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4.1章的目的
首先，将提供的样本的描述性统计，然后由一个讨论的回归分析，以确定这两种类型的所有权类型之间的差异。面板数据分析将遵循以确保鲁棒性。最后，本章将提出一个总结的结果，在前一章的子问题的问题。
4.2描述性统计
在表8中，在这项研究中使用的变量的描述性统计，作为每个单独的市场。该表被分为四个面板：面板和乙的新兴市场，埃及和泰国分别呈现描述性统计。面板和三维介绍了发达国家市场，巴西和德国的描述性统计。对于每一个变量，平均值和标准偏差的结果。显然，样本不会导致一个巨大的比例，家庭企业，每市场-家庭公司的比例最高的是在巴西（近35%），而最低的是在埃及（25%）。家族企业的总数，在所有四个市场是70，或29%。被发现的家庭企业的缺乏是一个要求，家庭企业的创始家族在业务中保持着关键作用的结果。
4.1 Aim of Chapter
The main objective of this chapter is to provide a discussion regarding the empirical results of this study which have been obtained from the data, and then through the implementation of the research methodology, as discussed in the previous chapter. Firstly, descriptive statistics for the sample will be provided, which will be followed by a discussion regarding the regression analysis which was employed in order to determine differences between both ownership types. Panel data analysis will follow in order to ensure robustness. Finally, this chapter will conclude by presenting a summary of the results, with regards to the sub-questions asked in the previous chapter.
4.2 Descriptive Statistics
In Table 8, the descriptive statistics for the variables used within this study are presented, as per individual market . The table is split into four panels: Panels A and B presents the descriptive statistics for the emerging markets, Egypt and Thailand respectively. Panels C and D presents the descriptive statistics for the developed markets, Brazil and Germany respectively. For each variable, the mean and standard deviation results are presented. Evidently, the sample does not result in a huge proportion of family firms per market - the highest percentage of family firms is in Brazil (almost 35%) whereas the lowest is in Egypt (25%). The total number of family firms, across all four markets is 70, or 29%. The lack of family firms being found is the result of placing a requirement that family firms are those in which the founding-family maintains a key-role in the business.
The key finding reported in table 8 is that family firms are not superior performers in every market: results are perfectly split - whereas family firms outperform non-family firms (based on all 3 performance measures - the exception is ROA for Brazil, but the difference is less than 0.04%) in developed markets, the same is not found in the emerging markets. Taking Egypt, non-family firms outperform family firms based on all three performance measures. Although the difference is sometimes minimal - i.e. a difference of 0.30% in ROA, under other measures (i.e. TQ), the difference is almost 33% . Furthermore, ROE results in a difference of 2.13%, thereby suggesting that, in Egypt, family controlled companies make poor resource allocation decisions, which affects the markets perceptions regarding the family firms.
Although the market views family firms in Thailand with more positivity than non-family firms, accounting-based performance measures do not suggest superior performance by family firms. ROA and ROE for non-family firms outstrip that of family firms: a difference of approximately 2.2% and 3.2% respectively. From the descriptive statistics regarding the emerging market alone, it appears as though family firms do not outperform non-family firms.
Moving onto the developed markets, findings differ: TQ and ROE is higher for family firms in both Brazil and Germany. For Brazil, the TQ ratio is approximately 15% higher, whereas ROE is approximately 1.25% higher. This suggests that family firms make better use of shareholders funds, as is suggested by the superior market valuation and ROE. On the other hand, Germany reports a TQ ratio that is approximately 22% higher for the family firm, and a ROE ratio that is approximately 12% higher. Much of this difference in ROE is due to one non-family firm reporting a huge reduction in net income. When this is set to 0, the ROE for family firms still outstrips non-family firms by approximately 7% . The final performance measure, ROA, is higher for family firms in Germany (by exactly 4%) whereas, the ROA is marginally higher for non-family firms in Brazil (6.63% for family firms, and 6.67% for non-family firms).
