MSc Finance Thesis
An Empirical Study on the Performance of Family Firms Listed on
the Amsterdam Stock Exchange
Student number: S3524981 Last name: Van Tienen First name: Mathijs
Email address: M.van.tienen@student.rug.nl
1
Introduction
The purpose of my research is to examine how family firms preform in relation to non-family firms. Family firms are unique because the family holds a large share in the company, although the family’s investment portfolio is poorly diversified. A family member or several family members often hold top management positions in the family firm which could lead to differences in performance compared to non-family firms. Some studies argue that family ownership increases the firm’s performance while others say there is no impact or even a negative effect on performance. Empirical evidence on a family firm’s performance isn’t unilateral, the goal of this research is to find more empirical evidence regarding performance of family firms to back related studies. Eventually investors can use this information to create portfolio’s that are more in line with their preferences.
In the studies of Anderson, Mansi, and Reeb (2003)Porta, Lopez-de-Silanes, and Shleifer (1999) is shown that family firms are common around the world. One-third of the S&P500 are family owned and in Europe the majority of public firms are under family control.
Anderson, Mansi, and Reeb (2003), Miller et al. (2007), Maury (2006) and Anderson and Reeb (2003) all performed an empirical study on the performance of family firms. These results are highly
sensitive to what the researcher defined as a family firm. The results of the three studies differ, in the fortune 1000 only lone founder firms outperform the other firms. At a lone founder firm the founder holds a major share in the firm and acts as CEO, there are no relatives active within the company. In the S&P500 family firms tend to outperform other non-family firms. This outperformance is at its best when the family holds up to 30% of the shares with a family member serving as CEO. Family firms in Western Europe outperform non-family organizations when the owners reduce the agency problem cost with active control. Passive family control typically will not effect performance. During this research, I did in-depth research on firms listed on the Amsterdam Stock Exchange to show if the assumptions made by other studies will hold in this region. This means that I compared the performance of listed family firms against listed non-family firms. The sample consist of all firms listed on the Amsterdam Stock Exchange excluding financial institutions and public utilities. I used the data from 1999 until 2018, and the performance will be measured using the return on assets (ROA), using earnings before interest taxes depreciation and amortization (EBITDA) as the return. To check for the robustness of the results, two other performance measurements were used. These are the annual percentage stock price change and Tobin’s q (James Tobin (1969)). The main research question of this study will be:
How do listed family firms perform compared to listed non-family firms?
Earlier studies also found a difference between the performance of young and old family firms. Anderson and Reeb (2003) distinguished between young firms, founded less than 50 years ago, and old firms which are founded more than 50 years ago. They found that young firms often have better performance due to the fact that the founding family was still present. To see if their assumption also holds for my sample, the sub-question for this research is:
How do young firms perform compared to old firms?
2
Literature review
In this chapter, I address the research questions. First I discuss three theoretical concepts that could influence the firm’s performance. Concentration of ownership, investment horizon and active management are the concepts that will be focused on. This will be followed by a summary of
previous empirical studies and the combination of these reviews will set the basis for my hypothesis.
Concentration of ownership
A common trait of the listed firms is the separation of ownership and control. Where most listed firms are held by many diversified shareholders, family firms are more often being held by one large undiversified shareholder. If in the last case the family has enough power and control, it could pursue private benefits at the cost of the firm. Fama and Jensen (1985) argue that the diversified
shareholder has different investment decisions rules than larger undiversified shareholder. The diversified shareholder wants to maximize the firm’s residual cash flow while the large undiversified shareholder might pursue other objectives then maximizing the value of the firm’s residual cashflow. Their objectives could be technological innovation, firm survival or organizational growth. The shareholder value of the firm could be lower when its hold by a large undiversified shareholder. This means that the performance measurements of a family firm could be lower than a non-family organization.
Family ownership and control can also increase the firm's value and performance. Demsetz and Lehn (1985)notes that concentrated investors have an incentive to minimize the agency cost and maximize firm value. In cases where the family's wealth is closely linked to the firm’s welfare, the incentives are enlarged. Families will benefit from close monitoring of management and thus minimize the freeride problem caused by managers. The family could be able to add value because the family can look further along the firm’s learning curve. This give the family a superior insight into the technology used in their firm. Their opinion is in line with Berle and Means (1932) who argue that ownership concentration reduces the agency problem. Based on these arguments family ownership should, theoretically, lead to a competitive advantage. The combined conclusion of these three papers is that family ownership should improve the firm’s performance in the long term. Although the family might pursue other objectives than shareholder value maximization these objectives will result in better performance in the future.
Investment horizon
Founding family’s will often hold a large stake in their firm for a long period of time. Therefore, the family has a longer investment horizon than other shareholders due to the fact they plan to keep their stake for generations. The papers of Stein (1989), James (1999) argued why the family’s longer investment horizon could lead to more efficient investment decision. The family firm is less likely to suffer from managerial myopia due to shareholders having longer investment horizon. Top
management position must be held by one or more family members in the family firm. Therefore managers are more likely to act on behalf of the shareholder, in fact some managers are
3
Active family management
In most studies a firm is only considered a family firm if one or multiple family members hold top management positions. Prior literature tells us that this could either benefit or harm the
organization. Anderson and Reeb (2003), Demsetz and Lehn (1985) both mention problems related to active family management. Active family management gives leadership the possibility to better align the firms interest with that of the family. The family could choose to pursuit personal goals through the organization, for example sponsorship deals which will not benefit the firm. A top manager will more likely be a family member if they want to reach the family’s consumption needs throughout the firm, instead of using the family’s wealth. Putting family members in top
management positions reduces the labour pool and thus more skilled manager could be excluded. In contrast, according to Anderson and Reeb (2003), Maury (2006), Davis, Schoorman, and
Donaldson (1997) active family management can also benefit the firm. A family CEO could bring skills to the table that outside managers don’t have. Suppliers or providers of capital are more likely to do business if firms have the same governing body for a long period of time. If a family member takes a top management position, he or she will keep the position longer than an outside manager. Active family management could decrease the agency conflict cost due to the fact the manager and principal are the same person or are related. The family manager would like to maximize the firm performance as he or she sees business performance as an extension of his/her wealth. Active family management has pro’s and contra’s, therefor it is hard to conclude what the effect will be on an active family management of the firm.
