Excerpt
Table of content
Table of content
List of figures
1 Introduction
2 Literature Review
3 Case Study
4 Conclusion
References
Appendix
List of figures
Figure 1: Overview of case study results
1 Introduction
The literature has covered the topic of how gender affects corporate financial decisions and risk taking with various articles. However, researchers have not come to a clear decision whether gender positively affects the previously stated points or not. Besides that, no research article has looked at data newer than 2010. So far, the literature has examined companies in the USA from 1992 to 2004 (Khan and Vieito, 2013), from 1993 to 2005 (Huang and Kisgen, 2012) and from 1996 to 2010 (Sila, Gonzalez and Hagendorff, 2015) as well as in Europe from 1999 to 2009 (Faccio, Marchica and Mura, 2016). Nelson (2016) used data from two prior articles to conduct her statistical analysis.
Hence, this essay aims at clarifying what effect gender has and at using more recent data, especially to include data from around and after the financial crisis of 2007/08. This essay tries to fill that gap by conducting a case study on EasyJet and comparing it to its peer Ryanair. EasyJet had a transition from male to female CEO in 2010. The case study retrieves data about these two companies, which comes from the years 2005 to 2015 and calculates ratios, regressions and averages. Further, it compares the averages before and after the transition within EasyJet and also against the peer company.
Findings are that risk taking with a female CEO has become less on an overall average. With a female CEO, the company has a higher return on assets and decreases the number of outstanding shares faster. But a male CEO leads to a lower Beta and standard deviation as well as a higher average return of shares on the stock market, hence a clear decision on the overall improvement on financial decision making cannot be made.
The essay is structured as follows. Section 2 covers the literature review, Section 3 develops and conducts a case study and Section 4 finishes the essay with a conclusion.
2 Literature Review
As previously written, research has not found a clear answer on whether women have a positive or negative effect on risk taking and corporate financial decisions. On the one hand Faccio, Marchica and Mura (2016) state that companies headed by female CEO’s are more likely to survive compared to similar companies, use lower leverage and have more constant earnings and hence women take less risk. Additionally, return on assets of companies managed by female CEO’s is higher than of companies managed by male CEO’s and compensation for female CEO’s is more risk-averse than for male CEO’s (Khan and Vieito, 2013). Further, male executives are relatively more overconfident than female executives (Huang and Kisgen, 2012), which leads to more risk taking among men.
On the other hand, Nelson (2016) finds that on an individual basis there is no correlation between gender and risk taking and hence stereotyping risk-aversion with female gender is not possible, not even on an aggregate level. Besides that, Sila, Gonzalez and Hagendorff (2015) cannot find any evidence that females on boards lower companies risk taking. Further, their study points out that boards with a high proportion of females are less likely to appoint more female directors and that it is more probable, that women replace each other in those positions. Besides this, female CEO’s do not allocate capital as good as their male counterparts (Faccio, Marchia and Mura, 2016).
Hence, per these authors the literature is leaning slightly towards the assumption that women in CEO or directing positions have a positive impact on risk taking and corporate financial decisions.
The difference in results is based on different methods, assumptions and data used by the previously named researchers. Khan and Vieito (2013) use CEO compensation, return on assets and share price volatility as their dependent variable to measure how risky the companies themselves are. Faccio, Marchica and Mura (2016) use some similar ratios such as return on assets, but they emphasize more on ratios which reflect risk taking and financial decision making of the CEO’s by using ratios like leverage, value-added growth and marginal Q. This approach answers the question asked by this essay better as it is looking more for risk taking of people, who are in leading positions, rather than for how risky the companies themselves are.
In more detail, Faccio, Marchica and Mura (2016) first compare only companies with a transition from male to female CEO or vice versa to eliminate any influence from cross-sectional correlation. Next, they compare companies with a transition to peer companies without a transition to exclude any external factors such as country or year. Their approach is valid and it has been used in a similar way by Huang and Kisgen (2012), but it is not possible to exclude all external factors. Some external factors are time and company specific and will therefore not be eliminated by this approach.
Huang and Kisgen (2012) use similar ratios and calculations as well as a similar approach in parts as Faccio, Marchica and Mura (2016), but they use data from the USA instead of data from Europe. Furthermore, they analyse effects of announcements for corporate decisions on the share price and how gender affects financial forecasting. But impacts of announcements on the share price do not necessarily imply that the CEO is taking more risk or making different financial decisions. It is the view of the outside world or of shareholders and they might not have all information or might just think differently. Forecasting in general is difficult as future is uncertain. Hence, the results of their analysis can show a difference between gender, but they should be considered carefully as they are based on forecasts of the management.
Nelson’s (2016) approach differentiates between an individual and an aggregate level. She argues that on an individual basis results are different to an aggregate basis since patterns that lead to the results of women being risk averse on an aggregate level do not exist on individual basis. This is a good point, but it is certain that if you compare one random male CEO to one random female CEO, the female CEO might be more risk loving and vice versa.
