Essays on Political Economy of Finance Yifan Zhou ORCID iD: 0000-0003-2882-9497 A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Finance Faculty of Business and Economics University of Melbourne Australia January 2021 To mum and dad, for their unconditional love, support, and encouragement. Abstract This thesis explores mechanisms that connect firms to politicians, as well as new channels through which firms benefit from being politically connected, under different ecopolitical environments. It contains three essays examining various aspects of finance at its intersection with political science. The first essay exploits Donald Trump’s nonpolitical background and surprise election victory to identify the value of sudden presidential ties among S&P 500 firms. In our setting firms did not choose to become politically connected, so we identify treatment effects comparatively free of selection bias prevalent in this literature. Firms with presidential ties enjoyed greater abnormal returns around the 2016 election. Since Trump’s inauguration, connected firms had better performance, received more government contracts, and were less subject to unfavorable regulatory actions. We rule out a number of confounding factors, including industry designation, sensitivity to Republican platforms, campaign finance, and lobbying expenditures. The second essay finds that borrowers from the same state as the Chairman of the US Senate Banking Committee, whom I term "connected", are able to borrow at spreads 14 basis points lower than other borrowers. Connected borrowers’ contributions toward the Chairman are influenced by their cost of loans, but the same is not true for nonconnected borrowers. Findings suggest the Chairman is incentivized by reelection to actively help connected borrowers obtain cheaper loans. Banks that offer a larger fraction of connected loans enjoy higher future excess stock returns. Results are consistent with the existence of a quid pro quo relationship triangle between firms, banks, and politicians. The third essay examines how changes in local political leadership affect firms’ gover- nance structures. Using a novel dataset, I document that following the appointment of a new city-level Chinese Communist Party (CCP) secretary, local firms increase (decrease) the fraction of directors who share a common birthplace with the incoming (departing) secretary. This appears to be a channel through which Chinese firms establish political connections. Firms with a higher percentage of birthplace-connected directors exhibit higher abnormal returns around secretary appointments. These firms enjoy superior accounting performances and attract institutional fund flows. I reject an alternative hypothesis that these directors are appointed to company boards on the "orders" of the politician, rather than actively recruited by firms. i Declaration I declare that i this thesis is comprised of only my original work towards the PhD, except where indicated in the Preface; ii due acknowledgment has been made in the text to all other material used; and iii this thesis is less than 100,000 words in length, exclusive of tables, maps, bibliographies and appendices. Yifan Zhou January 2021 ii Preface Chapter 2 is based on an accepted version of Child, T. B., Massoud, N., Schabus, M., Zhou, Y., 2020. Surprise Election for Trump Connections. Journal of Financial Economics, forthcoming. Chapters 3 and 4 comprise exclusively of my own original unpublished work. All co-authorships are in accordance with the Graduate Research Training Policy of the University of Melbourne. I acknowledge fundings from the Australian Government Research Training Program and the Faculty of Business and Economics Graduate Research Abroad Travelling Scholarship. iii Acknowledgment I am indebted in perpetuity to my supervisory committee members Antonio Gargano, Nadia Massoud (principal), Lyndon Moore, and Ekaterina Volkova for shaping not only my research, but also myself as a researcher. I am also forever grateful for Shang-Jin Wei’s support and guidance as a mentor, friend, and fellow economist. Their critiques and encouragements pushed me onto a journey of research. The completion of this thesis would not have been possible without them. I would also like to express my sincere gratitude toward all faculty members in the Department of Finance at the University of Melbourne; their insights helped build much of this thesis. A special thanks to Bruce Grundy, J. Spencer Martin, and Garry Twite for their contributions toward the PhD program. Thank you to my fellow PhD students Ryan Anderson, Nazanin Babolmorad, Heath Blake, Muhan Hu, Sheng Huang, Haoyi (Leslie) Luo, Linxiang Ma, Fei Shang, Jiamu Sun, Mengchuan (Kitty) Wang, Bochen Wu, Lin (Angie) Wu, Zijin (Vivian) Xu, and Bo Zhang. Discussions with them were always interesting and beneficial. Their companionship along the journey kept me going. I would also like to thank FIRN for organising