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Arvanitis, Stavros H.
Tzigkounaki, Irakleia S.
Stamatopoulos, Theodoros V.
Thalassinos, Eleftherios I.
Year of Publication: 
[Journal:] International Journal of Economic Sciences and Applied Research [ISSN:] 1791-3373 [Volume:] 5 [Year:] 2012 [Issue:] 3 [Pages:] 33-63
The issue of capital structure of companies is one of the most debated problems of financial management. According to economic theory, capital structure determines the stock market value of firms and therefore their viability, while one of the most negative result of the crash of 2008 and the persisting crisis (excess supply in markets of labor and money) is their ongoing steep decline of lending by credit institutions and other sources. In this paper, considering the importance of the issue and motivated by the conflicting results of previous empirical studies, we attempt the analysis of capital structure of the European Maritime Enterprises (oceanic shipping). We focus on shipping companies, because of the large volume of funding that demands their main operation, due to the intensity of the assets held. The objectives of this research are firstly the identification of factors that affect the capital structure of European oceanic shipping and secondly to search for the existence of an ideal - target capital structure ratio. The determinants of capital structure are examined through static (fixed effect method and FGLS) and dynamic (GMM Methods) econometric models, using data from the financial statements of 32 listed European shipping companies for the period 2005-2010. The results suggest the prevalence of pecking order theory in our case, while a positive relationship arises between tangible assets and tax benefits (arising from sources other than borrowing) against leverage. Moreover, we observe a negative relationship between size or profitability and debt. Our findings contribute to a deeper understanding of the decisions taken by European shipping on their capital structure.
Capital Structure
Trade-off Theory
Pecking Order Theory
Dynamic Panel Data
Shipping companies
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