An integrated model of capital structure to study the differences in the speed of adjustment to target corporate debt maturity among developed countries

Abstract

Abstract:In this paper, we propose an integrated model of capital structure to study the partial adjustment process to the optimal long term debt ratio. In our analysis, we consider the characteristics of the institutional environment as a factor that influences such adjustment. We use a sample of quoted firms from Germany, Denmark, Spain, Italy, USA, Australia, Belgium, UK and France for the period 1996-2008. The key findings are that the firms follow optimal long-term debt ratios. Such optimal ratios are determined by firm characteristics identified in the trade-off, pecking order and market timing theories and by the country institutional environment. We observe that in those countries with lower cost of adjustment, essentially in those where banks are the main source of funds, firms can reach their target debt ratio in half the time needed by those countries with higher adjustment costs.

Bank-Specific and Macroeconomic Determinants of Profitability: A Revisit of Pakistani Banking Sector under Dynamic Panel Data Approach

“…The organisation can measure profitability through a wide range of financial ratios. The most manifesting ratios as envisaged from prior literature are the return on assets, return on equity, net interest margin and return on investment (Flamini et al 2009;Naceur and Goaied 2008;Vallelado and Saona 2011). The research scholars have been interested in determining the impacts of the macro or microeconomic factors to increase the profitability levels.…”

Intra- and extra-bank determinants of Latin American Banks' profitability

“…In addition to the extra-bank determinants already described here, we used an alternative set of variables similar to those used in Vallelado and Saona (2011), such as: growth rate of GDP (GDP); total bank deposits (BANKDEP) (defined as the demand, time and saving deposits in deposit-taking banks as a share of GDP); foreign banks (FOREIGNBANK); cost income ratio (CIR) (which is the total cost as a share of total income of all commercial banks); and the stock market turnover ratio (STOCKMKTO) (which is the value of total shares traded to average market capitalization). The source of this information was the updated dataset gathered by Beck et al (2000).…”

Capital structure speed of adjustment heterogeneity across zero leverage and leveraged European firms

“…De Miguel and Pindado (2001), Ozkan (2001) and Gaud et al (2005), for Europe, Flannery and Rangan (2006), Huang and Ritter (2009) and Lemmon et al (2008), for the USA, and Antoniou et al (2008), for G5 countries, are examples of the first studies using dynamic panel data models in this context, all of them confirming that firms actively adjust to a target, although at different rates. Recent examples of studies that, like ours, focussed on European listed firms, are Vallelado and Saona (2011) and Castro et al (2016), both of which estimated their dynamic panel data models using GMM. The former authors examined the target long-term debt ratio, finding that country institutional environment plays a determinant role on long-term debt target behaviour, while the latter focussed on differences in target leverage and SOA across three firms' life cycle stages (introduction, growth and maturity), concluding that the SOA does not increase as the firms evolve over the life cycle, with firms in the introduction cycle adjusting the fastest.…”

“…Firm's financing decisions are also determined by the country's specific characteristics, with another stream of the literature investigating whether differences in SOA can be explained by variations in countries' legal, institutional and financial environments (e. g. Antoniou et al, 2008;Vallelado and Saona, 2011). Öztekin and Flannery (2012), resorting to a sample of 37 countries, and Drobetz et al (2015), using a sample of G7 countries, found that firms in countries with market-based financial systems, or with more developed financial systems, adjust faster due to lower transaction costs.…”