PhD courses. Thank you to Michael Gallmeyer and Jay Hartzell for sharing their knowledge. The professional staff in the Department of Finance were all very kind and supportive over the last five year. Thank you to Angela Ballard, Silvia Barberoglou, Suzie Collins, Steven Mitchell, and Rachel Soderstrom. I thank the Department of Finance, Faculty of Business and Economics, University of Melbourne for generous financial support and provision of resources over the last five year. Finally, I would like to thank my partner Fengqin Hu, without whom I could not have endured the difficult job market of 2020/21, and my dear friend Huixin Wang, for always being there in my hours of need. iv Contents 1 Introduction 1 2 Surprise Election for Trump Connections 4 2.1 Introduction . .4 2.2 Data . 10 2.2.1 Trump’s business network . 11 2.2.2 Trump news . 13 2.2.3 Government contracts . 14 2.2.4 Regulatory actions . 14 2.2.5 White house access . 15 2.2.6 Potential political economic confounders . 15 2.3 Value of political connections . 17 2.4 Real outcomes . 21 2.4.1 Firm performance . 22 2.4.2 Government contracts . 24 2.4.3 Regulatory actions . 24 2.5 Extensions . 26 2.5.1 Presidential ties and White House visits . 26 2.5.2 Major political and legal developments . 29 v Contents 2.6 Robustness . 32 2.6.1 Choice of industry classification . 32 2.6.2 Placebo elections . 34 2.7 Conclusion . 36 2.8 Appendix A . 38 2.9 Appendix B . 43 3 Politically Influenced Bank Lending 47 3.1 Introduction . 47 3.2 Background and Data . 54 3.2.1 Loan Pricing and Borrower Financial Data . 54 3.2.2 Chairmen and Political Contribution Data . 57 3.3 Empirical Results . 61 3.3.1 Banks & Firms – Connected vs. Nonconnected Loans . 61 3.3.2 Firms & Politicians – Political Contributions . 66 3.3.3 Banks & Politicians – Stock Returns . 70 3.4 Falsification and Robustness Tests . 71 3.4.1 Closely- vs. Non-closely-contested Reelections . 72 3.4.2 Past Contributions vs. Political Connection . 74 3.4.3 Active Chairman vs. Active Bank . 74 3.4.4 Powerful Senators vs. Chairman of the Senate Banking Committee . 77 3.4.5 Information Efficiency vs. Exchange of Favors . 79 3.4.6 HQ Location vs. Board Connectedness . 79 3.4.7 House Financial Services Committee . 81 3.4.8 Matched Sample . 83 vi Contents 3.4.9 Firm PAC vs. Employee Contributions . 83 3.4.10 Prime Rate-based Loans . 86 3.5 Conclusion . 88 3.6 Appendix . 90 4 Political Leadership and Governance Structure 94 4.1 Introduction . 94 4.2 Background and Setup . 100 4.2.1 Importance of Birthplace . 100 4.2.2 Data . 100 4.3 Empirical Analyses . 102 4.3.1 Connections through Common Birthplaces . 102 4.3.2 Market Reaction . 106 4.3.3 Firm Performance . 109 4.3.4 Institutional Ownership . 112 4.4 Robustness and Falsification Tests . 114 4.4.1 Appointing vs. Seeking Directors . 114 4.4.2 Birthplace vs. Jiguan (Ancestral Home) . 115 4.5 Conclusion . 117 5 Conclusion 119 vii Chapter 1 Introduction The longer you can look back, the farther you can look forward. Wiston Churchill, March 1944 Looking over our history, we cannot fail to recognize the close interdependency between economics and politics. Many economic turmoils have lead to or were lead to by political decisions; there are countless examples of extreme collective wealth or poverty that resulted in or were results of conflicts and wars. Recent events serve well to remind us of this interdependent relation. In 2020, we witnessed and endured the worst pandemic in a century. Amidst this chaos, the world turned it attention to the most powerful and wealthy economy on earth – the United States of America – for example and leadership. They failed us. The first case of Covid-19 was reported in the US on 20 January 2020. Precisely one year later, the US has over 24 million cases and more than 400,000 deaths.1 The botched pandemic response has had severe economic consequences. Goldman Sachs predicts 1Coronavirus in the U.S.: Latest Map and Case Count. The New York Times, https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html. Accessed 20 January 2020. 1 Introduction a 3.5 percent contraction of the US economy in 2020.2 At the same time, unemployment rate is almost double its pre-pandemic level.3 In stark comparison to the US and to almost every other major economy, China’s GDP grew by 2.3 percent in 2020.4 This phenomenal achievement can be largely attributed to its swift and forceful response to the pandemic at the very beginning of the outbreak. The pandemic serves as a good illustration of how politics, whether it be political systems or politicians, is able to heavily influence economies.5 This direction of influence is the primary focus of this thesis. There is a simple overarching question – how do politics influence economics? The first essay (Surprise Election for Trump Connections) examines firms with business or personal connections to the Trump family prior to the announcement of Donald Trump’s 2016 election campaign.