The brief discussion above, as based on table 8, is in line with the findings of Ibrahim and Samad (2011) - apparent superior performance can be the result of the choice of performance measure - in this sample, only Germany (for family firms) and Egypt (for non-family firms) shows superior (or inferior) performance based on all three measures. Further, due to past research having mainly focussed on the developed markets, my descriptive statistics are in agreement with the work of Villalonga and Amit (2006), Maury (2006), Anderson and Reeb (2003), amongst others prolific family-firm researchers .
Turning my attention to the independent variables, it is evident that the independent variables do not behave in the same way. Whereas Egypt and Germany show higher growth rates for non-family firms, Thailand and Brazil show higher growth rates for family firms. Where Egyptian and German non-family firms show superior growth rates of 19% and 9%, respectively, Thailand and Brazil show increases in growth of 38% and 130%, respectively, for family firms, thereby suggesting that family firms are better at exploiting the opportunities that are available to them.
In the emerging markets, family firms are younger than their non-family counterparts. The reverse is found for the developed market, where it is found that family firms are more mature. This impacts on the overall performance in that family firms in the emerging market are found to underperform non-family firms (at least based on 2 out of three measures), whereas family-firms are older in the developed market, in which they are found to outperform the non-family market.
The board size in Germany is smaller for family firms as compared to non-family firms. In the remaining markets, the board size is found to be larger for family firms. For the majority of markets it is found that, as the size of the board rises, performance declines. However, for Brazil the opposite is found; non-family firms have a smaller board, but inferior performance. Considering board composition, family firms in the emerging market have a lower proportion of independent directors, which could potentially explain the lower performance. However, board composition is also lower (for family firms) in Germany, where family firms perform better. Evidently, this may be suggestive of the notion that too many independent directors are equality destructive, given Germany's dual-board system. On the contrary, family firms in Brazil employ more independent directors, potentially explaining the superior performance.
Inconsistent with original beliefs, I fail to find that family firms employ lower levels of debt across all four markets - the only market which shows lower debt for family firms is Germany. What is worth noting is that family firms in Germany report superior performance across all three performance measures, whereas the rest of the sample does not. Therefore, it can be suggested that markets in which family firms outperform non-family firms do employ lower levels of debt. This was cited as a potential reason for the difference in performance between family and non-family firms by Kachaner et al. (2012).
Finally, firm size, suggests equal findings across all four markets - consistent with Anderson and Reeb (2003), I find that family firms are generally smaller than their non-family counterparts. This leads to suggestions that firm size is irrelevant to performance.
Table 8
Descriptive statistics for individual Markets
________________________________________
Variable All Firms Family Firms Non-Family Firms
________________________________________
Mean StDev Mean StDev Mean StDev
________________________________________
Panel A. Egypt
Fam_Firm 25.45% 0.436
Tobin's Q 1.127 1.075 0.882 #p#分页标题#e#0.516 1.211 1.197
Return on Assets 6.47% 0.091 6.25% 0.054 6.55% 0.091
Return on Equity 12.92% 0.184 11.33% 0.127 13.46% 0.200
Ln (Firm Age) 1.343 0.343 1.193 0.182 1.395 0.309
Ln (Firm Size) 7.892 0.855 7.817 1.023 7.918 0.791
