we find that more central lead SEO underwriters are associated with less negative SEO announcement effects; smaller SEO offer price revisions; smaller SEO discounts and underpricing; higher immediate post-SEO equity valuations for issuing firms; and greater post-SEO long-run stock returns for issuing firms. We also find that SEOs with more central lead underwriters are associated with greater institutional investor participation. Our instrumental variable (IV) analysis using the industry-average bargaining power of underwriters relative to issuers as the instrument shows that the above results are causal. Consistent with greater value creation by more central lead underwriters, we find that more central lead underwriters receive greater compensation. / Thesis (PhD) — Boston College, 2021. / Submitted to: Boston College. Carroll School of Management. / Discipline: Finance.