The difference in firm performance between male and female CEO’s of S&P 500 companies

The difference in firm performance between male and female CEO’s of S&P 500 companies.

Name: Maria Tuaeva Student number: 10732543 Supervisor: Ieva Sakalauskaite

Economie en Bedrijfskunde Track: Financiering & Organisatie

Abstract

With a rising interest in female representation in companies, a growing amount of papers on the topic appear. Just little research has been done on the effect of female CEO’s on firm performance. This paper therefore examines whether there is a difference in firm performance between firms with male CEO’s and firms with female CEO’s. A sample with annual data from 386 S&P 500 companies is used for the period 2008-2016. I have used the Tobin’s Q and the Return on Assets as performance measures. The ordinary least squares model and the fixed effects model are used to investigate the effect of female CEO’s on firm performance. When the Return on Assets is not controlled for, a significant effect is found between female CEO’s and the Tobin’s Q. Further results show no evidence for a difference in firm performance between male and female CEO’s, for both the Tobin’s Q and the Return on Assets. I did find female CEO’s to have a positive effect on the Tobin’s Q and to have a negative effect on the Return on Assets, but both effects are insignificant. Possible reasons for insignificance are discussed.

Statement of Originality

This document is written by student Maria Tuaeva, who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document are original and that no sources other than those mentioned in the text and its references

have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

Table of contents

1.INTRODUCTION 4

2.LITERATURE REVIEW 4

2.1 POSITIVE EFFECT OF FEMALE REPRESENTATION 4

2.2 NEGATIVE EFFECT OF FEMALE REPRESENTAION 6

2.3 NO EFFECT OF FEMALE REPRESENTATION 7

3. EMPIRICAL ANALYSIS 8

3.1 SAMPLE SELECTION 8

3.2RESEARCH DESIGN 8

3.3 DESCRIPTIVE STATISTICS 9

4.EMPIRICAL RESULTS AND DISCUSSION 9

4.1 EMPIRICAL RESULTS 9

4.2 DISCUSSION 11

5.CONCLUSION 12

BIBLIOGRAPHY 14

1. Introduction

With a growing amount of female CEO´s, from 1,5% in 2005 to 7% in 2016, there is also a rising interest in female representation in corporates among researchers (Huang and Kisgen, 2013; Mosbergen, 2016). Examining female influences on firm performance is important to get a better understanding in corporate behaviour (Huang and Kisgen, 2013). Research on female influences is also important because, although the number of female CEO’s is rising, female representation in corporates is not in comparison with female representation in the general population (Conyon and He, 2017). Several studies have found that female representation on the Board of Directors has a positive effect on firm performance (Adams and Ferreira, 2009; Bennouri et al., 2018; Conyon and He, 2017). While there is a fair amount of research on the effect a female director has on firm performance, there has not been a lot of research on the effect that female CEO´s have on firm performance. To contribute to existing research and to fill the knowledge gap, this study is going to examine whether there is a difference in firm performance between male and female CEO’s within the S&P 500 firms.

To research whether there is a difference between male and female led companies regarding the firm performance, a sample of 386 S&P 500 companies is collected. Since there is a significant rise in female CEO’s within the S&P 500, and also a significant amount of female CEO’s, these companies represent a good sample for this research. Of these 386 companies, 3455 observations were gathered from the period 1/1/2008 to 31/12/2016. This research uses Tobin’s Q and Return on Assets as measures of firm performance. Further, are the ordinary least squares model and the fixed effects model used to find evidence on whether there is a difference in firm performance between firms with a male CEO and firms with a female CEO within the S&P 500 firm.

In the second part of this paper relevant literature is discussed, additionally a hypothesis is formulated. In the third section the sample selection is further discussed and also the research design is further explained. Also the descriptive statistics are presented in the third section. In the fourth section the empirical results are being presented and discussed. Lastly the results are summarized and

concluded in the conclusion.

