Corporate financial leverage and M&As choices: Evidence from the shipping industry

Abstract

High capital intensity and reliance on debt financing are among the most prominent characteristics of the shipping industry. The corporate finance literature has documented that beyond a certain threshold, leverage can hamper a firm's ability to raise capital, and as a result, have a bearing on its corporate investment policy. The new, more restrictive, financing landscape in the shipping sector has put the management of capital structure on the spotlight as a key driver of investment policy, financial health, and thus, firm success. In this paper, we examine for the first time the link between the financing policy of shipping companies and their corporate investment decisions. We focus on the impact of deviations from target capital structure on mergers and acquisitions (M&A); an increasingly important corporate growth vehicle for shipping companies, with directly measurable outcomes. Deviations from optimal leverage display a strong association with the likelihood to consummate acquisitions, deal size, the financing method as well as the M&A outcome. Higher debt levels are shown to have a negative effect on acquisitiveness and a positive effect on the quality of corporate investment; a pattern with direct policy implications for shipping companies, their management teams, and shareholders.

The announcement effect of shipping sale-and-leaseback transactions

“…Luo (2005) finds that short-run changes in stock prices around M&As significantly affect managerial decisions to complete the deals. In shipping research, the event study analysis has gained popularity in examining The announcement effect of shipping SLBs the value creation effect of M&A (Alexandridis et al, 2020;Alexandrou et al, 2014;Andreou et al, 2012;Darkow et al, 2008;Panayides and Gong, 2002) while to the best of our knowledge, there is only one study reporting the long-run results (Choi and Yoshida, 2013).…”

“…Luo (2005) finds that short-run changes in stock prices around M&As significantly affect managerial decisions to complete the deals. In shipping research, the event study analysis has gained popularity in examining the value creation effect of M&A (Alexandridis et al. , 2020; Alexandrou et al.…”

Non-Financial Enterprise Financialization, Product Market Competition, and Total Factor Productivity of Enterprises

“…Likewise, Ehigiamusoe and Lean (2019) concludes in his study that financialization has acted as a “reservoir,” that is, the increasing percentage of financial assets held could alleviate financing constraints on enterprises. As far as financial assets are concerned, its profit effect could boost R&D and innovation of enterprises in the future (Carstens & Wesson, 2019), its high liquidity could mitigate risks of financial distress that enterprises may face (Aktas et al, 2019; Alexandridis et al, 2020), and its high return of investment (“ROI”) with rising asset prices could effectively ameliorate balance sheets of enterprises, which, in turn, will catalyze refinancing and drive enterprises to allocate more funds into real investments (Nasir et al, 2021). As for adverse viewpoints, enterprise financialization obviously imposes the “crowding-out” effect upon enterprises’ investment in main businesses and innovation (Stockhammer, 2004), while the decreasing funds for real investment and R&D greatly lowers down enterprises’ capabilities of innovation (Nguyen et al, 2020).…”

Credit Absorption Capacity of Businesses in the Construction Sector of the Czech Republic—Analysis Based on the Difference in Values of EVA Entity and EVA Equity

“…It can be used as a management system based on business values or within businesses to compare the performance of individual units [13]. A business may decide to use equity if the rating is favorable or to use external capital if the costs are relatively low [14]. Debt financing enables a business to, among other things, consider and take advantage of investment opportunities that can help increase its value.…”

“…EVA ENTITY 2014 = 1250.86 × (1 − 0.2032) − 15, 036.05 × 0.0888 = −338.80 EVA ENTITY 2015 = 1546.68 × (1 − 0.2021) − 15, 098.98 × 0.0820 = −3.42 EVA ENTITY 2016 = 2101.15 × (1 − 0.2115) − 21, 808.57 × 0.0749 = 23.66 EVA ENTITY 2017 = 2192.38 × (1 − 0.1785) − 18, 102.93 × 0.1008 = −23.02 EVA ENTITY 2018 = 2498.05 × (1 − 0.1774) − 235.70 × 13.873 = −1, 214.99(14) …”