Empirical research
Recognizable research on the subject in Western-Europe is Maury (2006), he finds that active family control can lead to an increase in profitability. Active family control is defined as the family holding one of the top two management positions within the company. The findings of Maury (2006) differ to those of Maury (2006) and Villalonga and Amit (2006). Villalonga and Amit (2006) preformed a study on Fortune-500 firms. They found that family control only adds value if the founder acts as CEO or chairman of the board of directors, in addition to a non-family CEO. Their study is done on one-tier board structures in the United-states. According to Anderson and Reeb (2003) family firms, where the founding family is present, outperform non-family firms on ROA (return of assets) and market performance. Another major finding is that the relation between founding-family ownership and performance is not monotonic. Anderson and Reeb (2003) show that up to approximately 30% ownership will increase the firm’s performance, afterwards it will decrease. Miller et al. (2007) went deeper into the subject and found that the outperformance of family firms depends a lot of the definition of a family firm. In other researches, the ‘’lone founder’’ firms were defined as family firms. Lone founder’s firms are organizations like Microsoft who have no relatives of the founder in the company, only the lone founder is active in the firm. So when lone founder organizations are not treated as a family firm, they outperform the family firm. Lone founder firms are the superior performer against all other firms. An interesting finding was done by Morck, Shleifer, and Vishny (1988). Their paper has evidence that Tobin’s q is lower for firms where a descendant of the found family is in charge. The paper also suggest that young family firms should outperform older family firms.
Earlier studies on the relation between performance and ownership have used Tobin’s q, the ratio of the firm’s market value to the replacement cost of its assets. Another ratio that is commonly used is the return on assets (ROA). The ROA is measured using the earnings before interest, taxes,
4
Hypotheses
I can conclude from the literature review that family can add value to the firm. They add value by reducing the agency conflict cost, prolonging the investment horizon and acting out of altruism. In some cases, the family can have a negative effect on the firm’s performance. When the family seeks to keep active control, they will experience smaller labour pools for top management positions. Prior research also finds that the pursuit of personal interest from the family could decrease the firm’s performance. The empirical research shows that the positive effect exceeds the negative and thus family firms ultimately have a higher Tobin’s q and ROA. Therefore, the first hypothesis of this study is as follows:
Family firms outperform non-family firms
Family firms are passed along throughout generations. Equating that these firms have longer investment horizons which lead to an increase in performance, but descendants of the family could negatively effect performance if they find themselves in a leadership position. It’s common that young entrepreneurial firms will outperform similar, but older organizations. Lone founder firms are superior performers and can be categorized as young entrepreneurial firms. A firm is considered young if the date of inception is no more than 50 years ago. To see if this also holds for family firms, I will test the second hypothesis:
5
Methodology
Below I explain the methodology used to answer the research questions. With this methodology the hypothesises set in the literature review can be tested.
The sample
The sample will consist of all the listed firms on the AEX/AMX and AScX, excluding any financial institution and public utilities. Financial institutions and public utilities are bound to government regulations which could effect the firm performance. Therefore, they were excluded from the sample (Anderson and Reeb (2003)). The firms in the sample needed to be listed on the AEX,AMX or AScX at the end of 2018. The sample period will be from 1999 till 2018.
The method
Definition of a family firm
Miller et al. (2007) find that the results of a study are sensitive to the definition of a family firm. As each study uses a different definition there isn’t one clear definition. Miller et al. (2007) gives an overview of the different definitions used in 28 papers. Based on their findings I will adjust their definition of a family firm and clarify it with more restrictions. Miller et al. (2007), pp 836:’’We define a family firm as one in which multiple members of the same family are involved as major owners or managers, either contemporaneously or over time. This allows for a number of variations: in the level of ownership and voting control, in managerial role played by family members, and in family
generation of key family members.’’ Their definition is still rather vague. However, the definition for a family firm in this paper is as followed: The family has to hold 10% of shares as presented on Orbis to be considered a major owner and at least one member has to hold a top management position. To analyse which firms are family firms, the ownership status is needed and the holders the top leadership need to be known. For some of the younger firms, this is relatively easy as the founder is still the owner and the CEO, and other relatives hold the same family name. A problem might arise while analysing the older firms because after several generations family members might not hold the same family name. If this is unclear, I treat them as non-family members.
The model
The methodology used by Anderson and Reeb (2003) will be followed in this study.
The main interest of this study is to analyse the relationship between family ownership and firm performance. A two-way fixed-effect model is used for this regression. The dependent variable of the regression is the performance of the firm, measured with return on assets (ROA) using earnings before interest taxed depreciation and amortization (EBITDA) as the return, Tobin’s q and stock return. Prior literature suggests that family firms should have higher performance compared to non-family firms. The younger firms are expected to have a higher performance measurement then older ones, as it is more likely that in young firms the founding owner is still present who will add value to the company. (Anderson and Reeb (2003)). For the same reason, it is expected that younger firms are more often a family firm. The regression will contain year and industry dummies, see equation 1.
𝐹𝑖𝑟𝑚 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒
= 𝛿0+ 𝛿1(𝐹𝑎𝑚𝑖𝑙𝑦 𝐹𝑖𝑟𝑚) + +𝛿2(𝐹𝑎𝑚𝑖𝑙𝑦 𝐹𝑖𝑟𝑚#𝑌𝑜𝑢𝑛𝑔 𝐹𝑖𝑟𝑚)𝛿4−11(𝐶𝑜𝑛𝑡𝑟𝑜𝑙 𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒) + 𝛿12−48(𝑡𝑤𝑜 𝑑𝑖𝑔𝑖𝑡 𝑆𝐼𝐶) + 𝛿1999−2018(𝑌𝑒𝑎𝑟 𝐷𝑢𝑚𝑚𝑦 𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒𝑠) + 𝜀
6 Appendix A gives an overview of all the variables, they will also be explained in detail below.
Firm performance will be measured as ROA, Tobin’s q and stock returns. ROA will be measured as the
book value of the total assets divided by EBIDTA. Tobin’s q will be measured as shown in equation 2. This is similar to that of Maury (2006).