2. Literature review

2.1 Positive effect of female representation

Studies suggest that there are several reasons why women would increase firm performance when included in the Board of Directors. One reason being that women bring a different view and opinion to the discussion (Fondas and Sassalos, 2000). Other reasons being that women experience things

differently since they go through another socialization process than men. Furthermore, women have a tendency to be better prepared for meetings than men and literature states that women compliment men in directing, which allows are a balance within the companies (Hillman et al., 2007; Adams and Ferreira, 2009; Morrison et al., 2004). Chen and Gavious (2016) find that including one female in the

Board of Directors is a good move, but this is only the case for female directors with a finance education or background. They also find that one female director with financial literacy has a greater impact on earnings management than a male director with financial literacy. The data used to obtain these results consists of Israeli high-technology firms from the period 2003 till 2010, for this particular study the difference-in-difference analysis was used. Furthermore, research suggests that when males and females have similar responsibilities and the same level of work, like CEO’s, that the firm performance of different companies still will have the tendency to differ significantly (Du Rietz and Henrekson, 2000).

The difference in promoting corporate performance between men and women could also cause women to have a positive effect on firm performance. Carter et al. (2010) suggests that human capital is the reason that different genders or ethnicities have different influences of firm performance. Human capital is a person’s education, skills and experience, which can be used to the benefit of the company, which makes it the basis for leadership (Kesner, 1988). Due to the differences in human capital, between men and women, females have unique human capital (Carter et al., 2010). This so called unique human capital is different than the human capital of men and would suggest that men and women do have different effects on firm performance.

Studies on ethical behaviour suggest that women are more ethical than man. This is shown through the behaviour and judgements of males and females (Chen and Gavious, 2016). Since women are more ethical than man, they are probably more likely to report illegal acts within the firm (Vermeit & Van Kernhove, 2008). This would mean that the firm’s internal monitoring would be strengthened when there is a female board member. This would not only be the case for female board members but also for female CEO’s. The difference in ethical values would suggest that female CEO’s do have a different effect on firm performance than male CEO’s.

Huang and Kisgen (2013) find a difference in financial and corporate decisions between male and female executives. They find that the difference is caused by males being overconfident in comparison to females. Due to the overconfidence of men a better-than-average effect arises, which causes males and females to make different corporate decisions. For example, the overconfidence causes male executives to invest in more projects with a negative net present value than female executives do, which decreases firm performance measures such as Return on Assets. The

overconfidence of men also causes them to provide narrower earnings forecasts than females would provide. Moreover, men also have a higher likelihood to be removed from their position compared to their female counterparts. Another explanation for the differences, apart form the overconfidence of men, is the fact that females are more risk averse than males. However, Huang and Kisgen (2013) conclude in their paper that overconfidence is most in line with the evidence found in their research. The data set of Huang and Kisgen (2013) consists of CEO’s and CFO’s of which 116 were female executives. The CEO’s and CFO’s came from US companies with book assets higher than $500 million. Also, the company had to be listed on one of the following indices: NYSE, Amex or Nasdaq.

Huang and Kisgen (2013) chose for a difference-in-difference analysis to mitigate endogeneity issues. The instrumental variable approach is also used with ‘the state’s gender status equality value for each firm based on the firm’s headquarters locations’ being the instrument.

A similar study of Bennouri et al. (2018) studies the effect of female directors on firm performance. The performance measurers used are the Return on Assets, Return on Equity and the Tobin’s Q. Bennouri et al. found that female directors have a significant positive effect on the Return on Assets and the Return on Equity. In contrast, a significant negative relationship was found between the female directors and the Tobin’s Q. The sample of Bennouri et al. (2018) contains all the 511 firms from the French CAC All-shares index. The sample contains data from 2001 to 2010 and the

