2019
DOI: 10.1016/j.jempfin.2019.03.004
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Risk changes and external financing activities: Tests of the dynamic trade-off theory of capital structure

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Cited by 36 publications
(46 citation statements)
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“…In particular, the SPSM process using the KSS PURT with the trend and Fourier functions offers robust proof showing the debt-ratio stationarity for 10 of 15 firms. These results are consistent with supporting trade-off theory (e.g., Solomon 1963;Shyam-Sunder and Myers 1999;Hovakimian et al 2001;Ozkan 2001;Sogorb Mira and López-Gracia 2003;Leary and Roberts 2005;Flannery and Rangan 2006;Hackbarth et al 2007;Chang and Yu 2010;Elsas and Florysiak 2011;Chen et al 2019;and Dierker et al 2019). In particular, the outcomes of this study were consistent with those of Flannery and Rangan (2006); Elsas and Florysiak (2011); and Ozkan (2001) in developed countries.…”
Section: Discussion Of the Resultssupporting
confidence: 89%
“…In particular, the SPSM process using the KSS PURT with the trend and Fourier functions offers robust proof showing the debt-ratio stationarity for 10 of 15 firms. These results are consistent with supporting trade-off theory (e.g., Solomon 1963;Shyam-Sunder and Myers 1999;Hovakimian et al 2001;Ozkan 2001;Sogorb Mira and López-Gracia 2003;Leary and Roberts 2005;Flannery and Rangan 2006;Hackbarth et al 2007;Chang and Yu 2010;Elsas and Florysiak 2011;Chen et al 2019;and Dierker et al 2019). In particular, the outcomes of this study were consistent with those of Flannery and Rangan (2006); Elsas and Florysiak (2011); and Ozkan (2001) in developed countries.…”
Section: Discussion Of the Resultssupporting
confidence: 89%
“…Debt maturity influenced insolvency risk positively, and it was significant for panels A & B but insignificant for panel-C. Whereas, the impact of capital structure on insolvency risk represented by debt ratio is negative in the case of panel A similar to (Dierker, Lee, & Seo, 2019) but positive for Panel B & C as in (Bhagat, Bolton, & Lu, 2015). However, this relationship is insignificant in all three cases, as also reported by (Chung, Na, & Smith, 2013).…”
Section: Methodssupporting
confidence: 52%
“…Following Dierker et al (2019), we use two measures of external financing: (1) External Equity Financing, estimated as the ratio of the difference between the sale of common and preferred stocks (SSTK) and the purchase of common and preferred stocks (PRSTKC) to total assets at the beginning of the year, and (2) External Debt Financing, estimated as the ratio of long-term debt issuance (DLTIS) minus long-term debt reduction (DLTR) to total assets at the beginning of the year. The term X i t , is a vector of controls.…”
Section: Data Breaches and External Financingmentioning
confidence: 99%
“…However, given that breached firms are probably viewed as a higher credit risk by the financial markets and therefore face higher costs of capital, we expect that they would find it difficult to raise external financing, and, therefore, external financing activities should decline after the disclosure of a breach incident. To test this, we specify the following model: External0.25emFinancei,t=α+βBreachMathClass-open(0/1MathClass-close)t+γXi,t+ρj+δt+εi,t. Following Dierker et al (2019), we use two measures of external financing: (1) External Equity Financing , estimated as the ratio of the difference between the sale of common and preferred stocks (SSTK) and the purchase of common and preferred stocks (PRSTKC) to total assets at the beginning of the year, and (2) External Debt Financing , estimated as the ratio of long‐term debt issuance (DLTIS) minus long‐term debt reduction (DLTR) to total assets at the beginning of the year. The term Xi,t is a vector of controls.…”
Section: Effects Of Actual Data Breachesmentioning
confidence: 99%