𝑇𝑜𝑏𝑖𝑛′𝑠 𝑞
= (𝑀𝑎𝑟𝑘𝑒𝑡 𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑐𝑜𝑚𝑚𝑜𝑛 𝑒𝑞𝑢𝑖𝑡𝑦 + 𝑏𝑜𝑜𝑘 𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑡𝑜𝑡𝑎𝑙 𝑎𝑠𝑠𝑒𝑡𝑠 − 𝑐𝑜𝑚𝑚𝑜𝑛 𝑒𝑞𝑢𝑖𝑡𝑦 − 𝑑𝑒𝑓𝑓𝑒𝑟𝑟𝑒𝑑 𝑡𝑎𝑥) / 𝑏𝑜𝑜𝑘 𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑡𝑜𝑡𝑎𝑙 𝑎𝑠𝑠𝑒𝑡𝑠
Equation 2
The stock return will be the annual percentage change in the share price. Three forms of firm performance will be used, ROA is an accounting measurement, Tobin’s Q is partly market based and partly accounting. The stock return is the market valuation of a firm. ROA will be the main variable for this study, the other two variables will be used to check for the robustness of the results. All of the data will be gathered from Eikon and is measured at the year-end.
Family firm will be measured using a binary variable that equals one when it’s a family firm and
otherwise zero. The main focus of this research is to find out if family firms have higher performance then non-family firms. Therefore, a binary variable is set for the family firm. The definition of family firm is that the family must hold at least 10% of the shares and a family member has to hold a top management position. I will use the latest data from Orbis which is from the end of 2018. Due to data and time limitation I won’t be able to compute this variable annually. This will not result in any problems, because if a firm is a family firm in 2018 it will have been a family firm in the past years as well. It might be happen that a firm was a family firm in the past and isn’t any more in 2018, although these are unique cases. Therefore it is unlikely that this will be the case for several firms in this sample.
Control variables will be measured the same as in Anderson and Reeb (2003). Officer holdings will be
measured as the percentage of shares held by a top management minus that of family top management. Officer holdings measures a governance mechanism, more holdings would mean higher involvement in the firm and theoretically a better firm performance.
Independent directors is a control variable that measures the percentage of independent board
members. One is considered an independent board member if he/she doesn’t hold any shares of the company. The total number of board members will be divided by number of independent board members. This will give a percentage that will be used as the control variable. The data for officer holdings and independent directors be gathered from Orbis and manually adjusted to fit these variables. The data used is from the year end of 2018 and is fixed for the whole sample period. Both variables are in place because corporate governance mechanisms can also influence the
organizations performance.
Unaffiliated blockholders are other large shareholders, who have at least a 5% stake in the firm and are not affiliated with the family. The variable blockholdings will be measured as the sum of shares of the unaffiliated block holders. In the presence of an unaffiliated blockholder, the control of the family could be substantially smaller.
7 The assumption of Modigliani and Miller (1958) is that the risk on the equity of a leveraged firm should be higher than that of a non-leveraged firm. In order to control for the assumption made by Modigliani and Miller (1958), the standard deviation of the stock returns for the past 60 months will be corrected with the leverage. I will use a simplified version of their model assuming that the volatility of debt is equal to zero. Therefore, risk will be measured as the equity divided by total book value of the assets multiplied by the standard deviation of the stock return for the past 60 months. The last control variables are to correct for size and age of the company. Log total assets will be measured as the natural logarithm of the market value in thousands. Log age will be measured as the natural logarithm of the firm’s age since inception.
It is expected that RD/TA and officer holdings have a positive association with the firm’s performance. Whereas Log total assets, D/TA, risk, log age and blockholdings have a negative association with the firm’s performance.
Two-digit SIC code will be measured using 1.0 for each industry to control for the industry effect. SIC
code 87 will be used as the base.
Year dummy variables will be measured using 1.0 for each year period from 2000 till 2018. 1999 will
be used as the base.
Young # Family will be measured by interacting the variables young and family firm. With this
interaction variable the four group, young family firm, old family firm, young non-family firm and old non-family firm can be analysed. It is expected that the firms age has a different effect on family firms then non-family firms, because family firms are passed along generations. Not interacting the variable could lead to insignificant values while interacted they could be significant. This interaction variables consist of two dummy variables meaning that only the intercept will change. The control variable Log age will be removed due to correlation.
Young firm will be measured as a binary variable which equals 1 if age < 50 years since inception and
otherwise 0. It is arbitrary of 50 years is long enough to test the effect of age. It is expected that as organizations grow older the family will have less contribution towards efficiency and productivity. Therefore it is likely that young firms show better performance (Maury (2006)). Anderson and Reeb (2003) describe that organizations led by younger entrepreneurs tend to perform better. This variable will only be used for the interaction with family firm.
8
Data collection
Moving forward the collected data will be analysed in this section, consisting of the descriptive statistics of the sample.
Sample descriptive statics
Table 1 shows in which SIC divisions the sample is active and the total percentage of family firms in the sample. It is interesting that in the Mining and Agriculture, Forestry and Fishing divisions no family firm is active. The wholesale trade seems to be dominated by family firms. In total the sample consists of 116 firms of which 38 are a family firm. Family firms make up 32% of the sample, which is in line with the studies of Anderson and Reeb (2003) and Maury (2006).
Range of SIC Codes Division Family firms
Non-Family firms
Percentage family firms
0100-0999 Agriculture, Forestry and Fishing 0 1 0%
1000-1499 Mining 0 7 0%
1500-1799 Construction 4 4 50%
2000-3999 Manufacturing 14 29 33%
4000-4999
Transportation, Communications,
Electric, Gas and Sanitary service 3 11 21%
5000-5199 Wholesale Trade 3 1 75%
5200-5999 Retail Trade 1 4 20%
6000-6799 Finance, Insurance and Real Estate 4 7 36%
7000-8999 Services 9 15 38%
Total 38 79 32%
Table 1
Number of family and Non-family firm by the SIC Divisions. (n=116)
Family firms refers to firms where a family holds 10% of the shares and a relative holds a top management position. Percentage of family firms is computed as the number of family firms divided by the total number of firms in the SIC Division
9 The sample consist mainly of well-established organizations, where the family firms are on average 56 years old and the average non-family firms are around 67 years old. The table shows that the minimum age in both groups is zero. The reason for this is that in both groups a firm had split up a division into a new firm which had a direct stock listing. A simple correlation matrix can be found in table 4. Family firm correlates negatively with ROA and stock return. This result is not in line with my earlier estimates, which suggested a positive relation. Family firm is positive related with Tobin’s q. In addition, some of the other variables do not correlate as expected and thus are different from other, similar conducted, studies. Earlier I expected that RD/TA and Officer holdings have a positive
association with the firm’s performance, whereas in these results both correlated negatively with ROA. Officer holdings also correlated negatively with Tobin’s q and stock return. RD/TA correlates positively with Tobin’s q and stock return. Other variables that didn’t behave as expected are total assets and age which have a positive correlation with ROA, whereas a negative correlation was hypothesized.
