Christopher A. Hennessy

Taxation, agency conflicts, and the choice between callable and convertible debt

We analyze debt choice in light of taxes and moral hazard. The model features an infinite sequence of nonzero-sum stochastic differential games between equity and debt. Closed-form expressions are derived for all contingent-claims. If equity can increase volatility without reducing asset drift, callable bonds with call premia are optimal. Although callable bonds induce risk shifting, call premia precommit equity to less frequent restructuring and are tax-advantaged. Convertible bonds mitigate risk shifting, but only induce hedging if assets are far from the default threshold. Convertibles are optimal only if risk shifting reduces asset drift sufficiently.

Skin in the Game and Moral Hazard

What determines securitization levels, and should they be regulated? To address these questions we develop a model where originators can exert unobservable effort to increase expected asset quality, subsequently having private information regarding quality when selling ABS to rational investors. Absent regulation, originators may signal positive information via junior retentions or commonly adopt low retentions if funding value and price informativeness are high. Effort incentives are below first-best absent regulation. Optimal regulation promoting originator effort entails a menu of junior retentions or one junior retention with size decreasing in price informativeness. Zero retentions and opacity are optimal among regulations inducing zero effort.

Secondary Market Liquidity and Security Design: Theory and Evidence from ABS Markets

We develop and empirically test a theory of optimal security design under adverse selection accounting for strategic trading by uninformed investors who will liquidate a security in secondary markets only if their idiosyncratic carrying costs exceed the securitys expected trading loss. Such investors demand primary market discounts equaling expected carrying costs borne plus trading losses incurred. Issuers minimize the total illiquidity discount by splitting cash-flow into tranched debt claims with liquidity predicted to increase with seniority, while the optimal number of tranches increases with underlying cash-flow risk. Empirical tests confirm our model predictions. Received November 7, 2013; accepted November 14, 2015 by Editor Itay Goldstein.

Beyond Investment-Cash Flow Sensitivities: Using Indirect Inference to Estimate Costs of External Funds

This paper estimates costs of external finance, applying indirect inference to a dynamic structural model where the corporation endogenously chooses investment, distributions, lever ageand default. The corporation faces double taxation, costly state verification indebt markets, and linear-quadratic costs of external equity. Consistent with direct evidence on under writer fee schedules, behavior is best explained by rising marginal costs of external equity, starting at 3.9%. Contrary to the notion that corporations are debt conservative, leverage is consistent with small (12.2%) bankruptcy costs. Investment-cash flow sensitivities are not a sufficient statistic for financing costs. The cash flow coefficient decreases in external equity costs and increases in bankruptcy costs. When the model is simulated using our parameter estimates, the cash flow coefficient across Fazzari, Hubbard, and Petersens dividend classes is U-shaped. The difference between cash flow coefficients across dividend classes actually decreases as costs are increased.

Beyond Random Assignment: Credible Inference of Causal Effects in Dynamic Economies

Random assignment is insufficient for measured treatment responses to recover causal effects (comparative statics) in dynamic economies. We characterize analytically bias probabilities and magnitudes. If the policy variable is binary there is attenuation bias. With more than two policy states, treatment responses can undershoot, overshoot, or have incorrect signs. Under permanent random assignment, treatment responses overshoot (have incorrect signs) for realized changes opposite in sign to (small relative to) expected changes. We derive necessary and sufficient conditions, beyond random assignment, for correct inference of causal effects: martingale policy variable. Infinitesimal transition rates are only sufficient absent fixed costs. Stochastic monotonicity is sufficient for correct sign inference. If these conditions are not met, we show how treatment responses can nevertheless be corrected and mapped to causal effects or extrapolated to forecast responses to future policy changes within or across policy generating processes.We argue exogenous random treatment is insufficient for valid inference regarding the sign and magnitude of causal effects in dynamic environments. In such settings, treatment responses must be understood as contingent upon the typically unmodeled policy generating process. With binary assignment, this results in quantitatively significant attenuation bias. With more than two policy states, treatment responses can be biased downward, upward, or have the wrong sign. Further, it is not only generally invalid to extrapolate elasticities across policy processes, as argued by Lucas (1976), but also to extrapolate within the same policy process. We derive auxiliary assumptions beyond exogeneity for valid inference in dynamic settings. If all possible policy transitions are rare events, treatment responses approximate causal effects. However, reliance on rare events is overly-restrictive as the necessary and sufficient conditions for equality of treatment responses and causal effects is that policy variable changes have mean zero. If these conditions are not met, we show how treatment responses can nevertheless be corrected and mapped back to causal effects or extrapolated to forecast responses to future policy changes.

