Aaltodoc publication archive (Aalto University institutional repository)
School of Business | Department of Finance | Finance | 2016
Thesis number: 14744
Industry effect on capital structure decisions: predictors of capital structure and determinants of financing decisions in European listed companies in 1999-2013
|Title:||Industry effect on capital structure decisions: predictors of capital structure and determinants of financing decisions in European listed companies in 1999-2013|
|Year:||2016 Language: eng|
|Department:||Department of Finance|
|Index terms:||rahoitus; pääoma; yritykset; velat|
|Key terms:||Capital structure, industry capital structure, median leverage, leverage decisions, capital structure determinants|
This thesis examines the reliable predictors of capital structure and the key determinants behind changes in companies' capital structures. The aim is to increase the understanding of the impact of industry median capital structure on companies' observed capital structures and in their decisions to alter their capital structure. Earlier research in the field has concentrated on identifying reliable predictors of capital structure and assessing theories behind observed capital structures. Another research direction has focused on explaining the timing of debt and equity issues with market conditions. In addition, theories of behavioral finance and peer pressure have been used to explain companies' capital structure decisions. This thesis builds on all of these directions of research.
In the empirical part two linear regression models have been developed. The first one is used to assess the reliable predictors of capital structure with the industry median leverage as the key independent variable. In the second regression model, determinants of changes in companies' capital structures are investigated. The key independent variable is a measure of a company's leverage compared to the median leverage within the industry at the end of previous fiscal year.
A total of 1380 European publicly listed companies have been studied during the period of 1999-2013. Companies have been divided into industry (peer) groups based on Fama-French industry classification. The analysis has been done for the full sample and separately for companies that are either under- or over-levered within an industry, and for companies that have been defined as financially constrained. Three criteria have been used to divide the sample into financially constrained and non-constrained groups: firm size, bond ratings and operating cash flow volatility.
I find that industry median leverage is a reliable predictor of company leverage. The regression coefficient of 0.5-0.6 between observed leverage and industry median leverage has both economic and statistical importance (at 99% confidence level). The results are similar for financial leverage and total liabilities to assets. I also find that the difference between the industry median leverage and a company's leverage (distance to median) is an important driver in changes of capital structure with a coefficient of 0.05-0.06 to change in leverage at 99% confidence level for the full sample. This applies especially to companies that deviate significantly from the industry median. The impact is stronger for companies that are highly levered compared to those that are closer to the median and especially to those that are below the industry median. For high leverage companies the regression coefficient can be between 0.1-0.5 meaning that a 10% distance to median leverage would lead to reduction of 1-5% in leverage in the following fiscal period. I also find some support for the hypothesis that the impact of industry leverage is stronger for financially constrained companies.
Master's theses are stored at Learning Centre in Otaniemi.