Variable Obs Mean Std.Dev. Min Max
1 ROA 1953 .068 .68 -17.667 4.492
2 Tobin’s q 1808 1.633 1.278 .194 19.828
3 Stock return 1953 .063 .465 -.987 7.273
4 D/TA 1953 .255 .276 0 8.453
5 RD/TA 1953 .022 .079 0 1.256
6 Total assets 1953 22.22e+07 46.7e+07 74 3.76e+08
7 Independent board members 1953 .895 .218 0 1 8 Officer holdings 1953 .011 .043 0 .339 9 Blockholdings 1953 .318 .232 0 .967 10 Age 1953 64.486 60.357 0 443 11 Risk 1789 .287 .361 -0.073 3.278 Table 2
Descriptive data of the full sample. (n=116)
The table presents the summary statistics of 116 firms listed on the Amsterdam Stock Exchange from 1999 until 2018. The variables ROA is measured as the EBIDTDA divided by the book value of the total assets. Tobin’s q is measured as the market value of common equity plus
the book value of total assets minus common equity and deferred tax all divided by the book value of total assets. Stock return is be measured as the annually percentage change in the stock price. RD/TA is measured as research & development costs divided by total book
value of the assets. D/TA is measured as total book value of debt divided by total book value of the assets. The total assets of a firm is measured as the total market value of the assets in thousands. Independent board members is measured as the percentage of board
members that doesn’t hold any shares. Officer holdings is the percentage of shares hold by top management excluding the family managers. Blockholdings is measured as the sum of the percentages held by unaffiliated shareholders that hold at least a 5% of the shares.
Table 3
Difference of means t-test. (n=116)
The table presents the summary statistics of 116 firms listed on the Amsterdam Stock Exchange from 1999 until 2018. The variables ROA is measured as the EBIDTDA divided by the book value of the total assets. Tobin’s q is measured as the market value of common equity plus the book value of total assets minus common equity and deferred tax all divided by the book value of total assets. Stock return is be measured as the annually percentage change in the stock price. RD/TA is measured as research & development costs divided by total book value of the assets. D/TA is measured as total book value of debt divided by total book value of the assets. The total assets of a firm is measured as the total market value of the assets in thousands. Independent board members is measured as the percentage of board members that doesn’t hold any shares. Officer holdings is the percentage of shares hold by top management excluding the family managers. Blockholdings is measured as the sum of the percentages held by unaffiliated shareholders that hold at least a 5%
of the shares. Age is measured from the day of inception. Risk is measured as the stock returns for the previous 60 months multiplied by equity divided by total assets.. Family firms are firms where one family has at least 10% of the shares and a family member holds a top management positions, all other firms are considered non-family firms. T-statistics are corrected for serial correlation using Huber White Sandwich Estimator
for variance.
Significance levels.*** p<0.01, ** p<0.05, * p<0.1
Non-family Family Non-family Family Non-family Family Non-family Non-family Family Family t- statistic
Variable Obs Obs Mean Mean Std.Dev. Std.Dev. Min Max Min Max
1 ROA 1388 565 .102 -.016 .197 1.222 -2.207 .704 -17.667 4.492 2.670 **
2 Tobin’s q 1284 524 1.660 1.578 1.202 1.447 .354 19.828 .194 15.157 1.150
3 Stock return 1388 565 .072 .039 .475 .441 -.981 7.273 -.987 3.714 1.499
4 Total assets 1388 565 2.80e+07 8042761 5.25e+07 2.25e+07 1407 3.76e+08 74 1.37e+08 11.735 ***
11 Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (1) ROA 1.000 (2) Tobin’s q -0.130 1.000 (3) Stock return 0.022 -0.058 1.000 (4) Family Firm -0.078 0.032 -0.038 1.000 (5) D/TA 0.018 -0.041 -0.055 -0.032 1.000 (6) RD/TA -0.112 0.016 0.060 -0.130 -0.125 1.000 (7) Total assets 0.053 -0.019 -0.006 -0.187 0.031 -0.019 1.000
(8) Independent board members 0.003 -0.022 0.034 -0.281 -0.049 0.117 -0.051 1.000
(9) Blockholdings -0.014 0.002 -0.029 -0.220 -0.115 0.005 -0.093 -0.019 1.000 (10) Officer holdings -0.032 -0.006 -0.037 0.254 0.117 -0.057 -0.115 -0.088 -0.096 1.000 (11) Risk -0.075 0.004 -0.027 0.048 -0.303 0.086 -0.105 -0.292 0.119 0.041 1.000 (12) Log age 0.064 -0.020 0.063 -0.133 0.010 -0.133 0.090 0.003 0.114 -0.144 -0.148 1.000 Table 4 Correlation matrix
The table provides the correlation matrix for the variables used in the analysis. The variables ROA is measured as the book value of the total assets divided by EBITDA. Tobin’s q is measured as the market value of common equity plus the book value of total assets minus common equity and deferred tax all divided by the book value of total assets. Stock return is be measured as the annually percentage change in the stock price.
RD/TA is measured as research & development costs divided by total book value of the assets. The leverage of a firm, D/TA, is measured as total book value of debt divided by total book value of the assets. The total assets of a firm is measured as the total book value of the assets in thousands. Independent board members is the percentage of board members that doesn’t hold any shares. Officer holdings is the percentage of shares hold by top management excluding the family managers. Blockholdings is the sum of the percentages held by unaffiliated shareholders that hold at least a 5% of the shares. Age is measured from the day of
The regression results
In this section the relationship between firm performance and family ownership is analysed. Table 5 shows the results of the pooled model, while table 6 shows the fixed effects model, and table 7 shows the fixed effects model capped at 5th and 95th percentile and table 8 shows the model with the
interaction variable family#young. In all tables return on assets (ROA) was measured using earnings before interest taxed and amortization (EBIDTA) as the return in column 1, column 2 uses Tobin’s q and column 3 uses the annual stock returns. I will focus on column 1 and use the other two columns for robustness checks.