Board Size 8.575 2.411 8.857 2.704 8.478 2.302
Board Comp. 0.559 0.192 0.529 0.182 0.570 0.194
Sales Growth 28.78% 0.902 14.77% 0.497 33.57% 1.001
Leverage 1.05% 0.252 7.68% 0.241 -1.21% 0.253
Observations 275 70 205
Panel B. Thailand
Fam_Firm 33.33% 0.472
Tobin's Q 1.125 0.978 1.168 1.181 1.103 0.861
Return on Assets 7.45% 0.082 6.00% 0.095 8.18% 0.074
Return on Equity 13.18% 0.222 11.05% 0.231 14.24% 0.217
Ln (Firm Age) 1.385 0.203 1.364 0.199 1.396 0.204
Ln (Firm Size) 8.741 0.570 8.510 0.512 8.562 0.563
Board Size 12.158 2.822 12.667 2.988 11.904 2.705
Board Comp. 0.371 0.188 0.338 0.261 0.387 0.135
Sales Growth 54.20% 0.528 79.31% 0.741 41.64% 0.314
Leverage 17.81% 0.249 23.72% 0.236 14.85% 0.237
Observations 360 120 240
________________________________________
________________________________________
Panel C. Brazil
Fam_Firm 34.88% 0.478
Tobin's Q 1.318 1.213 1.464 1.517 1.241 1.012
Return on Assets 6.66% 0.063 6.63% 0.077 6.67% 0.056
Return on Equity 15.49% 0.182 16.30% 0.215 15.06% 0.162
Ln (Firm Age) 1.138 0.491#p#分页标题#e# 1.270 0.420 1.068 0.513
Ln (Firm Size) 9.365 0.631 9.287 0.477 9.407 0.698
Board Size 8.228 2.800 8.693 2.365 7.979 2.985
Board Comp. 0.344 0.233 0.360 0.216 0.336 0.241
Sales Growth 232.14% 4.075 316.52% 6.450 186.93% 1.683
Leverage 14.55% 0.204 20.11% 0.170 11.56% 0.215
Observations 215 75 140
Panel D. Germany
Fam_Firm 26.25% 0.440
Tobin's Q 0.979 0.810 1.168 1.081 0.911 0.678
Return on Assets 3.95% 0.107 6.92% 0.068 2.92% 0.116
Return on Equity 3.79% 1.205 14.07% 0.201 0.13% 1.396
Ln (Firm Age) 1.654 0.483 1.817 0.299 1.596 0.522
Ln (Firm Size) 9.708 0.225 9.516 0.816 9.777 0.770
Board Size 17.679 7.11 17.056 7.220 17.901 7.067
Board Comp. 0.723 0.790 0.719 0.096 0.724 0.144
Sales Growth 12.42% 0.317 19.14% 0.226 27.89% 1.413
Leverage 12.60% 0.251 11.32% 0.242 13.05% 0.255
Observations 480 126 354
________________________________________
Table 8 Continued.
This table presents the descriptive statistics for my study, breaking the sample down into its individual markets. The variables are as follows: Fam_Firm, a dummy variable that equals one if the company is a family firm, and zero otherwise; Tobin's Q, as calculated by market capitalization + net debt over total assets; Return on Assets (ROA), as based on net income; Return on Equity (ROE), as based on net income; Ln (Firm size) which takes the natural log of total assets, in Euros; Ln (Firm Age) which takes the natural log of the firm age, in years; Board Size (total directors); Board comp. (number of independent directors/total directors); Sales Growth covering the period 2008 to 2011 (4 years); and Leverage (Net debt/total assets).
4.3 Regression Analysis
This section considers the relationship between firm performance and the determinants of firm performance, as presented by the dissertation model presented in chapter 3. Due to potential differences in markets, results will be presented as-per individual markets.
4.3.1 OLS Regression
In table 9, the OLS regression results, which examine the relationship between multiple independent variables and firm performance, are presented. The regression results for the emerging markets are presented first (panel A and B), and then the regression results for the developed markets are presented (panel C and D). The results suggest that, for different markets, the relationship between firm performance and the underlying variables differ.
The principle finding of my study is that family ownership has a two-way split with regards to influence on performance. As can be seen in table 9, for emerging markets, family ownership has a negative effect on performance measures (all three measures for Thailand; ROE and TQ for Egypt). Looking at Egypt, TQ is 19.25% lower for family firms, and ROE is 1% lower. However, when performance is measured through ROA, performance is approximately 17% higher for family firms. Thailand on the other hand shows lower performance for family firms, by 1.24% (TQ); 16.11% (ROA) and 12.14% (ROE) .