multivariate analysis was used to investigate the effects of female directors on firm performance. Sabatier (2015) studied French CAC40-listed companies to see whether female directors improve firm performance. The Return on Equity, Return on Assets and the Tobin’s Q are used as performance measures. It is interesting to look at French companies since in the studied period, 2008 till 2012, a law was passaged that installed a ‘women’s quota’. Now 40% of the Board of Directors of French companies have to consist of female directors by 2017. Due to this law the percentage of female directors was 28% in 2013, which was a 20-percentage points rise in six years’ time. To test whether female directors improve firm performance Sabatier (2015) uses two instrumental variables. The first instrument is ‘the fraction of female directors in connected boards’. The second instrument is ‘the variation in the pre-reform fraction of women in each board to account for temporal recurrence effects in gender diversity strategies’. Sabatier (2015) found that, in the short-term, female

representation in the Board of Directors does have a positive effect of firm performance.

2.2 Negative effect of female representation

On the other hand, female directors can be associated with negative effects on firm performance. Ahern and Dittmar (2012) find that the Tobin’s Q declined substantially due to female representation. This can be partially attributed to the fact that the data that was studied came from Norway where a ‘women’s quota’ has to be met by law. Ahern and Dittmar (2012) also conclude that this causes women to be hired not for their abilities but just to reach the quota. Furthermore, a quota ensures that women who are younger and less experienced than their male counterparts are hired, which causes them to underperform. The firms who had to adapt to reach the ‘women’s quota’ now have lower accounting returns. It has to be noted that the setting of the study does not allow for the identification of the different effects gender, experience and age could have on firm performance. Ahern and Dittmar (2012) used the instrumental variable approach. As an instrument ‘the pre-quota

representation of female directors’ is used to see what the effect of the quota on the Tobin’s Q is. The study found that implementing a ‘women’s quota’ could decrease firm performance for firms with strong governance, although a positive effect on firm performance is found for firms which have weak governance (Adams and Ferreira, 2009). One reason could be that this is due to over-monitoring,

which will cause female directors to have a negative effect on firm performance. Adams and Ferreira (2009) use a dataset of US companies from the S&P 500, S&P midcaps and the S&P smallcap from the period 1996 until 2003. The performance measures used are the Tobin’s Q and the Return on Assets to see if gender diversity has a positive effect of firm performance.

2.3 No effect of female representation

There are also studies that suggest female executives will not have any effect on firm performance. One theory being that for a CEO to be hired he or she needs a specific set of skills and characteristics, despite of their gender (Huang and Kisgen, 2013). Since male and female CEO’s will have a similar set of skills a significant difference in firm performance between them is not to be expected. Carter et al. (2010) concluded that gender diversity on the Board of Directors did not have any effect on the Tobin’s Q. A sample of S&P 500 companies was used for the period 1998-2002. Carter et al. (2010) used both the ordinary least squares model and the three stage least squares model with firm and time fixed effects to study whether the number of female directors had any effect on firm performance. For the three stage least squares the lagged value of the Tobin’s Q was used as instrument.

Another study finds that female CEO’s do not have effect on financial performance. The data used to conclude this consists of US small and medium-sized service businesses. Further, a

multivariate analysis of covariance was preformed, to see whether female CEO’s effect financial performance (Davis et al., 2010). After performing the analysis the authors found, that although female CEO’s do have a slightly higher financial performance, there is not enough statistical evidence to say that female CEO’s have any effect on financial performance.

Reasons for the mixed findings between the different studies could be the differences in empirical specifications and methodologies (Conyon and He, 2017). It can also be caused due to omitted variables or different time horizons (Conyon and He, 2017). Furthermore, it has to be kept in mind that females are not perfectly randomly selected as CEO (Huang and Kisgen, 2013). This can cause the female variable to be endogenous (Conyon and He, 2017).

