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Essays on Monetary Policy and Bitcoin Financial Economics Kyle Lance Rechard Clemson University, [email protected]

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Essays on Monetary Policy and Bitcoin Financial Economics Kyle Lance Rechard Clemson University, Krechar@Clemson.Edu View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Clemson University: TigerPrints Clemson University TigerPrints All Dissertations Dissertations May 2019 Essays on Monetary Policy and Bitcoin Financial Economics Kyle Lance Rechard Clemson University, [email protected] Follow this and additional works at: https://tigerprints.clemson.edu/all_dissertations Recommended Citation Rechard, Kyle Lance, "Essays on Monetary Policy and Bitcoin Financial Economics" (2019). All Dissertations. 2367. https://tigerprints.clemson.edu/all_dissertations/2367 This Dissertation is brought to you for free and open access by the Dissertations at TigerPrints. It has been accepted for inclusion in All Dissertations by an authorized administrator of TigerPrints. For more information, please contact [email protected]. ESSAYS ON MONETARY POLICY AND BITCOIN FINANCIAL ECONOMICS A Dissertation Presented to the Graduate School of Clemson University In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy Economics by Kyle Rechard May 2019 Accepted by: Dr. Gerald P. Dwyer, Jr., Committee Chair Dr. Robert Tamura Dr. Michal Jerzmanowki Dr. Scott Baier Abstract This dissertation includes three chapters. The first chapter investigates the impact of the Federal Reserve’s balance sheet normalization using a Bayesian vector autoregression (BVAR) framework. I use counterfactual conditional forecasts to find that a reduction in asset holdings down to a level where the federal funds market is active again will reducereal GDP growth by an average of 0.18 percent per year and core inflation by a non-significant average of 0.07 percent per year under Quantitative Tightening, relative to a scenario where the Federal Reserve maintains a constant dollar amount of assets until 2024. The second chapter models monetary policy using Taylor’s rule for the nominal interest- rate target and examines the difference between the actual Federal Funds Rate and the Tay- lor Rule model of behavior for distinct structural changes. Both a simple factor ANOVA and regime switching methods find that there were “tight” or “loose” regimes in U.S. mon- etary policy over the period 1965 to 2008. However, after accounting for the change in inflation measurement from CPI to PCE and then core PCE after 2004, Alan Greenspan’s tenure from 2003 to 2006 is consistent with his earlier symmetric deviations from the Tay- lor Rule. The final chapter examines the volatility of Bitcoin exchange rates which have gained a great deal of attention since the creation of the currency. Standard measures of volatility reflect the dramatic change in the Bitcoin/US dollar exchange rate, from about $0.05 USD in 2010 to the neighborhood of $20,000 USD at the end of 2017, and down to around ii $5,000 USD in mid-2019. Characterizing the short-term and long-term volatility gives an impression of the volatility of Bitcoin compared to other assets, as well as implying the viability of Bitcoin as a medium of exchange and alternative asset. iii Acknowledgements This dissertation has been greatly improved by the contributions of many people. First and foremost, I would like to thank my advisor, Dr. Gerald Dwyer, for his constant guid- ance throughout the entire process. Without his time and dedication, much of this disser- tation would not have been possible. I would also like to thank the other members of my committee, Dr. Robert Tamura, Dr. Michal Jerzmanowski, and Dr. Scott Baier, for their helpful comments and suggestions, as well as the participants in the Macro workshop at Clemson. The tips and comments I received while presenting in the workshop were instru- mental in shaping my research. I would like to thank Dr. John Deveraux, and Dr. Juan Rubio-Ramirez who were willing to read my work, and provide detailed feedback. I am also extremely grateful to Dr. Sam Standert for his feedback. Next, I would like to thank my family for their love and support. My parents, Rob and Pat Rechard, have been been a constant source of love and encouragment. I would not have accomplished this if it were not for them. Finally, I would like to thank the graduate students at Clemson. My classmatesOur helped shape my love for economics, and the friendships and fun experiences we’ve had are memories I’ll always carry with me. In particular, I am thankful for my officemate, Jacob Walloga, and roomate Ben Harbolt for all the fun conversations. All remaining errors are my own. iv Contents Title Page ...................................... i Abstract ....................................... ii Acknowledgements ................................. iv List of Tables .................................... vii List of Figures ................................... ix 1 Quantitative Tightening: What are the macroeconomic consequences of re- ducing the Federal Reserve Balance Sheet? ................... 