In contrast, family ownership has a positive effect in the developed markets based on all three performance measures (exception is Brazil - the relationship between family ownership and ROE is negative). For Germany, the relationship between family ownership and both TQ and ROA is significant, at the 10% and 1% level, respectively. Considering Brazil, it is found that TQ is 18.29% higher, ROA is 1.5% higher, and ROE is 2.6% lower for family firms. For Germany, the results suggest that family firms experience a 13.48% higher TQ; a 73.42% higher ROA, and a 255.94% higher ROE than their non family counterparts.
The results of this study are in partial-agreement with Ibrahim and Samad (2011), who suggest that perceived superior performance is dependent on the performance measure used. Although Egypt and Germany suggest the same direction across all three performance measures (i.e. for Egypt, all three measures suggest superior performance by non-family firms), for Brazil and Thailand, the three measures provide contradictory results regarding the relationship between family ownership and firm performance .#p#分页标题#e#
Amran and Ahmed (2009) suggested that firm age is negatively related to firm performance. However, I find conflicting results. For Egypt, I find that firm age and performance is positively related (with the exception being ROA for non-family firms). However, I find no significant relationship between firm performance and age for family firms, although for non-family firms, the relationship between performance (based on TQ) is significantly positive. Brazil shows similar results in that firm age is positively associated with performance, for which the relationship is significant for accounting based performance measures, for all three samples (family; non-family and all). For Germany, the relationship between firm age and performance, as based on TQ and ROA is significantly negative for family firms, whereas the relationship between ROA and firm age is significantly positive for non-family firms, suggesting that as family firms mature, they become less effective resource allocators, whereas non-family firms show superior performance with maturity. For Thailand, the relationship between firm performance and age shows mixed results as based on different performance measures; where the performance measure is TQ or ROA, the relationship is positive, and when the performance measure is ROE, the relationship is negative (for non-family firms). However, family firms show the complete opposite - For ROE, firm age is positive, but for ROA and TQ, the relationship is negative. This suggests that the performance attributes of family firms differ from that of the non-family firms and that as firm’s mature, family and non-family firms behave differently.
In line with Maury (2006) and Miller et al. (2007), I find a mainly positive relationship between firm size and accounting-based performance measures, for both family and non-family firms in Egypt, Thailand, and Germany. The relationship is significant for all companies in Egypt (at the 5% level of better), and for Thailand, a significant relationship is only found for family firms. For Germany, the relationship is insignificant for all companies. For Brazil, firm size lowers performance, although this is insignificant (exception is non-family firms, as based on ROE). Further, based on the TQ measure of performance, I find that firm performance is negatively related to firm size across all countries. For family firms, this relationship is found to be significant in Germany and Thailand. In contrast, Brazil suggest a significant relationship for non-family firms (as does Germany). Tuning towards Egypt, no significant relationship is found. Evidently, this negative relationship suggests that as company's age, the market believes a company's ability to profit declines.
Much of the work regarding the relationship between board size and performance suggests that larger boards inhibit performance . However, I find mixed findings; for Egypt, the relationship is negative for family firms (significant when the performance measure is TQ - in line with the majority of studies), but positive for non-family firms (significant when the performance measure is ROE); for Thailand, the relationship between board size and performance is positive (significant at the 5% level as based on performance measured through ROE) for non-family firms, and negative (significant at the 1% level) for family firms, as based on accounting measures of performance. In contrast, for performance as measured through TQ, the relationship is insignificantly positive for both family and non-family firms. Brazil almost shows a split in findings - when performance is measures based on TQ, board size has a positive relationship with performance. In contrast, for accounting based performance measures, the relationship is positive as based on ROA (significant for family firm), with ROE showing a insignificantly positive relationship for non-family firms, and a negative relationship for family firms. As expected, for Germany, who operates a dual board system, the relation is positive, with the exception being family firms as based on the ROE performance measure (although insignificant).