Table 5 demonstrates the pooled regression. In column 1, ROA, most variables are insignificant. Log of total assets and RD/TA are significant on a 1% level. Risk is significant on a 5% level. Economically log of total assets doesn’t add value, as a 1 percentage increase in the real value of total assets would only mean an increase in the ROA of 0.00032. The other significant variables are economically
significant as they possess higher values. In column 2, Tobin’s q, the variable family firm is significant on a 1% level. It has a negative value of 0.201 meaning that family firms perform worse than other firms. The value of -.201 is also economically significant because the mean for Tobin’s Q of the whole sample is 1.633. All the columns have a low R-Squared, so the model does not explain a lot about the dependent variable.
In order to control for time and industry, I have regressed a two-way fixed effect test, with the results being shown in table 6. The R-squared of this model is slightly higher but again still lower than expected. This model found a significant value on 10% level for the variable family firms in column 3. In appendix B the results of the F-test can be found. These result show that the null hypothesis should be rejected and the fixed effects add value to the model. Therefore, I used this model to perform differing experiments.
In order to see if my results are driving by outliers, I capped ROA, Tobin’s q and stock return at the 5th
and 95th percentile. Table 7 shows the results when these variables are capped. The capped model
has an increase in R-squared as well that more variables are significant. It shows on a 1% level that family firms tend to do worse on the performance measure Tobin’s q and stock return. They also have economically significant values. The value of family firm in column 1 is insignificant but the robustness checks are significant on a 1% level.
Prior literature suggests that if the firm is passed along generations, family members have less to contribute to the productivity and efficiency in the firm, thus suggesting that younger family firms should perform better than older family firms. To analyses these issues, an interaction variable was included in the model. This interacts the family firm with the dummy variable for young firms. A firm is considered young if their inception date is no more than 50 years ago. Table 8 depicts the results of this regression. It shows that familyfirm#young is not unilateral in all three regressions. The
coefficient for a familyfirm#young is significant on a 10% level and shows that a young family firm should have a ROA which is 20,9% higher than an old non-family firm. Column 2 shows that Tobin’s q for young family firms should be lower, which is the opposite of the results in column 1. This value is statistical significant on a 1 % level. Since column 1 shows a significant positive value and column 2 a significant negative value, the results are not robust. This specific model shows that older family firms tend to do worse than older non-family firms. The ROA is lower with a significance level of 1% and the stock returns are lower on 5% significance level. Both value are economically significant as well, ROA seems to be 21.8% lower and the stock return is 0.63% lower
13
(1) (2) (3)
VARIABLES ROA Tobin’s q Stock return
Family firm -0.061 -0.201*** -0.022 (0.037) (0.074) (0.030) D/TA -0.154* -0.212 -0.178** (0.088) (0.176) (0.071) RD/TA -1.003*** 3.829*** 0.448** (0.222) (0.437) (0.181)
Log total assets 0.032*** -0.069*** 0.003
(0.006) (0.012) (0.005) Independent directors -0.037 -0.084 0.017 (0.072) (0.141) (0.058) Blockholdings 0.056 0.104 -0.084 (0.068) (0.135) (0.056) Officer holdings 0.333 -0.490 -0.094 (0.345) (0.679) (0.280) Risk -0.124** 0.034 -0.056 (0.062) (0.121) (0.050) Log age -0.004 -0.036 0.032** (0.016) (0.031) (0.013) Constant -0.240* 2.818*** -0.030 (0.143) (0.283) (0.116) Observations 1,786 1,786 1,786 R-squared 0.044 0.087 0.015 Table 5
Firm performance and family ownership, Pooled OLS (n=116)
This table report the results of the pooled regression. Family firm is a binary variable that equals one if one family has at least 10% of the shares and a family member holds a top management positions otherwise 0. The variables ROA is measured as the book value of the total
assets divided by EBITDA. Tobin’s q is measured as the market value of common equity plus the book value of total assets minus common equity and deferred tax all divided by the book value of total assets. Stock return is be measured as the annual percentage change in the stock price. RD/TA is measured as research & development costs divided by total book value of the assets. D/TA is measured as total book
value of debt divided by total book value of the assets. The log total assets is measured as the natural log the total market value of the assets in thousands. Independent directors is measured as the percentage of board members that doesn’t hold any shares. Officer holdings is measured as the percentage of shares hold by top management excluding the family managers. Blockholdings is measured as the sum of the percentages held by unaffiliated shareholders that hold at least a 5% of the shares. Log age is measured as the natural logarithm of age since the inception of the firm. Risk is measured as the stock returns for the previous 60 months multiplied by equity divided by total assets.
14
(1) (2) (3)
VARIABLES ROA Tobin’s Q Stock return
Family firm -0.064 -0.425 -0.057* (0.039) (0.350) (0.033) D/TA -0.060 -0.268 -0.196** (0.157) (0.285) (0.088) RD/TA -1.122*** 0.175 0.286 (0.198) (0.377) (0.349)
Log total assets 0.046* -0.392*** -0.001
(0.023) (0.076) (0.005) Independent directors -0.241* 0.049 -0.058 (0.142) (0.732) (0.058) Blockholdings 0.043 -0.815 -0.095** (0.123) (0.821) (0.043) Officer holdings 0.462 -7.208*** -0.042 (0.457) (2.466) (0.162) Risk -0.016 0.462 -0.072 (0.066) (0.333) (0.075) Log age -0.008 -0.156 0.014 (0.018) (0.140) (0.012) Constant -0.084 7.906*** 0.373*** (0.290) (1.437) (0.125) Adjusted R-squared 0.105 0.123 0.154 Observations 1,786 1,786 1,786 Table 6
Firm performance and family ownership, fixed effects (n=116)
This table report the results of regressing firm performance on family ownership. Family firm is a binary variable that equals one if one family has at least 10% of the shares and a family member holds a top management positions otherwise 0. The variables ROA is measured as the book value of the total assets divided by EBITDA. Tobin’s q is measured as the market value of common equity plus the book value of
total assets minus common equity and deferred tax all divided by the book value of total assets. Stock return is be measured as the annual percentage change in the stock price. RD/TA is measured as research & development costs divided by total book value of the assets. D/TA is
measured as total book value of debt divided by total book value of the assets. The log total assets is measured as the natural log the total market value of the assets in thousands. Independent directors is measured as the percentage of board members that doesn’t hold any shares. Officer holdings is measured as the percentage of shares hold by top management excluding the family managers. Blockholdings is measured as the sum of the percentages held by unaffiliated shareholders that hold at least a 5% of the shares. Log age is measured as the natural logarithm of age since the inception of the firm. Risk is measured as the stock returns for the previous 60 months multiplied by
equity divided by total assets. The standard errors in parentheses are corrected for serial correlation with the Huber White Sandwich Estimator for variance.. All regression include dummy variables for the two-digit SIC code which has base SIC 89 and dummies for the year
which has as base 1999.