The Paradox of Policy-Relevant Natural Experiments

Conventional wisdom holds that natural experiments represent especially credible bases for econometric inference facilitating evidence-based policymaking. We illustrate the fragility of policy-relevant evidence generated by first-stage randomizations by way of parable economies. In the first (second) economy, the econometric analysis is relevant (irrelevant) as the government is able (powerless) to alter policy in the future. In the first economy, but not the second, econometric evidence is contaminated by endogeneity after-the-fact, with treatment responses contingent upon (unknown) parameters of the government objective function into which the empirical estimates will be fed. We have the following paradox: The irrelevant natural experiment is bias-free, while the relevant experiment is biased after-the-fact. Extending this argument, we show a perceived-credible natural experiment is biased by Hawthorne Effects while a perceived-non-credible experiment is not. Importantly, since we consider measure zero experimental subjects, the Hawthorne Effects we illustrate must be understood as arising from rational expectations as distinct from behavioral motives posited in the psychology literatures.

Subject Rational Expectations Will Contaminate Randomized Controlled Medical Trials

Double-blind RCTs are viewed as the gold standard in eliminating placebo effects and identifying non-placebo physiological effects. Expectancy theory posits that subjects have better present health in response to better expected future health. We show that if subjects Bayesian update about efficacy based upon physiological responses during a single-stage RCT, expected placebo effects are generally unequal across treatment and control groups. Thus, the difference between mean health across treatment and control groups is a biased estimator of the mean non-placebo physiological effect. RCTs featuring low treatment probabilities are robust: Bias approaches zero as the treated group measure approaches zero.

Empirical Analysis of Corporate Tax Reforms: What is the Null and Where Did it Come from?

Absent theoretical guidance, empiricists have been forced to rely upon numerical comparative statics from constant tax rate models in formulating testable implications of tradeoff theory in the context of natural experiments. We fill the theoretical void by solving in closed-form a dynamic tradeoff theoretic model in which corporate taxes follow a Markov process with exogenous rate changes. We simulate ideal difference-in-differences estimations, finding that constant tax rate models offer poor guidance regarding testable implications. While constant rate models predict large symmetric responses to rate changes, our model with stochastic tax rates predicts small, asymmetric, and often statistically insignificant responses. Even with very long regimes (one decade), under plausible parameterizations, the true underlying theory—that taxes matter—is incorrectly rejected in about half the simulated natural experiments. Moreover, tax response coefficients are actually smaller in simulated economies with larger tax-induced welfare losses.

Markets vs. Mechanisms

We demonstrate constraints on usage of direct revelation mechanisms (DRMs) by corporations inhabiting economies with securities markets. We consider a corporation seeking to acquire decision relevant information. Posting a standard DRM in an environment with a securities market endogenously increases the outside option of the informed agent. If the informed agent rejects said DRM, then she convinces the market that she is uninformed, and she can trade aggressively sans price impact, generating large (off-equilibrium) trading gains. Due to this endogenous outside option effect, using a DRM to screen out uninformed agents may be impossible. Even when screening is possible, refraining from posting a mechanism and instead relying on markets for information is optimal if the endogenous change in outside option value is sufficiently large. Finally, even if posting a DRM dominates relying on markets, outcomes are improved by introducing a search friction, which randomly limits the agents ability to observe the DRM, forcing the firm to sometimes rely on markets for information.

Liquidity and Feasible Debt Relief

This paper analyzes the determinants of secondary debt market liquidity, identifying conditions under which trading in competitive markets results in sufficient ownership concentration to induce ex post efficient debt relief. The feasibility of debt relief is path-dependent, hinging upon interim economic conditions. Secondary debt markets are likely to freeze during recessions, precisely when trading has high social value. This is due to three factors: severe free-riding reduces profits of large bondholders; uninformed small bondholders are reluctant to sell due to high informational sensitivity of debt; and large investors are more likely to face wealth constraints. However, secondary markets need not freeze during recessions since high liquidity demand of uninformed bondholders increases their willingness to trade. Additionally, broader liquidity shocks during recessions increase the equilibrium stake held by large investors, promoting debt relief.