This dissertation consists of two essays. The first, titled “Market Timing in Corporate Finance Decisions: Evidence from Stock Market Anomalies” revisits the question of market timing in corporate finance by using a new mispricing measure based on stock return anomalies. Using this mispricing measure, I show that U.S. firms are 59% more likely to issue equity when overvalued and 28% more likely to repurchase shares when undervalued. Moreover, this market timing behavior is more pronounced as executives gain more personal benefits from these strategies. Executives use market timing strategies in acquisitions as well. I document that executives are more likely to use equity as currency in acquisitions when overvalued and use cash when undervalued. I find consistent evidence using an international dataset that includes 33 countries. These findings provide new evidence about market timing and support the market timing hypothesis. The second essay, titled “Monetary Policy Uncertainty and Asset Price Bubbles” examines the impact of monetary policy uncertainty (MPU) in predicting future asset price bubbles. Using US data from 1926-2019, this paper shows that greater monetary policy uncertainty leads to a greater likelihood of bubbles in industry-level returns. The result is robust to criticisms on the ex-ante identification of bubbles. This paper also documents that including MPU in machine learning models improves the models’ ability to predict bubbles in real-time.

Natural Language Processing (NLP) techniques have increasingly been used in finance, accounting, and economics research to analyze text-based information more efficiently and effectively than primarily human-centered methods. The literature is rich with computational textual analysis techniques applied to consistent annual or quarterly financial fillings, with promising results to identify similarities between documents and firms, in addition to further using this information in relation to other economic phenomena. Building upon the knowledge gained from previous research and extending the application of NLP methods to other categories of financial documents, this project explores financial credit contracts, better understanding the information provided through their textual data by assessing patterns and relationships between documents and firms. The main methods used throughout this project is Term Frequency-Inverse Document Frequency (to represent each document as a numerical vector), Cosine Similarity (to measure the similarity between contracts), and K-Means Clustering (to organically derive clusters of documents based on the text included in the contract itself). Using these methods, the dimensions analyzed are various grouping methodologies (external industry classifications and text derived classifications), various granularities (document-wise and firm-wise), various financial documents associated with a single firm (the relationship between credit contracts and 10-K product descriptions), and how various mean cosine similarity distributions change over time.

This thesis studies the technological change in the US commercial banking market and its influence on banks' lending practices. The second chapter provides some empirical facts.

The third chapter studies the welfare consequences of the destructive creation (bank

branches replaced by internet banking) of the US commercial banking

market following the Great Recession of 2009. Using a structural model,

we find that the cleansing effect (closure of unproductive bank branches)

of the recession increases the units of internet banking by about 56\% in 2016, compared to the case where the cleansing effect is absent. The share of internet banking in the retail service market is increased from 48\% to 60\% and the price of internet banking service is decreased by a factor of 16 by the cleansing effect of the Great Recession.

The two changes lowers the price of retail banking services in 2016 by 37\%: 53\% of the price reduction is attributable

to the replacement

of branches by internet banking and 47\% is attributable to the reduction of the price of internet banking. However, this cleansing effect also

results in a 2.5\% decrease in small business services in small cities.

These findings suggest that the cleansing effect of the recession benefits

retail consumers. However, small business lending may suffer.

The fourth chapter evaluates how information technology (IT) improvements contribute to the decline of small business lending in the US commercial banking market from 2002 to 2017. This paper estimates a general equilibrium dynamic model with banks that differ in size and choose the level of the transaction (hard information intensive) and relationship (soft information intensive) lending. The model shows that banks’ costs of evaluating borrowers’ hard information declined over this period by 46\%, and small business loans fell by 7\% (12\% in the data). This paper finds that banks’ higher reliance on IT to issue transaction loans is responsible for 37\% of the decline in the data, and the consolidation caused by IT improvements caused 22\% of the decline. Contrary to previous findings, this paper finds that when general equilibrium is considered, policy protecting small banks cannot increase small business lending.

This paper looks at defined contribution 401(k) plans in the United States to analyze whether or not participants have plans with better plan characteristics defined in this study by paying more for administration services, advisory services, and investments. By collecting and analyzing Form 5500 and audit data, I find that there is no relation between how much a plan and its participants are paying for recordkeeping, advisory, and investment fees and the analyzed characteristics of the plan that they receive in regards to active/passive allocation, revenue share, and the performance of the funds.