Based on the past findings I expect the following hypotheses:

Hypotheses 1: Female CEO’s do have a significant positive effect on firm performance, ceteris

paribus. (1)

Since studies where a negative effect between female directors and firm performance is found, deal with ‘women’s quota’ and the US does not have any quotas this contributes to excluding a negative effect from the hypotheses. Also looking to the study of Huang and Kisgen (2013), which has a similar sample and finds a positive effect on financial and corporate decisions, contributes to

3. Empirical analysis 3.1 Sample

To study the effects of female CEO on firm performance, I use a sample of S&P500 firms during the period 2008-2016. The companies that are in the S&P 500 and the data on female CEO’s are retrieved from Orbis. Compustat provided the data on total assets, total leverage, market value, net income and the 3-digit SIC code of all the companies. After all the eliminations on missing data were done, 3455 observations were left of 386 S&P 500 companies.

3.2 Research design

To find out whether the hypothesis stated in the literature review is true, I estimate the following model:

𝑇𝑄 = ß0 + ß1 ∗ 𝐹𝑒𝑚𝑎𝑙𝑒 + ß2 ∗ 𝑅𝑜𝐴 + ß3 ∗ 𝑆𝑖𝑧𝑒 + ß4 ∗ 𝐿𝑒𝑣𝑒𝑟𝑎𝑔𝑒 + 𝛾𝑌𝑒𝑎𝑟 + 𝛿𝑆𝐼𝐶 (1) Where the dependent variable TQ stands for Tobin’s Q, calculated as the ratio of firm market value to total assets. I followed existing literature and therefore use the Tobin’s Q as a measure of firm performance. The Tobin’s Q shows what the expectations of the market are about future earnings of the firm since it is a market-based performance measure (Sabatier, 2015). Accounting influences therefore have little effect on the Tobin’s Q in contrast to accounting based measures as Return of Assets or Return of Equity (Bennouri et al., 2018). The female dummy is the key variable of interest and takes value one when the company has a female CEO and zero if otherwise.

In regressions, I control for the firm’s Return on Assets (RoA), which is defined as net income divided by total assets. The Return on Assets is used to control since it is an accounting based performance measure instead of a market based performance measure as the Tobin’s Q is. The proxy used for size is the natural logarithm of the total assets since this is the proxy mostly used in existing literature. Lastly leverage stands for total liabilities divided by total assets and it shows whether the company can meet their financial obligations. I also control for fixed year effects to control for firm characteristics that can influence performance measures over time (Sabatier, 2015). For example CEO transitions, as a male-to-female transition, are now included. Fixed industry effects are also being controlled because this allows for the differences between industries be taken into account (Carter et al., 2010). Using fixed effects thus helps to point out unobserved changes over time and to temper omitted variables (Carter et al., 2010). Also by using fixed effects it can be estimated how the Tobin’s Q changes on average. Furthermore, the model is corrected for robustness.

I did several regressions. In a two regressions the Return on Assets is used as dependent variable instead of the Tobin’s Q. This is done because, as above mentioned, Return on Assets is an accounting based measure in contrast to the Tobin’s Q. The Return on Assets is thus based on present firm performance while the Tobin’s Q is based on the expectations the market has of firm performance (Sabatier, 2015). In two other regressions the control variable Return on Assets is removed to see what the effect now would be of the female dummy on the Tobin’s Q. This is also done to see if the results

without the Return on Assets would differ significantly from the results with the Return on Assets. In order to prove the formulated hypotheses the beta of the female dummy variable needs to be bigger than 1.

3.3 Descriptive statistics

In table 1 the descriptive statistics of the sample are presented. The average of the Tobin’s Q is 1.46, has a minimum of 0 and a maximum of 20.09. Furthermore, the average of the Return on Assets is 0.06, has a minimum of -1.23 and a maximum of 0.77. In table 2 it is shown that the biggest correlation is between the variables Tobin’s Q and Return on Assets, which is to be expected since they are both performance measures. Table 2 also shows that there is no multicollinearity between any of the variables.