(1) (2) (3)
VARIABLES ROA Tobin Stock return
Family firm -0.015 -0.382*** -0.051*** (0.013) (0.120) (0.019) D/TA -0.080*** -0.080 -0.096** (0.022) (0.157) (0.048) RD/TA 0.080 0.973* -0.125 (0.089) (0.574) (0.154)
Log total assets 0.004 -0.100*** 0.001
(0.003) (0.028) (0.004) Independent directors -0.003 -0.172 0.009 (0.035) (0.222) (0.037) Blockholdings -0.038 -0.784*** -0.035 (0.027) (0.236) (0.033) Officer holdings -0.185** -2.873*** -0.077 (0.082) (0.751) (0.177) Risk -0.032* 0.283** -0.051 (0.017) (0.140) (0.041) Log age 0.012 -0.083 0.007 (0.007) (0.065) (0.009) Constant 0.027 3.678*** 0.043 (0.070) (0.527) (0.089) R-Squared 0.335 0.279 0.219 Observations 1,635 1,608 1,590 Table 7
Firm performance and family ownership, fixed effects, capped at 5th and 95th percentile (n=116)
This table reports the results of regressing firm performance on family ownership. Family firm is a binary variable that equals one if one family has at least 10% of the shares and a family member holds a top management positions otherwise 0. The variables ROA is measured as the book value of the total assets divided by EBITDA. Tobin’s q is measured as the market value of common equity plus the book value of
total assets minus common equity and deferred tax all divided by the book value of total assets. Stock return is be measured as the annual percentage change in the stock price. RD/TA is measured as research & development costs divided by total book value of the assets. D/TA is
measured as total book value of debt divided by total book value of the assets. The log total assets is measured as the natural log the total market value of the assets in thousands. Independent directors is measured as the percentage of board members that doesn’t hold any shares. Officer holdings is measured as the percentage of shares hold by top management excluding the family managers. Blockholdings is measured as the sum of the percentages held by unaffiliated shareholders that hold at least a 5% of the shares. Log age is measured as the natural logarithm of age since the inception of the firm. Risk is measured as the stock returns for the previous 60 months multiplied by
equity divided by total assets. The standard errors in parentheses are corrected for serial correlation with the Huber White Sandwich Estimator for variance. All regression include dummy variables for the two-digit SIC code which has base SIC 89 and dummies for the year
which has as base 1999. The variables ROA, Tobin’s q and stock return are capped at the 5th and 95th percentile.
16
(1) (2) (3)
VARIABLES ROA Tobin's Q Stock return
Family firm -0.218*** 0.036 -0.0631** (0.0839) (0.331) (0.0310) Young 0.0189 0.305** 0.0235 (0.0269) (0.138) (0.0267) Familyfirm#young 0.209* -0.666*** 0.00120 (0.117) (0.250) (0.0487) D/TA -0.0450 -0.289 -0.193** (0.163) (0.273) (0.0880) RD/TA -1.100*** 0.569 0.233 (0.219) (0.452) (0.345)
Log total assets 0.0475** -0.352*** -0.000423
(0.0229) (0.073) (0.00487) Independent directors -0.244** -0.038 -0.0516 (0.124) (0.687) (0.0575) Blockholdings 0.0463 -0.771 -0.0772* (0.116) (0.770) (0.0405) Officer holdings 0.272 -5.998*** -0.0701 (0.353) (2.310) (0.192) Risk -0.0356 0.466 -0.0828 (0.0574) (0.339) (0.0750) Constant -0.153 6.800*** 0.385*** (0.325) (1.331) (0.119) R-squared 0.109 0.133 0.154 Observations 1,789 1,789 1,789 Table 8
Firm performance and young family ownerships (n=116)
This table report the results of regressing firm performance on family ownership. Family firms is a binary variable that equals one if one family has at least 10% of the shares and a family member holds a top management positions otherwise 0. Young is binary variable that equals 1 if the firm age is below 50 and otherwise 0. Family firm#young is an interaction variable between family firm and young. The variables ROA is measured as the book value of the total assets divided by EBITDA. Tobin’s q is measured as the market value of common equity plus the book value of total assets minus common equity and deferred tax all divided by the book value of total assets. Stock return is be measured as the annual percentage change in the stock price. RD/TA is measured as research & development costs divided by total book value of the assets. D/TA is measured as total book value of debt divided by total book value of the assets. The log total assets is measured
as the natural log the total market value of the assets in thousands. Independent directors is measured as the percentage of board members that doesn’t hold any shares. Officer holdings is measured as the percentage of shares hold by top management excluding the family managers. Blockholdings is measured as the sum of the percentages held by unaffiliated shareholders that hold at least a 5% of the
shares. Log age is measured as the natural logarithm of age since the inception of the firm. Risk is measured as the stock returns for the previous 60 months multiplied by equity divided by total assets. The standard errors in parentheses are corrected for serial correlation with
17
Summary and conclusion
I will now summarize my paper and make conclusion based on the results shown earlier. The first hypothesis of this paper is ‘’ Family firms outperform non-family firms’’. The panel used in this study indicates that family owned firms tend to perform worse than non-family organizations but, most values are insignificant. I used the return on assets (ROA) as a performance measurement, using earnings before interest taxes and amortisations (EBIDTA) as the return. To check for the robustness of my results I used two other performance measurements. These were Tobin’s Q and the annual stock return. I have made three models and found none significant value for the ROA. Based on these findings, the model is not sufficient enough to make a solid and satisfying conclusion. Therefore I can’t reject the null hypothesis that family firms have different performance than non-family firms. Some of the robustness checks indicate negative significant values for the performance of family firms. This is not in line with the studies of Anderson and Reeb (2003) and Maury (2006) who both suggested a higher performance of family firms.
The results for the second hypothesis which states “Do young family firms outperform older family
firms”, are significant but not robust. Tobin’s Q has a negative coefficient while the coefficient for
ROA is positive. The result being, I can not reject the null hypothesis and further research will be needed to make reliable conclusion.
Limitation and further research
As my research did not find any significant results and thus I could not make reliable conclusion, further research is needed. In this part I will analyse the limitation of this study and make suggestions for further research.