Considering board composition, for Thailand and Germany, as board composition increases, firm performance declines. This is in line with the findings of Ibrahim and Samad (2011). However, for family firms in Egypt, the relationship is positive for both family and non-family firms, as based on accounting performance measures (significant for family firms as based on the ROA performance measure), and insignificantly negative for both family and non-family firms as based on TQ. For Brazil, it is also found that board composition positively impacts family firm performance (significant as based on ROE) However, for non-family firms, a negative relationship is found between accounting based performance measures (significant for ROA), but for TQ based, the relationship is insignificantly positive.
As expected, growth has a positive impact on market valuations (exception being Brazil). This is significant for Egyptian family firms, and non-family firms in Thailand. Given that share price is the present value of future cash flows, this is self evident. For family firms in the emerging market, sales growth appears to have a significantly positive effect on accounting performance measures. Thailand also shows a significant relationship for non-family firms as based on the ROE performance measure. Taking the developed markets, it is found that, for Brazil, sales growth negatively impacts performance based on all three performance measures, however it is only significant for family firms based on accounting-based performance measures. For non-family firms, the coefficient is 0 when accounting based performance measures are used. However, a highly significant relationship is found for non-family firm as based on the market measure, TQ. For Germany, a negative relationship is found as based on accounting performance measures (only significant for family firms, as based on ROA). Considering TQ, the relationship is insignificantly negative.
Taking the final variable, I find that leverage has a negative impact on firm performance when an accounting-based performance measure is used. This is significant for family firms in all markets when the performance measure is ROA. For Thailand and Brazil, the relationship is also significant when the performance measure used is ROE (for family firms). Turning towards non-family firms, all companies show a significantly negative relationship as based on ROA. However, Brazil does not show a significant relationship when the performance measure used is ROE. This is perhaps un-surprising given that higher leverage increases risk. However, what is surprising is that, for German and Egyptian companies, leverage is positively associated with a higher level of market performance (significant for Egyptian family firms). Considering Brazil and Thailand, the relationship is found to be negative, with the exception being non-family firms in Thailand (insignificantly positive). Both Brazil and Thailand show a significantly negative relationship on family firms. It appears that leverage affects family firms more than non-family firms, given that the relationship is more-often significant for family firms, as compared to non-family firms.
Table 9
OLS regression results for individual countries
TQ ROA ROE
ALL
(1)
Family
(2)
Non-Family
(3)
ALL
(4)
Family
(5) Non-Family
(6)
ALL
(7)
Family
(8)
Non-Family
(9)
Panel A.
Egypt
Fam_Firm -0.217
(0.157) 0.012
(0.013) -0.001
(0.026)
Ln (Firm Age) 0.593***
(0.207) 0.249
(0.164) 0.850***
(0.298) -0.006
(0.017) 0.046
(0.034) -0.029
(0.022) 0.023
(0.035) 0.053