Table 1: descriptive statistics

Variable Obs Mean Std. Dev. Min Max

Female 3456 0.0411 0.1985 0 1 Tobin’s Q 3456 1.4586 1.3421 0 20.0927 RoA 3456 0.0607 0.0835 -1.2270 0.7691 Leverage 3456 0.6137 0.2089 0 2.0325 Size 3456 9.5817 1.3574 5.4484 14.7606 Table 2: correlation

Female Tobin’s Q RoA Leverage Size Total assets Female 1 Tobin’s Q -0.0152 1 RoA 0.0046 0.3518 1 Leverage 0.1160 -0.2833 -0.2627 1 Size 0.1611 -0.4528 -0.1446 0.2954 1 Total assets 0.1758 -0.1639 -0.0823 0.1797 0.5321 1

4. Empirical results and discussion 4.1 Empirical results

I did several regressions to investigate whether there is a difference in firm performance between firms with male and female CEO’s. The results can be found in table 3.

I performed both the ordinary least squares model and the fixed effect model. I used both to see if a female CEO has a different effect on firm performance when not controlled for year or industry effects. Although using fixed effects has some advantages, the amount of CEO transitions can be low so it could be interesting to also look to the ordinary least squares model. As can be seen in table 3,

columns 1 and 2, the beta’s of the female dummy are positive which indicates that female CEO’s have a slightly higher effect on the Tobin’s Q than male CEO’s. The beta of the female dummy for the ordinary least squares model is slightly higher than the beta of the female dummy of the fixed effects model. But for both regressions the variable of interest, the female dummy, is insignificant. So in this case there is not enough statistical evidence to support the hypotheses.

After the first two regressions, two other regressions were made. The results of these regressions can be found in columns 3 and 4 of table 3. Again, the ordinary least squares model and the fixed effects model are being regressed but now one control variable is removed, namely the Return on Assets. When examining the ordinary least squares model in column 4 it is shown that the beta of the female dummy now is significant at a significance level of 1%. This gives enough statistical evidence to support the hypotheses. However, when fixed effects are controlled for, which is shown in column 3, the beta of the variable of interest is insignificant and this therefore does not support the hypotheses.

Lastly, two regressions were done with the Return on Assets as dependent variable instead of the Tobin’s Q. The results can be found in columns 5 and 6 of table 3. In the results it is shown that the beta of the female dummy for both the ordinary least squares model and the fixed effects model is insignificant. So again there is not enough statistical evidence to support the hypotheses. Also, the beta’s are both negative in contrast to the other four regressions. The negative beta’s indicate that female CEO’s have a slightly lower effect on the Return on Assets than males.

The control variables are in general significant at 1%. This is not the case for Size in columns 5 and 6, where the control variable is not significant. This is also not the case for Leverage in column 1, which is significant at 5%.

Table 3: regression output TQ FE (1) TQ OLS (2) TQ FE (3) TQ OLS (4) RoA FE (5) RoA OLS (6) Female 0.0132 (0.1088) 0.0379 (0.1039) 0.0296 (0.1116) 0.3894*** (0.1160) -0.0071 (0.0072) -0.0003 (0.0058) RoA 2.0886*** (0.6045) 2.1559*** (0.5802) Leverage -0.9646** (0.4259) -0.9071*** (0.3104) -1.2818*** (0.4165) -0.9922*** (0.3745) -0.1855*** (0.0417) -0.1605*** (0.0365) Size -0.3524*** (0.0908) -0.3789*** (0.0514) -0.3842*** (0.0530) -0.1268*** (0.0432) -0.0095 (0.0099) 0.0006 (0.0043) Constant 4.8230*** (0.8288) 5.9441*** (0.5541) 6.3835*** (0.5622) 3.2646*** (0.3671) 0.2515*** (0.0843) 0.1677*** (0.0340)

Year fixed effects Yes No Yes No Yes No

Industry fixed effects

Yes No Yes No Yes No

N 3455 3455 3455 3455 3455 3455

Notes: This table shows the results of the regressions of equation 1. The numbers in the table stand for the beta’s of the variables. The numbers found between the brackets are the standard errors. N is the amount of observations.