The underlying issue for these result could be the definition of a family firm used in this study. Miller et al. (2007) found the results of a study highly depended on the definition of a family firm. Further research should use multiply definition of a family firm. The definition could be adjusted by changing the amount of shares the family needs to be in possession of, or that the family must be have a higher level of active management.
This research has used equity stake as the measurement of ownership but, it is common that control rights exceed their equity stake. Families who don’t have a majority equity stake, often stay in control because they hold 2.75 times the board seats to what their equity stake should give them (Anderson and Reeb (2003)). Devices to gain more control rights than equity stake would give are pyramidal structures, holdings through multiple control chains, multiple classes of shares and cross-holdings (Faccio and Lang (2002)). Further research could focus on control rights instead of the equity stake, because the ones who control the firm can make investment decisions.
During this research it was sometimes unclear if top managers are related to the founding family. Further research should go deeper into this matter as it affects which firms are considered a family firm. This is particularly difficult and time consuming due to the changes in the last names over the generations.
18
References
Anderson, Ronald C., Sattar A. Mansi, and David M. Reeb, 2003, Founding family ownership and the agency cost of debt, Journal of Financial Economics 68, 263–285.
Anderson, Ronald C., and David M. Reeb, 2003, Founding-Family Ownership and Firm Performance: Evidence from the S&P 500, Journal of Finance 58, 1301–1328.
Berle, Adolf, and Gardiner Means, 1932, The Modern Corporation and Private Property (Harcourt, Brace, & World, New York, NY).
Davis, James H., F. David Schoorman, and Lex Donaldson, 1997, Toward a Stewardship Theory of Management, The Academy of Management Review 22, 20.
Demsetz, Harold, and Kenneth Lehn, 1985, The Structure of Corporate Ownership: Causes and Consequences, Journal of Political Economics 93, 1155–1177.
Faccio, Mara, and Larry H P Lang, 2002, The ultimate ownership of Western European corporations,
Journal of Financial Economics 65, 365–395.
Fama, Eugene F., and Michael C. Jensen, 1985, Organizational forms and investment decisions,
Journal of Financial Economics 14, 101–119.
James, Harvey S., 1999, Owner as Manager, Extended Horizons and the Family Firm, International
Journal of the Economics of Business 6, 41–55.
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and Banking 1, 15–29.
Maury, Benjamin, 2006, Family ownership and firm performance: Empirical evidence from Western European corporations, Journal of Corporate Finance 12, 321–341.
Miller, Danny, Isabelle le Breton-Miller, Richard H. Lester, and Albert A. Cannella, 2007, Are family firms really superior performers?, Journal of Corporate Finance 13, 829–858.
Modigliani, Franco, and Merton H Miller, 1958, The Cost of Capital, Corporation Finance and the Theory of Investment, The American Economic Review 48, 261–297.
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Appendix A
Overview of the variables
Variable Definition Method Source Frequency
Firm performance Return on assets using earnings before interest taxes depreciation and amortization
EBIDTA divided by book value of total assets Eikon Annually at the year end.
Tobin's q (Market value of common equity + Book value of total assets - common
equity - deferred taxes)/book value of total assets
Eikon Annually at the year end.
Stock return Yearly percentage change Eikon Annually at the year end.
Family firm One is considered a family firm if the family holds 10% of the shares and a family member holds a top management position
A binary variable that equals one when it's a family firm and otherwise zero
Orbis Year end 2018
Officer holdings The shares hold by top management Sum of shares hold by top management less family top management holdings
Orbis Year end 2018 Independent directors The fraction of directors on the board that don't hold
shares
Independent director divided by the total size of the board Orbis Year end 2018 Blockholdings Sum of the shares hold by unaffiliated blockholders. One is
considered a unaffiliated blocker holder if he/she only holds 5% but isn't family
Sum of all shares hold by unaffiliated blockholders Orbis Year end 2018
R&D/TA To proxy for growth opportunities Research and development expenses divided by the book value of total assets
Eikon Yearly at year end
Risk To control for firm specific risk Standard deviation of the stock returns form the past 60 months
multiplied by the equity to total asset ratio
Eikon Annually at the year end. Log total assets To proxy for the size of a company The natural logarithm of the market value of total assets in thousands Eikon Annually at the year end.
Log age Age since inception The natural logarithm of age since inception Eikon Annually at the year end.
Two-digit SIC code Two digit SIC code to control for industry effect A dummy variable for each SIC code using SIC 87 as the base Eikon Year end 2018
Year Year dummy to control for time fixed effects A dummy variable for each year using year 1999 as the base Annually at the year end.
