2012
DOI: 10.1017/s0022109012000051
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Equity Mispricing and Leverage Adjustment Costs

Abstract: We find that equity mispricing impacts the speed at which firms adjust to their target leverage (TL) and does so in predictable ways depending on whether the firm is overor underlevered. For example, firms that are above their TL and should therefore issue equity (or retire debt) adjust more rapidly toward their target when their equity is overvalued. However, when a firm is undervalued but needs to reduce leverage, the speed of adjustment is much slower. Our findings support the role of equity mispricing as a… Show more

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Cited by 117 publications
(51 citation statements)
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References 55 publications
(122 reference statements)
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“…8 To probe the effect of CEO's inside debt holdings on capital structure adjustments, we conduct both univariate and multivariate analyses. For the univariate analyses, we follow Faulkender et al (2012) and Warr et al (2012) to estimate Model (1) using ordinary least squares (OLS) in subsamples partitioned according to CEO's inside debt holdings, with the target leverage, L * it , as the predicted value from Model (2). For the multivariate analyses, we modify Equation (1) as follows to allow for CEO's inside debt and other factors to affect SOA:…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…8 To probe the effect of CEO's inside debt holdings on capital structure adjustments, we conduct both univariate and multivariate analyses. For the univariate analyses, we follow Faulkender et al (2012) and Warr et al (2012) to estimate Model (1) using ordinary least squares (OLS) in subsamples partitioned according to CEO's inside debt holdings, with the target leverage, L * it , as the predicted value from Model (2). For the multivariate analyses, we modify Equation (1) as follows to allow for CEO's inside debt and other factors to affect SOA:…”
Section: Methodsmentioning
confidence: 99%
“…3 Monte Carlo simulations conducted by Flannery and Hankins (2013) and Dang, Kim, and Shin (2015) find that the Elsas-Florysiak (2015) DPF estimator and the Blundell-Bond (1998) system GMM estimator produce consistent estimates. Faulkender et al (2012), Warr et al (2012), and Liao et al (2015) use this dynamic panel model to estimate target leverage. Then, in the second step, they estimate the heterogeneous SOAs toward this target that hinge on factors including cash flows and corporate governance.…”
Section: Related Literaturementioning
confidence: 99%
“…Only a few previous studies address cross-sectional heterogeneity in adjustment speeds (Byoun 2008;Flannery and Hankins 2007;Hovakimian and Li 2009;Lockhart 2010;Warr et al 2009). These studies typically focus on one specific issue and do not explore heterogeneity in speeds of adjustment with regard to a broad set of firm characteristics.…”
Section: Introductionmentioning
confidence: 99%
“…We estimate firms' TDRs with a similar regression specification to those used in Hovakimian and Li (2011) and Warr, Elliot, Koëter-Kant, and Öztekin (2012). However, in order to avoid a substantial look-ahead bias, we do not include firm or time fixed-effects in our main model.…”
Section: Tdr and Soamentioning
confidence: 99%
“…provides evidence that mechanical mean reversion in the DRs cannot explain our return results.Thus far, we have not excluded utility stocks and financial stocks from the sample. Previous capital structure studies, includingFlannery and Rangan (2006) andWarr et al (2012), among others, have excluded utilities (standard industrial classification [SIC] codes 4900-4999) and financials (SIC codes 6000-6999) since these are heavily regulated industries. To test whether the inclusion of utilities and financials are driving the results, the HDMLD portfolios are formed excluding utilities and financials and are presented in Section 5.2.…”
mentioning
confidence: 99%