*p<0.1 **p<0.5 ***p<0.01

4.2 Discussion

The key variable of interest, the female dummy, mostly turned out to be insignificant and therefore not providing enough evidence to confirm the formulated hypotheses. This was only not the case for the female variable of the ordinary least squares model in column 4 where significance at 1% was found. The insignificance that was most often found could have several reasons. One reason could be that in the existing literature, where a positive effect is found, just a subset of corporate decisions that executives have to make is being studied (Huang and Kisgen, 2013). When the studied subset of corporate decisions are specifically the subset of corporate decisions where women outperform men, this indeed would give the idea that female CEO’s also would have a significant effect on firm performance compared to male CEO’s. But if men outperform women in other subsets of corporate decisions, that are not being studied, it would balance out the different effects on firm performance. As already mentioned another reason for the found insignificance could be that for a person to be hired as CEO, he or she needs certain types of skill sets or characteristics so no difference would be found (Huang and Kisgen, 2013). Also the endogeneity of the female dummy could be the reason of

the insignificance found (Conyon and He, 2017). There are several factors that can cause the female dummy to be endogenous. Boards that discriminate on gender, for example to reach a quota, can cause the sample to not be random. This would cause the external validity to decrease since the sample would not be representative for the general population. Another reason could be that when women themselves choose to work for a specific industry or companies that are different, endogeneity can be caused (Huang and Kisgen, 2013). For example when women mostly choose to work for an industry with an on average higher Return on Assets, this would give the wrong indication of the effect of female CEO’s on firm performance.

Further research could solve the endogeneity problem by using the instrumental variable

approach. By using the two stage least squares model the endogeneity of the variable of interest would be taken care of, which would give more useful results. Several studies already use methods in the instrumental framework to find whether there is a difference in firm performance between male and female board members. A good next step would be to do this to see if there is a difference in firm performance between firms with male CEO’s and firms with female CEO’s. Another way of solving the endogeneity problem would be to use the difference-in-difference empirical framework. There are several advantages the difference-in-difference has compared to the fixed effects model, for example that the CEO needs to have had the position for a significant amount of time. The difference-in-difference analysis also cancels out uncommon effects of CEO transitions and decreases the noise from observations that are outdated. To expand existing literature specific industries or other countries than the US could be studied.

5. Conclusion

With a growing amount of female CEO’s comes a growing amount of interest in the female CEO’s effect on firm performance. Although the amount of female representation in corporates is growing, it is not yet in line with female representation in the general population. A great deal of literature shows a positive effect of female directors on firm performance. The existing literature that finds a negative effect of female directors on firm performance in general have samples that have to deal with a ‘women’s quota’.

Instead of examining the effect of female directors on firm performance, this paper studied the effect that female CEO’s have on firm performance in comparison to their male counterparts. I did this for S&P 500 companies for the period 2008-2016. This study used as performance measures the Tobin’s Q and the Return on Assets to study the effect of female CEO’s on firm performance. There was not enough statistical evidence found to support the hypotheses that female CEO’s do have a significant positive effect on firm performance but for one exception. Furthermore, the female dummy has a slight positive effect on the Tobin’s Q while it has a slight negative effect on the Return on Assets. Both effects are insignificant.

The mixed results could be caused by the endogeneity of the variable of interest but this has to confirmed in further research. Further research can solve the problem of endogeneity by using the instrumental variable framework or the difference-in-difference analyses. Also due to the sample not being perfectly random the external validity of this study decreases. Several countries could be studied and compared in further research to ensure external validity. This study concludes that there is no statistical evidence to proof that there is a difference between the effects that male and female CEO’s have on firm performance.

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