In contrast to observing CEO’s, Sila, Gonzalez and Hagendorff (2015) look at how gender diversity of boards has an influence on a company’s risk taking and financial decision making. They use similar ratios and calculations as Huang and Kisgen (2012) but they relate those only to the boards composition. Boards serve the purpose of leading companies in their strategy, represent shareholders and supervise senior management, whereas CEOs are responsible for day to day business. As boards serve a different purpose, they do not directly control the risk taking and financial decision making, but indirectly, by deciding on main topics such as risk management, investments and major human resources, which include the CEO. Indirect influence and that boards consist of several members, which all have different responsibilities and hence do not all impact risk taking and financial decision making, lead to boards composition not being as important as CEO gender in terms of risk taking. This is reflected by the results of Sila, Gonzalez and Hagendorff (2015), which state that gender diversity on boards does not lower risk taking.
As written in the introduction, all researchers have used data from different time- frames and geographic backgrounds. An interesting point is, that only Sila, Gonzalez and Hagendorff (2015) have included data which covers and reaches beyond the financial crisis of 2007/08 and they conclude, that women do not have a positive impact on their company’s risk taking. Thus, the financial crisis might have an external impact on the data and findings.
3 Case Study
EasyJet has been chosen as the company with a transition from male to female CEO. The transition took place in July 2010 and hence enough time for change after the transition is given. The peer company is Ryanair. It has its male CEO since 1994 and both companies operate in the budget airline market. Ryanair as well as EasyJet only operate the European market, but EasyJet is based in the UK and Ryanair in Ireland. Still, as both have an identical market, it is a good pair for comparison to filter out external factors.
The case study is set up to find correlations between two main points. It compares EasyJet with itself before and after the transition from male to female CEO. Then it has a look at how EasyJet has performed in comparison to its peer Ryanair as well as to the market, which is the FTSE 350, to calculate Beta. The comparison to its peer is necessary to make sure that external factors like the financial crisis in 2007/2008 are not the only reasons for a better or worse risk taking. The approach used is similar to Faccio, Marchica and Mura (2016).
The data has been collected for the years 2005 to 2015 in order to grasp the same time frame before and after the transition and has been taken of Bloomberg. The data needed for this case study involves operating income, sales, interest expenses, longterm debt, equity, total assets, number of outstanding shares as well as the share price or index development for both companies and the FTSE 350. Besides that, it includes data from before and after the financial crisis to show general effects of the crisis and its outcome (see Appendices 8 - 14).
All results of calculations and regressions are presented in the same manner. Firstly, each figure is listed yearly according to the time-frame from 2005 to 2015. Than the average of all figures before and in as well as after 2010 (year of transition) are calculated to show the overall difference caused by the transition. To evaluate risk taking, the following ratios are used. First, operating gearing (see Appendix 1), which is the change in operating income divided by change in sales. It represents how much fixed compared to variable costs a company has and higher fixed costs result in higher risk (Pike, Neale and Linsley, 2015). Secondly, income gearing is calculated by dividing interest expenses by operating income (see Appendix 2). Hence, it shows how interest expenses are absorbed by income. The higher income gearing is, the higher is the risk for the company (Pike, Neale and Linsley, 2015). Another measure for risk taking is capital gearing (Faccio, Marchica and Mura, 2016). It is calculated by dividing long-term liabilities by the sum of equity and long-term liabilities (see Appendix 3). Capital gearing gives insight on the capital structure of a company and a higher gearing leads to higher risk. Thus, capital gearing can be used to measure risk taking and also financial decision making.
Furthermore, the impact of a female CEO on share returns, which gives a view on how shareholders perceive risk taking and financial decisions is examined. If shareholders think that too much risk is involved or that management is making bad decisions, the share price will fall. In this case a regression analysis of the day to day change of share and index price has been done to calculate Beta, standard deviation and average return for each year (see Appendix 4 and 5) (Sila, Gonzalez and Hagendorff, 2015).
The usage and origin of capital are the key questions in financial decision making. Therefore, it is assessed by looking at the development of number of shares outstanding or frequency of equity issuance as this visualizes how the company has obtained some of their funds (see Appendix 6) (Huang and Kisgen, 2012). Equity is usually more expensive than liabilities and hence a lower proportion, to a certain extent, of equity is good for the company and its shareholders. Therefore, a decrease of number of shares outstanding is favourable. Besides that, capital gearing is another measurement for from where capital is obtained. A lower gearing leads to lower risk, but it is preferable to obtain some funds through liabilities as they are cheaper than equity. Furthermore, financial decision making is measured by the return on assets (Khan and Vieito, 2013). This ratio shows how much return per assets has been made. Hence, it illustrates the profitability of investments that have been done and how capital has been allocated (see Appendix 7).
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Figure 1: Overview of case study results
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