(0.046) 0.016
(0.047)
Ln (Firm Size) #p#分页标题#e#-0.097*
(0.091) -0.055
(0.078) -0.096
(0.122) 0.027***
(0.008) 0.040**
(0.016) 0.030***
(0.009) 0.069***
(0.015) 0.056**
(0.022) 0.089***
(0.019)
Board Size -0.005
(0.028) -0.058**
(0.025) 0.019
(0.039) 0.002
(0.002) -0.007
(0.005) 0.002
(0.003) 0.007
(0.005) -0.007
(0.007) 0.011*
(0.006)
Board Comp. -0.245
(0.349) -0.451
(0.345) -0.190
(0.442) 0.087***
(0.029) 0.077
(0.072) 0.072**
(0.032) 0.096
(0.058) 0.128
(0.097) 0.067
(0.070)
Sales Growth
0.139*
(0.072) 0.528***
(0.116) 0.125
(0.084) -0.002
(0.006) 0.059**
(0.024) -0.006
(0.006) -0.013
(0.012) 0.070**
(0.033) -0.018
(0.013)
Leverage 0.179
(0.294) 0.668**
(0.258) 0.116
(0.376) -0.112***
(0.024) -0.070
(0.054) -0.123***
(0.272) -0.108**
(0.049) -0.075
(0.073) -0.116*
(0.060)
Constant 1.286
(0.882) 1.634**
(0.638) 0.691
(1.252) -0.205***
(0.073) -0.293**
(0.132) -0.184
(0.090) -.549***
(0.148) -0.400**
(0.180) -.719***
(0.199)
R2 0.080 0.392 0.062 0.114 0.188 0.150 0.118 0.194 0.148
N 275 70 205 275 70 205 275 70 205
Panel B. Thailand
Fam_Firm
-0.014
(0.123) -0.012
(0.009) -0.016
(0.028)
Ln (Firm Age) -0.006
(0.250) -0.850*
(0.486) 0.311
(0.273) -0.019
(0.019) -0.026
(0.037) 0.003**
(0.022) -0.011
(0.056) 0.083
(0.102) -0.010
(0.069)
Ln (Firm Size) -0.207*
(0.110) -0.073
(0.201) -0.298**
(0.121) 0.008
(0.008) 0.053***
(0.016) -0.015
(0.010) 0.068***
(0.025) 0.109**
(0.043) 0.054
(0.030)
Board Size 0.300
(0.021) 0.019
(0.040) 0.033
(0.024) -0.003*
(0.002) -0.011***
(0.003) 0.002
(0.002) -0.009*
(0.005) -.033***
(-0.008) 0.001**
(0.006)
Board Comp. -0.210
(0.295) -0.099
(0.404) -0.054
(0.467) -0.017
(0.022) -0.047
(0.031) -0.003
(0.037) -0.035
(0.066) -0.130
(0.085) -0.030
(0.006)
Sales Growth 0.151
(0.102) 0.153
(0.128) 0.397**
(0.189) #p#分页标题#e#0.021***
(0.008) 0.019*
(0.010) 0.010
(0.015) 0.085***
(0.023) 0.054**
(0.027) 0.109**
(0.048)
Leverage -0.925***
(0.231) -2.756***
(0.406) 0.073
(0.283) -0.154***
(0.018) -0.216***
(0.031) -0.129***
(0.023) -0.218***
(0.052) -0.239*
(0.086) -.224***
(0.071)
Constant 2.747***
(0.947) 3.201*
(1.732) 2.760***
(1.017) 0.090
(0.072) -0.163
(0.133) 0.207**
(0.081) -0.326
(0.212) -0.447
(0.365) -0.340
(0.256)
R2 0.080 0.327 0.077 0.241 0.380 0.205 0.098 215 0.076
N 360 120 240 360 120 240 360 120 240
Table 9
Continued
Panel C.
Brazil
Fam_Firm 0.241
(0.168)
0.005
(0.009) -0.004
(0.026)
Ln (Firm Age) 0.333**
(0.160)
0.762
(0.495) 0.155
(0.168) 0.033***
(0.008)
0.053**
(0.021) 0.031***
(0.010)
0.114***
(0.026) 0.190***
(0.060) 0.110***
(0.300)
Ln (Firm Size)
-0.584***
(0.149)
-0.440
(0.451) -0.619***
(0.155) -0.007
(0.008) -0.011
(0.019) -0.010
(0.009) -0.034
(0.024) -0.020
(0.055) -0.051*
(0.028)
Board Size -0.052*
(0.030)
-0.136*
(0.076)
-0.021
(0.030) 0.002
(0.002)
0.000
0.003) 0.005***
(0.002) 0.000
(0.005) -0.004
(0.009) 0.008
(0.005)
Board Comp. 0.413
(0.321)
0.496
(0.792) 0.264
(0.327) 0.007
(0.017) 0.034
(0.034) -0.025
(0.019) -0.020
(0.051) 0.183*
(0.097) -.164***
0.058)
Sales Growth
-0.015
(0.019)
-0.001
(0.029) -0.619***
(0.155) -0.004***
(0.001) -0.005***
(0.001) 0.000
(0.003) -0.009***
(0.003) -.011***
(0.003)
0.000
(0.009)
Leverage -1.268***
(0.408)
-2.605**
(1.135) -0.756*
(0.397) -0.114***
(0.021) -0.249***
(0.048) -0.074**
(0.023) -0.047
(0.065) -.530***
(0.139)
0.110
(0.070)
Constant 6.833***
(1.301)
6.118
(4.501) 7.194***
(1.292) 0.098***
(0.068) 0.156
(0.192) 0.106
(0.075) 0.376*
(0.208) 0.212
(0.550) 0.497**
(0.229)
R2 0.260 0.274 0.306 0.256
0.481 0.214 0.158 0.460 0.148
N 215 75 140 215 75 140 215 75 #p#分页标题#e#140
Table 9
Continued
Panel D.
