This dissertation consists of three essays studying the relationship between corporate finance and monetary policy and macroeconomics. In the first essay, I provide novel estimations of the monetary policy’s working capital channel size by estimating a dynamic stochastic macro-finance model using firm-level data. In aggregate, I find a partial channel —about three-fourths of firms’ labor bill is borrowed. But the strength of this channel varies across industries, reaching as low as one-half for retail firms and as high as one for agriculture and construction. These results provide evidence that monetary policy could have varying effects across industries through the working capital channel. In the second essay, I study the effects of the Unconventional Monetary Policy (UMP) of purchasing corporate bonds on firms’ decisions in the COVID-19 crisis. Specifically, I develop a theoretical model which predicts that the firm’s default probability plays a crucial role in transmitting the effects of COVID-19 shock and the UMP. Using the model to evaluate two kinds of heterogeneities (size and initial credit risk), I show that large firms and high-risk firms are more affected by COVID-19 shock and are more responsive to the UMP. I then run cross-sectional regressions, whose results support the theoretical predictions suggesting that the firm’s characteristics, such as assets and operating income, are relevant to understanding the UMP effects. In the third essay, I document that capital utilization and short-term debt are procyclical. I show that a strong positive relationship exists at the aggregate and firm levels. It persists even when I control the regressions for firm size, profits, growth, and business cycle effects. In addition, the Dynamic Stochastic General Equilibrium (DSGE) model shows that in the presence of capital utilization, positive real and financial shocks cause the firm to change its financing of the equity payout policy from earnings to debt, increasing short-term debt.

This dissertation consists of three essays studying topics in financial economicsthrough the lens of quantitative models. In particular, I provide three examples of the effective use of data in the disciplining of financial economics models. In the first essay, I provide evidence of a significant transitory component of aggregate equity payout. Leading asset pricing models assume exogenous dividend growth processes which are inconsistent with this fact. I find that imposing market clearing for consumption and income in these models induces the relevant behaviors in dividend growth, even when dividend growth is obtained indirectly. In the second essay, I provide a novel decomposition of the unconditional equity risk premium. In the data, the majority of the equity premium is attributable to moderate left tail risks, not those associated with disaster states. In stark contrast to the data, leading asset pricing models do not predict that this intermediate left tail region meaningfully contributes to the equity premium. The shortcomings of the models can be pinned on unreasonably low prices of risk for tail events relative to the data. In the third essay, I document a large dispersion in household allocations to risky assets conditional on age. I show that while standard household portfolio choice models can be made to match the average risky share over the lifecycle, the models fall short of generating sufficient heterogeneity in the cross-section of household portfolios.

My project has been a long journey, one that I have learned a tremendous amount on. The final version of my project has come out to be a booklet teaching first time users of code and python the basic steps of getting started and some vital information that I learned while I was learning the language. I started my thesis with the idea of creating a portfolio of stock, bonds and commodities to determine the best allocation of your money over a 30-year period. To do this, I needed to learn how to code and become proficient quickly so I could create a program that would be powerful enough as well as spit out the correct output in the end. Unfortunately, I fell short of being able to build this portfolio out. I took on the challenge of learning Python on my own with no knowledge of any coding language to see if I could pull the whole project together. I failed, but I learned so much along the way and that I think is more valuable than anything. Since I was unable to complete my code, I shifted my attention to creating a small booklet on the basics of getting started in Python as if you have never looked at a coding language. Many of the tips I discuss in my booklet are problems I struggled with when I began. In the beginning I couldn’t even figure out how to get to a coding platform to begin my work, so I began to research and found many helpful tips that took me quite a while to understand.

This thesis aims to promote financial literacy in the community. It was driven by the realization that there was a lack of basic financial knowledge among people at ASU and beyond. The people involved in the reason for the guide had all heard of bonds and understood the basic concepts, but lacked the knowledge of the finite details. The research starts with an overview of the United States bond market and focuses on the creation of a short simple guide. The goal is that anyone can read the guide and have a basic understanding of bonds, talk to financial managers, and do some basic investing. The easy guide is basically a two-page crash course on investing in bonds. Anyone can take a class or watch a video on bonds, but how do they actually start investing in them? This thesis works to answer this question by providing knowledge of real world application. The goal is to take knowledge beyond a book or video and learn from actively investing in a safe and clear way. Bonds are a very useful tool in investing and provide safe returns. The investing proposed is one that would be an alternative to putting money into a savings account. The guide recommends a good starting point of a way to invest in bonds (Specifically the US Treasury). At the same time does some analysis on other investing options for more advanced investors. The work includes an analysis of five bond portfolios and the calculations of finding their actual returns after loads and other fees.