<div> In the first chapter, I document that online feedback loops, such as search engines, drive customers and revenue to prominent firms, contributing to rising industry concentration. To identify prominent firms online, I measure centrality in a network of firm websites covering more than 100,000 public and private firms. Industries with firms that are more central become more concentrated and central firms increase their market share during the sample period. This appears to be due to firms' ability to meet earnings expectations. Central firms become more profitable and peripheral firms earn negative risk-adjusted returns and underperform earnings forecasts. Evidence from the COVID-19 shutdown, which drove economic activity to the Internet, supports these conclusions. Central firms received the vast majority of the influx of web traffic and had significantly higher returns during the shutdown.</div><div> </div><div> In the second chapter, I create a novel definition of peer groups (web-based peers) for over 100,000 public and private firms by extracting clusters from a network of firm websites. The network is built from unique data on overlapping web traffic. Peer firms are therefore more likely to have similar website users, and by extension, provide similar products or services. Web-based peer groups are related to traditional industry classifications, the preferred choice when defining industries for private firms, but outperform them in standard benchmarking tests. To further demonstrate the benefits of web-based peer groups, I examine IPO waves. IPO activity is closely related to peer-firm IPO activity in the past 12 months, controlling for the overall IPO market and waves within traditional industries. IPO followers earn lower post-IPO returns up to three months after going public, consistent with these firms being lower quality and attempting to benefit from the successful IPOs of their peers.</div>
Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/14896938 |
Date | 22 July 2021 |
Creators | Logan P Emery (11061996) |
Source Sets | Purdue University |
Detected Language | English |
Type | Text, Thesis |
Rights | CC BY 4.0 |
Relation | https://figshare.com/articles/thesis/Essays_on_the_Financial_Implications_of_Web_Traffic/14896938 |
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