Germany
Fam_Firm 0.132*
(0.078)
0.029***
(0.011) 0.097
(0.129)
Ln (Firm Age) -0.108
(0.074)
-1.174***
(0.329) -0.0003
0.068 0.027**
(0.010) -0.064***
(0.021) 0.023*
(0.013) 0.192
(0.122)
-0.101
(0.065) 0.175
(0.156)
Ln (Firm Size) -0.395***
(0.065) -0.379*
(0.196) -0.408***
(0.064) 0.005
(0.009) -0.013
(0.012) 0.002
(0.012) 0.117
(0.108) 0.000
(0.039) 0.129
(0.146)
Board Size
0.005
(0.007)
0.015
(0.024)
0.002
(0.007)
0.000
(0.001)
0.001
(0.002)
0.000
(0.001)
0.008
(0.012)
-0.003
(0.005)
0.009
(0.016)
Board Comp.
-0.274
(0.267)
-1.263
(1.210)
-0.224
(0.242)
-0.009
(0.038)
-0.052
(0.007)
-0.037
(0.044)
-0.243
(0.441)
-0.091
(0.240)
-0.009
(0.016)
Sales Growth
0.563***
(0.108)
0.131
(0.443) 0.030
(0.024) 0.068***
(0.015) -0.019
(0.028) -0.019***
(0.004) 0.299*
(0.178) -0.028
(0.088) -0.045
(0.056)
Leverage 0.173
(0.142)
0.427
(0.440) 0.084
(0.135) -0.068***
(0.020) -0.040
(0.028) -0.071***
(0.025) -0.461**
(0.234) -0.072
(0.087) -0.548*
(0.307)
Constant 4.975***
(0.643)
7.482***
(2.129) 5.013***
(0.634) -0.065
(0.090) 0.341**
(0.136) 0.014
(0.115) -1.381
(1.059) 0.445
(0.423) -1.428
(1.445)
R2 0.211 0.185 0.209 0.109
0.165 0.101 0.031 0.067 0.030
N 480 126 354 480 126 354 480 126 354
Table 9 Continued
* Denotes significance at the 10% level or better. This table presents regression results for individual markets. Dependent variables: Fam_Firm, a dummy variable that equals one if the company is a family firm, else zero; TQ, as calculated by market capitalization + net debt over total assets; Return on Assets (ROA), as based on net income; Return on Equity (ROE), as based on net income; Ln (Firm size); Ln (Firm Age) which takes the natural log of the firm age, in years; Board Size (total directors); Board Comp. (number of independent directors/total directors); Sales Growth covering the period 2008 to 2011 (4 years); and Leverage (net debt/total assets).
4.4 Panel Data Analysis
In order to control for heterogeneity across firms, I employ alternative econometric techniques, such-as fixed-random effects panel data regressions. Many past studies have simply adopted either one of the models, however due to my study covering multiple markets, it is evident that choosing either of the models will result in inaccuracy, given that different markets face different effects. For my panel data analysis, 6 years of data is used for firms in Germany and Thailand, and 5 years of data for firms in Brazil and Egypt. Using the Hausman test, we compare fixed-effects models to random-effects models. A significant Hausman test value implies that the random effects estimator is inconsistent, thereby suggesting that the fixed-effect estimator is more accurate (Paton and Elsayed, 2005). The results of the panel data analysis are presented in table 10, below.