Young firm Binary variable for young firms A binary variable that equals one when a the date of the firm's inception is below or equal to 50 years, otherwise 0
Eikon Annually at the year end. Familyfirm#young Interaction variable between young firm and family firm
Appendix B
Fixed effects F-test
Fixed effects F-Test ROA Fixed effects F-Test Tobin's q Fixed effects F-Test Stock return
SICtest SICtest SICtest
( 1) SIC8 - SIC10 = 0 ( 1) SIC8 - SIC10 = 0 ( 1) SIC8 - SIC10 = 0 ( 2) SIC8 - SIC13 = 0 ( 2) SIC8 - SIC13 = 0 ( 2) SIC8 - SIC13 = 0 ( 3) SIC8 - SIC15 = 0 ( 3) SIC8 - SIC15 = 0 ( 3) SIC8 - SIC15 = 0 ( 4) SIC8 - SIC16 = 0 ( 4) SIC8 - SIC16 = 0 ( 4) SIC8 - SIC16 = 0 ( 5) SIC8 - SIC20 = 0 ( 5) SIC8 - SIC20 = 0 ( 5) SIC8 - SIC20 = 0 ( 6) SIC8 - SIC25 = 0 ( 6) SIC8 - SIC25 = 0 ( 6) SIC8 - SIC25 = 0 ( 7) SIC8 - SIC27 = 0 ( 7) SIC8 - SIC27 = 0 ( 7) SIC8 - SIC27 = 0 ( 8) SIC8 - SIC28 = 0 ( 8) SIC8 - SIC28 = 0 ( 8) SIC8 - SIC28 = 0 ( 9) SIC8 - SIC29 = 0 ( 9) SIC8 - SIC29 = 0 ( 9) SIC8 - SIC29 = 0 (10) SIC8 - SIC33 = 0 (10) SIC8 - SIC33 = 0 (10) SIC8 - SIC33 = 0 (11) SIC8 - SIC34 = 0 (11) SIC8 - SIC34 = 0 (11) SIC8 - SIC34 = 0 (12) SIC8 - SIC35 = 0 (12) SIC8 - SIC35 = 0 (12) SIC8 - SIC35 = 0 (13) SIC8 - SIC36 = 0 (13) SIC8 - SIC36 = 0 (13) SIC8 - SIC36 = 0 (14) SIC8 - SIC37 = 0 (14) SIC8 - SIC37 = 0 (14) SIC8 - SIC37 = 0 (15) SIC8 - SIC38 = 0 (15) SIC8 - SIC38 = 0 (15) SIC8 - SIC38 = 0 (16) SIC8 - SIC40 = 0 (16) SIC8 - SIC40 = 0 (16) SIC8 - SIC40 = 0 (17) SIC8 - SIC42 = 0 (17) SIC8 - SIC42 = 0 (17) SIC8 - SIC42 = 0 (18) SIC8 - SIC43 = 0 (18) SIC8 - SIC43 = 0 (18) SIC8 - SIC43 = 0 (19) SIC8 - SIC45 = 0 (19) SIC8 - SIC45 = 0 (19) SIC8 - SIC45 = 0 (20) SIC8 - SIC48 = 0 (20) SIC8 - SIC48 = 0 (20) SIC8 - SIC48 = 0 (21) SIC8 - SIC49 = 0 (21) SIC8 - SIC49 = 0 (21) SIC8 - SIC49 = 0 (22) SIC8 - SIC50 = 0 (22) SIC8 - SIC50 = 0 (22) SIC8 - SIC50 = 0 (23) SIC8 - SIC51 = 0 (23) SIC8 - SIC51 = 0 (23) SIC8 - SIC51 = 0 (24) SIC8 - SIC54 = 0 (24) SIC8 - SIC54 = 0 (24) SIC8 - SIC54 = 0 (25) SIC8 - SIC55 = 0 (25) SIC8 - SIC55 = 0 (25) SIC8 - SIC55 = 0 (26) SIC8 - SIC56 = 0 (26) SIC8 - SIC56 = 0 (26) SIC8 - SIC56 = 0 (27) SIC8 - SIC57 = 0 (27) SIC8 - SIC57 = 0 (27) SIC8 - SIC57 = 0 (28) SIC8 - SIC59 = 0 (28) SIC8 - SIC59 = 0 (28) SIC8 - SIC59 = 0 (29) SIC8 - SIC60 = 0 (29) SIC8 - SIC60 = 0 (29) SIC8 - SIC60 = 0 (30) SIC8 - SIC64 = 0 (30) SIC8 - SIC64 = 0 (30) SIC8 - SIC64 = 0 (31) SIC8 - SIC65 = 0 (31) SIC8 - SIC65 = 0 (31) SIC8 - SIC65 = 0 (32) SIC8 - SIC67 = 0 (32) SIC8 - SIC67 = 0 (32) SIC8 - SIC67 = 0 (33) SIC8 - SIC73 = 0 (33) SIC8 - SIC73 = 0 (33) SIC8 - SIC73 = 0 (34) SIC8 - SIC79 = 0 (34) SIC8 - SIC79 = 0 (34) SIC8 - SIC79 = 0 (35) SIC8 - SIC80 = 0 (35) SIC8 - SIC80 = 0 (35) SIC8 - SIC80 = 0 (36) SIC8 - SIC30 = 0 (36) SIC8 - SIC30 = 0 (36) SIC8 - SIC30 = 0 (37) SIC8 = 0 (37) SIC8 = 0 (37) SIC8 = 0
21 Fixed effects F-Test ROA Fixed effects F-Test Tobin's q Fixed effects F-Test Stock
return
Yeartest Yeartest Yeartest
( 1) Year2000 - Year2001 = 0 ( 1) Year2000 - Year2001 = 0 ( 1) Year2000 - Year2001 = 0 ( 2) Year2000 - Year2002 = 0 ( 2) Year2000 - Year2002 = 0 ( 2) Year2000 - Year2002 = 0 ( 3) Year2000 - Year2003 = 0 ( 3) Year2000 - Year2003 = 0 ( 3) Year2000 - Year2003 = 0 ( 4) Year2000 - Year2004 = 0 ( 4) Year2000 - Year2004 = 0 ( 4) Year2000 - Year2004 = 0 ( 5) Year2000 - Year2005 = 0 ( 5) Year2000 - Year2005 = 0 ( 5) Year2000 - Year2005 = 0 ( 6) Year2000 - Year2006 = 0 ( 6) Year2000 - Year2006 = 0 ( 6) Year2000 - Year2006 = 0 ( 7) Year2000 - Year2007 = 0 ( 7) Year2000 - Year2007 = 0 ( 7) Year2000 - Year2007 = 0 ( 8) Year2000 - Year2008 = 0 ( 8) Year2000 - Year2008 = 0 ( 8) Year2000 - Year2008 = 0 ( 9) Year2000 - Year2009 = 0 ( 9) Year2000 - Year2009 = 0 ( 9) Year2000 - Year2009 = 0 (10) Year2000 - Year2010 = 0 (10) Year2000 - Year2010 = 0 (10) Year2000 - Year2010 = 0 (11) Year2000 - Year2011 = 0 (11) Year2000 - Year2011 = 0 (11) Year2000 - Year2011 = 0 (12) Year2000 - Year2012 = 0 (12) Year2000 - Year2012 = 0 (12) Year2000 - Year2012 = 0 (13) Year2000 - Year2013 = 0 (13) Year2000 - Year2013 = 0 (13) Year2000 - Year2013 = 0 (14) Year2000 - Year2014 = 0 (14) Year2000 - Year2014 = 0 (14) Year2000 - Year2014 = 0 (15) Year2000 - Year2015 = 0 (15) Year2000 - Year2015 = 0 (15) Year2000 - Year2015 = 0 (16) Year2000 - Year2016 = 0 (16) Year2000 - Year2016 = 0 (16) Year2000 - Year2016 = 0 (17) Year2000 - Year2017 = 0 (17) Year2000 - Year2017 = 0 (17) Year2000 - Year2017 = 0 (18) Year2000 - Year2018 = 0 (18) Year2000 - Year2018 = 0 (18) Year2000 - Year2018 = 0 (19) Year2000 = 0 (19) Year2000 = 0 (19) Year2000 = 0
