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Essays in Macroeconomics and Financial Economics

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Essays in Macroeconomics and Financial Economics Essays in Macroeconomics and Financial Economics by Christian T. Jauregui Adissertationsubmittedinpartialsatisfactionofthe requirements for the degree of Doctor of Philosophy in Economics in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Yuriy Gorodnichenko, Chair Professor Amir Kermani Professor Martin Lettau Professor David Sraer Spring 2019 Essays in Macroeconomics and Financial Economics Copyright 2019 by Christian T. Jauregui 1 Abstract Essays in Macroeconomics and Financial Economics by Christian T. Jauregui Doctor of Philosophy in Economics University of California, Berkeley Professor Yuriy Gorodnichenko, Chair This dissertation is comprised of two chapters on separate topics at the intersection of Macroeconomics and Financial Economics. The first chapter analyzes the relationship between non-financial U.S. corporations’ debt structure and their behavior in the product market. The second chapter, which is co-authored with Ganesh Viswanath Natraj, examines the international real e↵ects of monetary policy through financial markets. In the first chapter, I answer the following crucial question: how does a non-financial firm’s product market behavior interact with its capital structure choice and cash-flow pro- cess? A significant portion of the corporate finance literature considers debt borrowing the primary source of financing through which firms smooth cash-flow shocks, with bank loans and market debt the two primary sources of debt financing. However, firms can also smooth cash-flow shocks through adjustments in their variable markup of products. This behavior is consistently unaccounted for, yet provides financial flexibility, more so for firms with a loyal customer base. I study how firms smooth cash-flows via traditional financing in the form of abankloanormarketdebtinstrument,aswellasthroughnon-traditionalinternalfinancing generated from variable markup adjustments. First, I hypothesize the empirical relationship between a firm’s markup strategy and debt financing choice, measured as the share of mar- ket debt in total debt, is conditionally non-linear. I find a robust, conditional hump-shaped relationship between the variable markup and market debt share. On average, markups rise with market debt shares, peaking at a share of 61-67% before declining. Second, I demon- strate this novel finding with a quantitative model of firm dynamics in a monopolistically competitive economy. In my model, firms set variable markups in a customer market while trading o↵restructurable bank loans for marginally cheaper, non-restructurable market debt. Market debt contracts reduce flexibility in cash flows, increasing a firm’s incentive to raise today’s profits by setting a higher markup. However, the trade-o↵between current and future profits implies the benefits of a high markup are maximized at a given market debt share. Beyond this share, markup reductions are required to attract new customers, thus generating the hump shape. My model replicates the empirical hump shape while matching several key cross-sectional and aggregate features of the data. Third, I use my model as a 2 laboratory to study the response of firms to a bank credit crunch, akin to that of the 2008-09 U.S. financial crisis. I show how my model explains 75% of the decline in total sales by public U.S. corporations following the crisis. In the second chapter, I document the international real spillovers of major central banks policies’ through their indirect e↵ect on a set of base asset prices, by using high-frequency identification of monetary policy announcements. I implement a gross domestic product (GDP)-tracking approach to identify real spillovers of monetary policy, by mimicking real GDP news based on my set of asset returns around monetary announcements. This procedure enables me to estimate news regarding real GDP growth due to monetary policy. Most importantly, this provides me with a direction of causation from monetary announcements to real variables through their indirect e↵ects on asset prices. In response to positive, domestic monetary shocks, I find real GDP-tracking news becomes negative for the U.S., Australia, and Canada. My methodology indicates significant spillovers of U.S. monetary policy to asset prices in periphery countries, such as Australia and Canada, with a U.S. monetary contraction leading to a significant e↵ect in both of these countries’ real GDP-tracking news measures, albeit the e↵ects di↵er between both countries: contractionary U.S. monetary policy is contractionary in Australia after a year, but expansionary in Canada within two quarters. Summarizing, my dissertation’s first chapter yields crucial information for better pre- dicting a