We study a model in which leverage and compensation are both choice variables for the firm and borrowing spreads are endogenous. First, we analyze the correlation between leverage and variable compensation. We show that allowing for endogenous compensation and leverage can explain the conflicting findings of the empirical literature. We uncover a new channel of complementarity between effort and leverage that induces a correlation sign opposite to what current theoretical models predict. Second, we study the dynamics of leverage and compensation design after a credit stimulus. We derive a set of new empirical predictions. For outward-shifts in credit supply, variable compensation is increasing in leverage growth. Moreover, variable compensation increases after the credit stimulus, especially for firms with low idiosyncratic risk.

Corporate bond mutual funds increased their selling of credit protection in the credit default swaps (CDS) market during the 2007–2008 financial crisis. This trading activity was primarily in multi-name CDS, greater among larger and established funds, and directed toward counterparty dealers in financial distress. Funds that sold credit protection during the crisis experienced greater credit market risk and superior post-crisis performance, consistent with higher expected returns from liquidity provision. Funds using Lehman Brothers as a counterparty experienced abnormal outflows and returns of –2% immediately following Lehman's bankruptcy, suggesting that funds’ opportunistic trading in CDS exposed investors to counterparty risk.

Drawing on current literature, this study develops a simple external financing model and provides international evidence of the causal effects of corporate governance improvements on trade credit. We introduce an internal governance perspective, hypothesizing that weak internal governance, which fosters managerial agency problems, allows firm managers to misuse trade credit. Specifically, poor governance may lead firms to rely on supplier financing as a substitute for traditional financing when they face financing constraints, a practice the literature argues raises concerns about shifting a firm's financial burdens onto its suppliers. Using a decade of data surrounding governance-enhancing board reforms in 38 countries, our difference-indifferences analyses strongly support these predictions. We find that strengthening board oversight via exogenous reforms reduces firms' reliance on supplier financing. Improved internal governance decreases firms' dependence on supplier financing and limits the manipulation of payables through real earnings management activities, such as inventory overproduction, which affects accounts payable. We also find that the effect of internal governance reforms is most pronounced in countries with stronger external governance mechanisms, suggesting a complementary effect. Additionally, our findings show that enhanced governance leads to better investment decisions and improved firm performance, especially for financially constrained firms and those with high agency costs.

Using Internet search volume of dividend-related keywords to measure investor preference for dividends that varies over time and across states, we show that dividend sentiment affects corporate policies and asset prices. Investors search more for dividends when economic conditions are poor, with the peak volume reached during the recent COVID-19 pandemic. Firms initiate or increase dividends when dividend sentiment is stronger, especially in regions with strong dividend sentiment. Shifts in dividend sentiment predict higher investor demand for dividends and higher returns for high dividend stocks. Further, mutual funds that pay high dividends receive more inflows when dividend sentiment is stronger.

Rising intangible assets on corporate balance sheets around the world could limit borrowing capacity and consequently hinder growth if firms must preserve cash and forgo investment opportunities. We show that financial development lowers the sensitivity of cash holdings to tangible assets and promotes firm growth. We also find that sectors with a smaller proportion of tangible assets grow faster in countries with more developed financial markets. Our analysis reveals an important asset tangibility channel through which financial development facilitates firm growth.

We examine the impact of local religious beliefs on organizational risk-taking behaviors using hedge funds as a new and unique setting. We find robust evidence that local religiosity is significantly negatively related to both total and idiosyncratic volatilities of hedge funds during 1996–2013. This relation is primarily driven by semi-directional funds, reversed for directional funds, and nonexistent for non-directional funds. Consistent with the local preference channel, the impact of local religiosity on risk-taking is only pronounced among funds for which local managers and investors are economically more important, namely young and small funds. Further, hedge funds located in more religious counties tend to hold less risky stocks and diversify their stock portfolios across industries, thus contributing to lower hedge fund risk-taking. Overall, our evidence suggests that local culture, in particular religiosity, may motivate hedge fund managers to reduce risk.

We evaluate the descriptive validity of the cost behavior model for profit analysis using Compustat data. For this purpose, we propose an earnings forecast model decomposing earnings into components that reflect (1) variability of costs with sales revenue and (2) stickiness in costs with sales declines. We evaluate the predictive ability of our model by benchmarking its performance in forecasting one-year-ahead returns on equity against that of two other time-series models based on line item information reported in the income statement and in the statement of cash flows. Specifically, we consider a model that disaggregates earnings into operating income and non-operating income components and another that disaggregates earnings into cash flows and accruals components. While all three models are less accurate than analysts' consensus forecasts that rely on a larger information set, we find that our model provides substantial improvement in forecast accuracy over the other two models that use only the line items in the financial statements. Finally, invoking the market efficiency assumption, we find that earnings forecast errors based on our model have greater relative information content than forecast errors based on the two alternative models based on financial statement information in explaining abnormal stock returns.

We examine the cross-sectional predictability of corporate bond returns using a novel international dataset and a set of machine learning techniques. We find strong predictability in both U.S. and non-U.S. markets, with differing predictive factors. Bonds in developed markets show greater integration with the U.S. market and stronger ties to equity markets. Predictive performance of machine learning models varies over time and is greater before the onset of the COVID-19 pandemic and during periods of deteriorating business conditions, reduced market liquidity, elevated investor sentiment, and heightened risk aversion. The results offer insights into bond pricing and global diversification opportunities.