Business Models and Incentives in Rating Markets: Three Essays
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Business Models and Incentives in Rating Markets: Three Essays by Paul Robert Seaborn A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate Department of Management University of Toronto © Copyright by Paul Robert Seaborn 2011 Library and Archives Bibliothèque et Canada Archives Canada Published Heritage Direction du Branch Patrimoine de l'édition 395 Wellington Street 395, rue Wellington Ottawa ON K1A 0N4 Ottawa ON K1A 0N4 Canada Canada Your file Votre référence ISBN: 978-0-494-78016-9 Our file Notre référence ISBN: 978-0-494-78016-9 NOTICE: AVIS: The author has granted a non- L'auteur a accordé une licence non exclusive exclusive license allowing Library and permettant à la Bibliothèque et Archives Archives Canada to reproduce, Canada de reproduire, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par télécommunication ou par l'Internet, prêter, telecommunication or on the Internet, distribuer et vendre des thèses partout dans le loan, distrbute and sell theses monde, à des fins commerciales ou autres, sur worldwide, for commercial or non- support microforme, papier, électronique et/ou commercial purposes, in microform, autres formats. paper, electronic and/or any other formats. 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Business Models and Incentives in Rating Markets: Three Essays Paul Robert Seaborn Doctor of Philosophy Graduate Department of Management University of Toronto 2011 Abstract This dissertation consists of three essays linking the business models of rating agencies to the rating decisions these agencies make as market intermediaries between buyers and sellers. The first study examines the link between a rating agency‟s primary revenue source and its rating decisions. Theoretically, rating payments could influence rating agency decisions or be counterbalanced by reputational rewards for rating accuracy. I explore this relationship in U.S. corporate credit ratings, where some agencies are primarily paid by bond issuers (sellers) and others by investors (buyers). Analysis of a balanced panel of 338 companies rated between 2005 and 2009 reveals that agencies produce differing ratings consistent with the preferences of their paying customers. Changes in buyer-paid ratings are more frequent and generally precede corresponding seller-paid rating changes. Seller-paid ratings are slower to incorporate negative information, particularly for rated firms in the financial services sector and firms with ratings above a critical grading cutoff. The second study complements the first by estimating the gap between the rating information disclosed by sellers and the information sought by buyers, again using evidence from U.S. corporate credit ratings. While seller willingness to pay for an additional rating is highly ii concentrated among a subset of relatively high-quality firms, buyers demonstrate more uniform interest in additional ratings for firms at all quality levels. This finding highlights an information gap among high-risk firms that is not a major focus of existing regulation. The third study focuses on rating decisions by government rating agencies, an alternative rating model to those examined in the first two studies. The empirical setting is Canadian film classification where the existence of multiple regional regulators has been justified by claims of variation in community standards. I find significant and increasing consistency in the regulatory decisions of these agencies, suggesting institutional isomorphism that brings into question the persistence of the parallel regional structure. Overall, these studies provide new empirical insight into the relevance of rating agency heterogeneity to firm strategy and policy. The findings may also be relevant to a variety of other settings involving information disclosure such as environmental impact and corporate social responsibility. iii Dedication I dedicate this thesis to my wife Heidi, who has supported and encouraged me from the first moment I considered a career in academia and whose love continues to inspire me daily. I also dedicate this thesis to my parents, Tex and Glynda Seaborn, who fostered in me a love of learning and new experiences and the confidence to pursue my dreams. I am grateful to all of my family, friends and colleagues for their support and encouragement. iv Acknowledgments I am truly fortunate to have chosen the University of Toronto and the Rotman School of Management for my PhD studies five years ago. Little did I know that I was joining such a rich learning environment and amazing community of scholars. My thesis committee members – Brian Silverman, Tim Simcoe, Mara Lederman and Anne Fleischer – have provided me with wonderful support and guidance, particularly at the most difficult junctures of the process. As researchers, teachers and mentors they have given me four powerful examples of how to make the most of my academic career. One of the most rewarding aspects of my time at Rotman has been getting to know my fellow PhD students whom I admire and respect tremendously. Christian Catalini, Alastair Lawrence, Jay Horwitz, Elena Kulchina, Alex Oettl, Alison Kemper and Nan Jia have been particularly good friends and colleagues. Many others at Rotman, including George Fleischmann, Joanne Oxley, Anita McGahan, Bill McEvily, Ken Corts, Olav Sorenson, Sarah Kaplan, Matt Grennan and Rick Powers have also been very helpful to my progress. Financial support from the SSHRC Canada Graduate Scholarship and the AIC Institute for Corporate Citizenship is gratefully acknowledged. Data access from Egan-Jones, Gus DeFranco, Florin Vasvari, Olav Sorenson, Sean Forbes, Kevin Mak and the Rotman BIC is also acknowledged. v Table of Contents Dedication ...................................................................................................................................... iv Acknowledgments ........................................................................................................................... v Table of Contents ........................................................................................................................... vi List of Tables ................................................................................................................................. ix List of Figures ................................................................................................................................ xi Chapter 1 ......................................................................................................................................... 1 1 Introduction ................................................................................................................................ 1 Chapter 2 ......................................................................................................................................... 3 2 Business Models and Incentives in Rating Markets: How „Who Pays‟ Matters ....................... 3 2.1 Introduction ......................................................................................................................... 3 2.2 Literature and Theory ......................................................................................................... 6 2.3 Empirical Setting: U.S. Corporate Credit Ratings ............................................................ 12 2.4 Data and Sample ............................................................................................................... 14 2.5 Empirical Approach .......................................................................................................... 16 2.5.1 Fixed Effects Panel Data Regression .................................................................... 16 2.5.2 Granger Causality Tests ........................................................................................ 18 2.6 Results ............................................................................................................................... 19 2.6.1 Descriptive Statistics ............................................................................................. 19 2.6.2 Fixed Effects Panel Data Regression .................................................................... 21 2.6.3 Granger Causality Tests ........................................................................................ 24 2.7 Discussion and Conclusion ............................................................................................... 26 Chapter 3 ......................................................................................................................................