1 1.1 Introduction . 1 1.2 Review of the Literature . 2 1.2.1 Quantitative Easing . 2 1.2.2 Quantitative Tightening . 5 1.3 Empirical Approach . 9 1.3.1 Identification . 13 1.4 Estimation and Inference . 16 1.4.1 Counterfactual Forecasting . 18 1.5 Results . 20 1.5.1 Robustness . 24 v 1.6 Conclusion . 26 1.7 Appendix . 28 2 Greenspan didn’t cause the Great Recession: Examining Federal Reserve Chairmen Deviations from the Taylor Rule ................... 33 2.1 Introduction . 33 2.2 Previous Literature . 35 2.3 Data . 36 2.3.1 Real Time Taylor Rule . 37 2.4 Empirical Methodology . 40 2.5 Results . 42 2.6 Conclusion . 46 3 Long-run and Short-run Volatility in Bitcoin’s Price .............. 50 3.1 Introduction . 50 3.2 Volatility of Bitcoin . 51 3.2.1 Volatility Calculation . 52 3.3 Short-run and Long-run Variance Decompositions . 53 3.3.1 Changes in Mean Over Time . 53 3.3.2 The Local Linear Trend Model . 56 3.4 Variance Decompositions of Bitcoin . 57 3.5 Conclusion . 59 Bibliography . 60 vi List of Tables 1.1 OLS Estimation: Non-Linear Coefficients . 13 1.2 Security Purchase Shock Sign Restrictions . 16 1.3 Reverse QE I 2018-2024 Annualized Median Differential Effects: 2007- 2017 sample . 21 1.4 Reverse QE II 2018-2024 Annualized Differential Effects: 2007-2017 sam- ple....................................... 32 2.1 Tukey HSD:St. Louis Rule . 48 2.2 Tukey HSD: Bernanke Rule . 49 3.1 Changes in Mean Decomposition . 57 vii List of Figures 1.1 Federal Reserve Balance Sheet Trends . 7 1.2 Monetary Policy Instruments . 11 1.3 Securities Held Outright as a proportion of nominal GDP . 12 1.4 Perfect Foresight Conditional Forecasts: 2007-2017 sample . 22 1.5 Perfect Foresight Output and Inflation Conditional Forecasts: 2007-2017 sample . 25 1.6 The Data . 28 1.7 Asymmetric Impact of 1% Decline in Assets/GDP Ratio . 31 2.1 St. Louis Fed Taylor rule . 36 2.2 iF edF und;t − iT aylor;t: 1954-2008 . 37 2.3 Gap Version of Okun’s Law 1954-2008 . 39 2.4 Real-Time iF edF und;t − iSt:Louis;t, 1965-2008 . 39 2.5 Fitted Regimes with Fed Chairmen tenure periods, 1965-2008 . 42 2.6 Fitted Regimes using PCE rather than CPI inflation target from 2000 to 2008 44 2.7 Markov Switching: Regime 1 . 44 2.8 Markov Switching: Regime 2 . 45 2.9 Markov Switching: Regime 3 . 46 3.1 Log Scale Price Level . 51 3.2 Monthly Realized Volatility . 53 viii 3.3 Change-in-Mean Volatility Decomposition . 58 3.4 Bitcoin Realized Volatility Trend Decomposition . 59 ix Chapter 1 Quantitative Tightening: What are the macroeconomic consequences of reducing the Federal Reserve Balance Sheet? 1.1 Introduction What effects will Quantitative Tightening (QT), or Reverse Quantitative Easing have on the United States real economy and financial markets? If the U.S. Federal Reserve’s accumu- lation of a massive quantity of assets had an expansionary effect on the real economy and financial markets, will the plan to shrink the massive balance sheet have the opposite effect on the real U.S. economy and financial markets? For the Federal Reserve, the purpose of reducing security holdings is to eventually reduce the reserve holdings of banks and other entities held at the Federal Reserve to a level where overnight borrowings are needed by some entities to meet reserve require- 1 ments. Once this occurs, the federal funds rate will be the monetary policy instrument of the FOMC, as it was prior to 2008. This balance sheet “normalization” of the conduct of monetary policy will allow the Fed to discontinue the dual policy instrument structure it has operated under since 2008. In the current monetary policy framework, both Interest on Excess Reserves (IOER) and the level of security holdings are used to influence long- term interest rates and (more importantly) portfolio flows from the Treasury market into the private bond and equity markets (Minutes of the FOMC, July 29-30, 2014). In this paper I create a regime dependent, Bayesian structural vector autoregressive (VAR) model and forecast the differential outcome for real economy until December 2024, conditional on the proposed path of asset reduction or a counterfactual policy of maintain- ing a $4.2 trillion security holding portfolio. I find that reverse QE will result in an average of 0.18 percent less real GDP growth per year until 2024, comparing the conditional point forecasts for December 2024 to the forecast conditional on the Federal Reserve maintain- ing a constant dollar value of asset holdings until 2024. However, for both perfect foresight and structural forecasts, the average forecast difference is calculated from forecast variable levels in December 2024. The results are unaffected by shocks to the path of reductions, so long as the Federal Reserve still plans to normalize the balance sheet by the end of 2024. 1.2 Review of the Literature 1.2.1 Quantitative Easing The Federal Reserve’s response to the 2008-2009 financial crisis included large-scale asset purchases - buying government debt and mortgage backed securities (MBS) as a means to provide continued stimulus after the Federal Funds rate had been reduced near zero in November 2008.
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