Sudheer Chava

Modeling the Loss Distribution

In this paper, we focus on modeling and predicting the loss distribution for credit risky assets such as bonds and loans. We model the probability of default and the recovery rate given default based on shared covariates. We develop a new class of default models that explicitly accounts for sector specific and regime dependent unobservable heterogeneity in firm characteristics. Based on the analysis of a large default and recovery data set over the horizon 1980--2008, we document that the specification of the default model has a major impact on the predicted loss distribution, whereas the specification of the recovery model is less important. In particular, we find evidence that industry factors and regime dynamics affect the performance of default models, implying that the appropriate choice of default models for loss prediction will depend on the credit cycle and on portfolio characteristics. Finally, we show that default probabilities and recovery rates predicted out of sample are negatively correlated and that the magnitude of the correlation varies with seniority class, industry, and credit cycle. This paper was accepted by Wei Xiong, finance.

Determinants of the floating-to-fixed rate debt structure of firms.

We analyze the effects of managerial incentive, monitoring, firm characteristics and market-timing on floating-to-fixed rate debt structure of firms. We find that the CFOs (not CEOs) incentive has a strong influence on a firms debt structure. When CFOs have incentives to increase (decrease) firm-risk, firms obtain volatility-increasing (decreasing) debt structure. Internal monitoring by the CEO and independent board members as well as external monitoring through corporate control market weakens the link between CFOs incentive and debt structure. Our findings suggest that agency problems at the level of non-CEO executives may be an important driver of various corporate decisions.

Related Securities and Equity Market Quality: The Case of CDS

We document that the emergence of markets for single-name credit default swap (CDS) contracts adversely affects equity market quality. The finding that firms with traded CDS contracts on their debt have less liquid equity and less efficient stock prices is robust across a variety of market quality measures. We analyze the potential mechanisms driving this result and find evidence consistent with negative trader-driven information spillovers that result from the introduction of CDS. These spillovers greatly outweigh the potentially positive effects associated with completing markets (i.e., CDS markets increase hedging opportunities) when firms and their equity markets are “bad” states. In “good” states, we find some evidence that CDS markets can be beneficial.

Credit Conditions and Stock Return Predictability

Credit Conditions and Expected Stock Returns We analyze the predictability of U.S. stock returns using a measure of credit standards (Standards) derived from the Federal Reserve Board’s Senior Loan Officer Opinion Survey on Bank Lending Practices. We find that Standards is a strong predictor of stock returns at a business cycle frequency, especially in the post-1990 data period. Standards performs well both in-sample and out-of-sample and is robust to a host of consistency checks including a small sample analysis. Standards is a survey variable that is not linked to the level of stock prices; hence, it is unlikely that the predictive power of Standards is driven by stock mispricing. Instead, its predictive power is consistent with capturing a time-varying investment opportunity set through either time-varying aggregate risk aversion or timevarying risk.

Modeling Expected Loss with Unobservable Heterogeneity

In this paper we model the expected loss over multi-year horizons. Investors usually have only incomplete information about the true state of a firm. To model this form of unobservable heterogeneity, we introduce a latent non-negative random variable into the model specification of the probability of default and the recovery rate. To estimate the expected loss over arbitrary horizons, we estimate the coefficients for the stochastic processes describing the covariates for the probability of default for each obligor and the loss given default. We provide an analysis of both in and out of sample performance of our estimates of the probability of default and the loss given default.

Lending to Innovative Firms

Is bank financing compatible with innovation? We show that an exogenous enhancement in the value of borrowers’ patents, either through greater patent protection or creditor rights over collateral, results in cheaper loans. Using regression discontinuity design, we show that although R&D investment sharply drops following a financial covenant violation, the reduction is concentrated in firms with less productive R&D. Consequently, R&D reduction does not impair innovative output. Our results suggest that the property rights that patents confer to intellectual property and to lenders’ judicious exercise of control rights allow bank loans to be a viable means of financing for innovative firms.

Credit Default Swaps and Moral Hazard in Bank Lending

We analyze whether introduction of Credit Default Swaps (CDSs) on borrowers’ debt misaligns incentives between banks and borrowers in the private debt market. In contrast to predictions of an empty creditor problem, after a covenant violation, CDS firms do not become distressed or go bankrupt at a higher rate than firms without CDS. But, consistent with lender moral hazard, CDS firms do not decrease their investment after a covenant violation, even those that are more prone to agency issues. In line with increased bargaining power of lenders, CDS firms pay a significantly higher spread on loans issued after covenant violations compared with non-CDS firms that violate covenants. These results are magnified when lenders have weaker incentives to monitor (higher purchase of credit derivatives, higher amount of securitization and higher noninterest income). Finally, consistent with our evidence of lender moral hazard, we document positive abnormal returns around bank loan announcements only for nonCDS firms, but not for CDS firms. JEL Code: G21, G31, G32.

Shareholder Bargaining Power, Debt Overhang, and Investment

Using a dynamic model of strategic bargaining between equity and debt holders following default, we analyze the impact of shareholder bargaining power on the investment effects of debt overhang. Our empirical tests utilize a new measure of debt overhang wedge based on default probabilities generated from a hazard model for bankruptcy. Consistent with the theoretical predictions, bondholder (shareholder) ownership concentration ceteris paribus enhances (weakens) the overhang wedge and dampens (increases) capital investment. We identify novel ownership structure related factors in firm-level capital investment and document how post-default shareholder bargaining power alleviates the underinvestment problem caused by debt overhang.

Financial Constraints, Monetary Policy Shocks, and the Cross-Section of Equity Returns

We analyze the impact of unanticipated monetary policy changes on equity returns and document that financially constrained firms earn a significantly lower return following rate increases as compared to unconstrained firms. Trading volume is significantly lower for constrained firms on FOMC announcement days but the differential return response manifests with a delay. Further, unanticipated increases in Federal funds rate are associated with a larger decrease in expected cash flow news, but not of discount rate news, for constrained firms relative to unconstrained firms. Our results highlight how monetary policy shocks have a disproportionate real impact on financially constrained firms.

The Dark Side of Technological Progress? Impact of E-Commerce on Employees at Brick-and-Mortar Retailers

Using an employer-employee payroll dataset for approximately 2.6 million retail workers, we analyze the impact of the staggered rollout of a major e-commerce retailers fulfillment centers on the income and employment of workers at geographically proximate brick-and-mortar retail stores. We find that the establishment of an e-commerce fulfillment center in a county has a negative effect on the income of retail workers in that county and in neighboring counties within 100 miles. Wages of hourly workers, especially part-time hourly workers, decrease significantly. This decrease is driven by a drop in the number of hours worked. We observe a U-shaped pattern in which both young and old workers experience a sharper decrease in wage income. Consequently, in these counties, there is a decrease in credit scores and an increase in delinquency for retail workers that have higher prior credit utilization. Using sales and employment data for 3.2 million stores, we find that retail stores in counties around fulfillment centers experience a reduction in sales and in their number of employees. Further, there is a decrease in entry and an increase in exits for stores in the retail sector, with small and young retail stores exiting at a higher rate. Our robustness tests show that our results are unlikely to be driven by prevailing local economic conditions. Overall, our results highlight the extent to which a dramatic increase in e-commerce retail sales can have some adverse consequences for workers at traditional brick-and-mortar stores.