Real Assets and Capital Structure

Abstract

We characterize the relation between asset structure and capital structure by exploiting variation in the salability of corporate assets. To establish this link, we distinguish across different assets in firms’ balance sheets (machinery, land, and buildings) and use an instrumental approach that incorporates market conditions for those assets. We also use a natural experiment driving differential increases in the supply of real estate assets across the United States: The Defense Base Closure and Realignment Act of 1990. Consistent with a supply-side view of capital structure, we find that asset redeployability is a main driver of leverage when credit frictions are high.

Annual Report Readability, Tone Ambiguity, and the Cost of Borrowing

“…We include PROFITABILITY to capture the fact that the default risk is relatively low for a profitable firm. TANGIBILITY is the ratio of total tangible assets (property, plant, and equipment (PPE)) to the book value of total assets (Campello and Giambona (2013)). A firm with high tangibility generally has high expected recovery rates in the event of default and thus should be able to borrow at a relatively low interest rate by pledging tangible assets to creditors.…”

“…PROFITABILITY: The ratio of earnings before interest, taxes, depreciation, and amortization (EBITDA) to total assets. TANGIBILITY: The ratio of total tangible assets (property, plant, and equipment (PPE)) to book value of total assets, following Campello and Giambona (2013). EDF: A firm's expected default frequency, following Bharath and Shumway (2008).…”

Credit Protection and Lending Relationships

“…Shim and Zhu (2010), in a study of the impact of CDS trading on spreads in Asian bond markets, instead find that more opaque firms tend to benefit more. They also find 29 For recent evidence, see Campello and Giambona (2012). 30 Formally, in our model, spreads are given by (T − (1 − θ)L/(θe * T ) − 1, where T ≥ I (with strict inequality for some borrowers) and e * is equilibrium effort.…”

The Long-Run Real Effects of Banking Crises: Firm-Level Investment Dynamics and the Role of Wage Rigidity

“…To alleviate concerns that my results are driven by other firm characteristics which were found to be associated with refinancing risk or firms' corporate policies, I combine the difference-in-differences approach with an appropriate matching methodology. This paper uses the bias-corrected Abadie and Imbens (2006) matching estimator, which has recently been used in the corporate finance literature by Almeida, Campello, Laranjeira, and Weisbenner (2012), Campello and Giambona (2013), Gropp, Mosk, Ongena, and Wix (2016), and Kahle and Stulz (2013). 8 In contrast to standard propensity score matching, the Abadie and Imbens (2006) matching estimator minimizes the (Mahalanobis) distance between a vector of observed matching covariates across firms in the treatment group and firms in the control group pool and introduces a bias correction to account for inexact matches on continuous variables.…”