Firms reduce investment when facing downward wage rigidity (DWR), the inability or unwillingness to adjust wages downward. I construct DWR measures and exploit staggered state-level changes in minimum wage laws as an exogenous variation in DWR to document this fact. Following a minimum wage increase, firms reduce their investment rate by 1.17 percentage points. Surprisingly, this labor market friction enhances firm value and production efficiency when firms are subject to other frictions causing overinvestment, consistent with the theory of second best. Finally, I identify increased operating leverage and aggravation of debt overhang as mechanisms by which DWR impedes investment.

Schennach (2007) has shown that the Empirical Likelihood (EL) estimator may not be asymptotically normal when a misspecified model is estimated. This problem occurs because the empirical probabilities of individual observations are restricted to be positive. I find that even the EL estimator computed without the restriction can fail to be asymptotically normal for misspecified models if the sample moments weighted by unrestricted empirical probabilities do not have finite population moments. As a remedy for this problem, I propose a group of alternative estimators which I refer to as modified EL (MEL) estimators. For correctly specified models, these estimators have the same higher order asymptotic properties as the EL estimator. The MEL estimators are obtained by the Generalized Method of Moments (GMM) applied to an exactly identified model. The simulation results provide promising evidence for these estimators. In the second chapter, I introduce an alternative group of estimators to the Generalized Empirical Likelihood (GEL) family. The new group is constructed by employing demeaned moment functions in the objective function while using the original moment functions in the constraints. This designation modifies the higher-order properties of estimators. I refer to these new estimators as Demeaned Generalized Empirical Likelihood (DGEL) estimators. Although Newey and Smith (2004) show that the EL estimator in the GEL family has fewer sources of bias and is higher-order efficient after bias-correction, the demeaned exponential tilting (DET) estimator in the DGEL group has those superior properties. In addition, if data are symmetrically distributed, every estimator in the DGEL family shares the same higher-order properties as the best member.  

Mutual monitoring in a well-structured authority system can mitigate the agency problem. I empirically examine whether the number 2 executive in a firm, if given authority, incentive, and channels for communication and influence, is able to monitor and constrain the potentially self-interested CEO. I find strong evidence that: (1) measures of the presence and extent of mutual monitoring from the No. 2 executive are positively related to future firm value (Tobin's Q); (2) the beneficial effect is more pronounced for firms with weaker corporate governance or CEO incentive alignment, with stronger incentives for the No. 2 executives to monitor, and with higher information asymmetry between the boards and the CEOs; (3) such mutual monitoring reduces the CEO's ability to pursue the "quiet life" but has no effect on "empire building;" and (4) mutual monitoring is a substitute for other governance mechanisms. The results suggest that mutual monitoring by a No. 2 executive provides checks and balances on CEO power.

This paper examines how equity analysts' roles as information intermediaries and monitors affect corporate liquidity policy and its associated value of cash, providing new evidence that analysts have a direct impact on corporate liquidity policy. Greater analyst coverage (1) reduces information asymmetry between a firm and outside shareholders and (2) enhances the monitoring process. Consistent with these arguments, analyst coverage increases the value of cash, thereby allowing firms to hold more cash. The cash-to-assets ratio increases by 5.2 percentage points when moving from the bottom analyst-coverage decile to the top decile. The marginal value of $1 of corporate cash holdings is $0.93 for the bottom analyst-coverage decile and $1.83 for the top decile. The positive effects remain robust after a battery of endogeneity checks. I also perform tests employing a unique dataset that consists of public and private firms, as well as a dataset that consists of public firms that have gone private. A public firm with analyst coverage can hold approximately 8% more cash than its private counterpart. These findings constitute new evidence on the real effect of analyst coverage.

This paper examines dealers' inventory holding periods and the associated price markups on corporate bonds from 2003 to 2010. Changes in these measures explain a large part of the time series variation in aggregate corporate bond prices. In the cross-section, holding periods and markups overshadow extant liquidity measures and have significant explanatory power for individual bond prices. Both measures shed light on the credit spread puzzle: changes in credit spread are positively correlated with changes in holding periods and markups, and a large portion of credit spread changes is explained by them. The economic effects of holding periods and markups are particularly sharp during crisis periods.