I empirically investigate the relation between chief executive officer (CEO) inside debt holdings and mergers and acquisitions (M&As), and find evidence consistent with the agency theory’s prediction of a negative relation between CEO inside debt holdings and corporate risk taking. Further analysis shows that CEO inside debt holdings are positively correlated with M&A announcement abnormal bond returns and long-term operating performance, but negatively correlated with M&A announcement abnormal stock returns. Finally, I find evidence that acquirers restructure the postmerger composition of CEO compensation that mirrors their capital structure in order to alleviate incentives for wealth transfer from shareholders to bondholders or vice versa.

We investigate stock returns, market quality, and options market activity around the flash crash of May 6, 2010. Abnormal returns are negative on the day of and the day after the flash crash for stocks that had trades that executed during the crash subsequently cancelled by either Nasdaq or NYSE Arca. Consistent with studies that suggest that other sources of liquidity withdrew from the markets during the flash crash, we find that the fraction of trades executed by the NYSE increases during this volatile period. Market quality deteriorates following the flash crash as bid-ask spreads increase and quote depths decrease. Evidence from the options markets indicates that investor uncertainty increased around the time of the crash and remained elevated for several days.

This paper develops a theory in which housing prices, the capital structures of banks (mortgage lenders) and the capital structures of mortgage borrowers are all endogenously determined in equilibrium. There are four main results. First, leverage is a “positively correlated” phenomenon in that high leverage among borrowers is positively correlated with high leverage among banks, and higher house prices lead to higher leverage for both. The intuition is that first-time homebuyers with fixed wealth endowments must borrow more to buy more expensive homes, whereas higher current house prices rationally imply higher expected future house prices and therefore higher collateral values on bank loans, inducing banks to be more highly levered. Second, higher bank leverage leads to greater house price volatility in response to shocks to fundamental house values. Third, a bank’s exposure to credit risk depends not only on its own leverage but also on the leverage decisions of other banks. Fourth, positive fundamental shocks to house prices dilute financial intermediation by reducing banks’ pre-lending screening, and this reduction in bank screening further increases house prices. Empirical and policy implications of the analysis are drawn out, and empirical evidence is provided for the first two main results. The key policy implications are that greater geographic diversification by banks, tying mortgage tax exemptions to the duration of home ownership, and increasing bank capital requirements when borrower leverage is high can help reduce house price volatility.

Massive Online Open Courses (MOOCs) present the potential to deliver high quality education to a large number of students. But they suffer from low completion rates. This paper identifies disorganization as a factor behind failure to complete a MOOC. Students who enroll one day late are 17 percentage points less likely to earn a certificate than students who enroll exactly on time. This reflects selection, but it does seem to be related to demographic characteristics, motivation to complete the course, or ability. This suggests that building in even more structure in the MOOC could be a factor in improving performance.

We show that wrongful discharge laws—laws that protect employees against unjust dismissal—spur innovation and new firm creation. Wrongful discharge laws, particularly those that prohibit employers from acting in bad faith ex post, limit employers' ability to hold up innovating employees after the innovation is successful. By reducing the possibility of holdup, these laws enhance employees'innovative efforts and encourage firms to invest in risky but potentially mould-breaking projects. We develop a model and provide supporting empirical evidence of this effect using the staggered adoption of wrongful discharge laws across U.S. states.

We investigate the effect of shareholder activism on debtholders by examining a sample of bank loans for firms targeted by activist hedge funds. We compare loan spreads before and after intervention and show the effects of heterogeneous shareholder actions. Spreads increase when shareholder activism relies on the market for corporate control or financial restructuring. In contrast, spreads decrease when activists address managerial entrenchment. Furthermore, the effects are more pronounced when pre-existing governance mechanisms are weak. Our findings suggest that shareholder activism does not necessarily exacerbate bondholder-shareholder conflicts of interest and highlight the role of activism in aligning investors.

Why don’t VCs eliminate excess demand for follow-on funds by raising fees? We propose a model of learning that leads to informational holdup. Current investors learn about skill whereas outside investors observe only returns. This gives current investors holdup power when the VC raises his next fund: Without their backing, no-one will fund him, as outside investors interpret the lack of backing as a sign of low skill. Holdup power diminishes the VC’s ability to increase fees in line with performance, leading to return persistence. Empirical evidence supports the model. We estimate that up to two-thirds of VC firms lack skill.

We propose robust methods for inference about the effect of a treatment variable on a scalar outcome in the presence of very many regressors in a model with possibly non-Gaussian and heteroscedastic disturbances. We allow for the number of regressors to be larger than the sample size. To make informative inference feasible, we require the model to be approximately sparse; that is, we require that the effect of confounding factors can be controlled for up to a small approximation error by including a relatively small number of variables whose identities are unknown. The latter condition makes it possible to estimate the treatment effect by selecting approximately the right set of regressors. We develop a novel estimation and uniformly valid inference method for the treatment effect in this setting, called the “post-double-selection†method. The main attractive feature of our method is that it allows for imperfect selection of the controls and provides confidence intervals that are valid uniformly across a large class of models. In contrast, standard post-model selection estimators fail to provide uniform inference even in simple cases with a small, fixed number of controls. Thus, our method resolves the problem of uniform inference after model selection for a large, interesting class of models. We also present a generalization of our method to a fully heterogeneous model with a binary treatment variable. We illustrate the use of the developed methods with numerical simulations and an application that considers the effect of abortion on crime rates.

The Combinatorial Clock Auction (CCA) is an important recent innovation in auction design which has been adopted for many spectrum auctions worldwide. Since its inception, the CCA has been in almost continual evolution. We begin by reviewing some important changes which have already occurred. Despite these enhancements, we observe that the performance of the CCA is still limited by weak activity rules, suboptimal price feedback, and a missing-bid problem. We then describe further evolutionary changes, including new activity rules, new approaches to pricing, and an integration of non-mutually-exclusive bids, which will help to address these issues.