non-financial firm’s default choice. Moreover, it provides insight into how a firm’s customer base – a source of market power – directly impacts capital structure decisions and vice versa. My second chapter shows the U.S. Federal Reserve is a fundamental driver of global asset prices and real output abroad, which is a topic at the core of recent policy discussions in international macroeconomics and finance. i To my family and friends, especially to my wife Jessica Fennessey. Their unwavering love, encouragement, and support enabled me to get here and finalize this significant segment in my life. ii Contents Contents ii List of Figures iv List of Tables vi 1 Variable Markup Implications of Corporate Debt Structure 1 1.1 Introduction . 1 1.2 Related Literature and Contributions . 5 1.3 Data Overview . 6 1.4 Research Design: Reduced-Form Evidence . 8 1.5 Theory: A Model of Variable Markups and Debt Structure . 13 1.6 TheModel’sPerformanceandHump-ShapedStructure . 25 1.7 AggregateShocksandCounterfactuals . 28 1.8 Concluding Remarks . 31 2 International Monetary Policy Spillovers: A High-Frequency Approach 50 2.1 Introduction . 50 2.2 Related Literature . 53 2.3 Methodology of Real GDP-Tracking Portfolios . 55 2.4 Data . 57 2.5 Empirical Evidence . 60 2.6 Conclusion . 63 A Appendix to Chapter 1 78 A.1 AdditionalFigures ................................ 79 A.2 AdditionalTables ................................ 97 A.3 DescriptionofVariables . 104 A.4 EstimationofVariableMarkups . 104 A.5 CalibrationProcedures . 106 A.6 DerivationsandProofs . 108 B Appendix to Chapter 2 109 iii B.1 Construction of Real GDP-Tracking News via Replicating Portfolios . 110 Bibliography 111 iv List of Figures 1.1 Relationship between variable markup and Leverage, SGAX ........ 33 1.2 Relationship between variable markup M and MarketDebtShare ........ 34 1.3 Relationship between and MarketDebtShareM - “Low” and “High” LeverageM ............................. 35 1.4 Relationship between and MarketDebtShare - “Low” and “High” SGAXM .............................. 36 1.5 Model-Implied Relationship between and MarketDebtShare ......... 37 1.6 Model-Implied Relationship between M and MarketDebtShare - M (zlow vs. zhigh)..................................... 38 1.7 Average and Hump Shape’s “Peak” MarketDebtShare across BankCreditShocks.................................. 39 1.8 Average and Hump Shape’s “Peak” MarketDebtShare across “Tax Reform” Shocks . 40 2.1 ComputingU.S.FederalFundsRateShocks . 65 2.2 Response of U.S. Real GDP-Tracking News to FOMC slope ........... 65 2.3 Response of Australia’s Real GDP-Tracking News to RBA slope ......... 66 2.4 Response of Canada’s Real GDP-Tracking News to BOC slope .......... 66 2.5 Response of Australia’s Real GDP-Tracking News to FOMC level ........ 67 2.6 Response of Canada’s Real GDP-Tracking News to FOMC slope ......... 67 A.1 (Robustness) Relationship between and Leverage, SGAX .......... 79 A.2 (Robustness) Relationship between M and MarketDebtShare .......... 80 A.3 Estimated Relationship between Mand MarketDebtShare - “Low” and “High” Leverage .............................M 81 A.4 (Robustness) Relationship between and MarketDebtShare - “Low” and “High” Leverage .............................M 82 A.5 Estimated Relationship between and MarketDebtShare - “Low” and “High” SGAX ..............................M 83 A.6 (Robustness) Relationship between and MarketDebtShare - “Low” and “High” SGAX ..............................M 84 v A.7 Estimated Relationship between and MarketDebtShare - “Low” and “High” SalesShare M........................... 85 A.8 Relationship between and MarketDebtShare - “Low” and “High” SalesShareM ........................... 86 A.9 (Robustness) Relationship between and MarketDebtShare - “Low” and “High” SalesShare ...........................M 87 A.10 Relationship between and MarketDebtShare - M (zlow vs. zhigh)..................................... 88 A.11 Relationship between and MarketDebtShare ................. 89 A.12 (Robustness) RelationshipM between and MarketDebtShare .......... 90 A.13 Relationship between and MarketDebtShareM - “Low” and “High” LeverageM ............................. 91 A.14 (Robustness) Relationship between and MarketDebtShare - “Low” and “High” Leverage .............................M 92 A.15 Relationship between and MarketDebtShare - “Low” and “High” SGAXM .............................. 93 A.16 (Robustness) Relationship between and MarketDebtShare - “Low” and “High” SGAX ..............................M 94 A.17 Relationship between and MarketDebtShare - “Low” and “High” SalesShareM ........................... 95 A.18 (Robustness) Relationship between and MarketDebtShare - “Low” and “High” SalesShare ...........................M 96 A.19U.S.FlowsinExternalEquityandDebtFinancing . 97 vi List of Tables 1.1 ContributedData-DescriptionofVariables
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