For Egyptian companies (reported in panel A), fixed-effects estimates are presented for family and non-family firms as based on performance measured by ROE. When the performance measure is ROA, fixed-effects estimates are presented for non-family firms and random-effects estimates are presented for family firms. For market based measures of performance (TQ), random effects estimates are presented for both family and non-family.
Considering Thailand (panel B), for accounting based measures of performance, random-effects estimates are presented for family firms and fixed-effects estimates are presented for non-family firms. In contrast, as based on market based performance measures, the opposite is done - fixed-effects estimates are presented for family firms, and random-effects estimates are presented for non-family firms.
Panel C and D presents the results for the developed markets - panel C represents Brazil, and panel D represents Germany. For Brazilian companies, the Hausman test suggests that the random-effects estimator provides more accurate results, therefore random-effects estimates are presented for all Brazilian companies, across all three performance measures.#p#分页标题#e#
Considering Panel D, the results of the Hausman tests again differ for different performance measures/samples. However, the split is more even - for family firms, the Hausman test accepts the null-hypothesis, therefore random-effects estimates are given for all performance measures. In contrast, for non-family firms, the null hypothesis is rejected; thus fixed-effects estimates are presented in order to maintain reliability.
In line with the OLS regression results for Egypt, it is found that family ownership negatively impacts on performance. It is also evident that the age of family firms has a positive effect on firm performance as based on ROA and TQ. However, inconsistent with the OLS regression, I find that the older family firms perform poorer when the performance measure is ROE (significant). For non-family firms, accounting measures suggest older firms perform poorly (significant). However, market measures do not agree. considering firm size, it is found that, accounting measures are better for the larger firm however market-based measures deteriorate for larger firms. The effect of firm-size on performance is significant for accounting measures, but insignificant for market based valuations. Considering board size in Egypt, family firms perform poorly when the boards are larger, whereas for non-family firms, bigger boards improve performance as based on TQ (significant) and ROE. Board composition suggests that, for all companies, a higher number of independent directors results in poorer market performance (insignificant), however, accounting based measures improves for all companies. Sales growth was dropped for the fixed-effects model, however it is again found that family firms are better users of increased sales (highly significant), which is reflected through a higher family firm/TQ coefficient. Considering leverage, it is found that family firms make better use of debt, which is reflected in a significantly positive relationship between leverage and TQ. Although positive, a significant relationship is not found between non-family firms and TQ. However, for accounting based measures of performance, a highly significant and negative value is found between non-family firm performance and leverage. A similar relationship is found for family firms as based on ROA, however this is insignificant. ROE again is positive (insignificant) for family firms.
Like Egypt, panel data analysis verifies that family ownership results in inferior performance for companies in Thailand. With the exception of family firms as based on the ROA performance measure, it is found that as companies mature, performance improves. Family firms also make better use of their size as compared to non-family firms; this relationship is significant as based on accounting-based performance measures. For non-family firms, the relationship is significantly negative as based on TQ and ROA, and simply negative for ROE. Both board size and its subsequent composition negatively affects accounting-based performance. For family firms, this relationship is found to be significant based on ROE. For ROA, board size has a significantly negative effect on firm performance, whilst board composition has no significant effect. A positive relationship is also reported between family firms and market-based performance measures. For non-family firms, board composition and size again negatively influences firm performance, as based on accounting measures (significant for ROA). However, for TQ, the relationship is significantly positive between board size and TQ, whereas it is insignificantly negative between TQ and board composition. Sales growth is again positive for all companies. Considering the final variable, is it found that leverage reports a negative impacts the performance of family firms (significant for accounting-based measures). Considering non-family firms, a negative relationship is again found between leverage and performance, with the exception being TQ. This relationship is only significant for performance measured through ROA.
Panel data analysis verified that family ownership and control results in superior performance. Firm age again plays an important role in Brazil; it has a significantly positive influence on firm performance as based on accounting measures for all companies. Considering market measures of performance, the relationship for family firms is again found to be positive, although insignificant. In contrast, for non-family firms, the relationship is found to be negative (significant). Considering the size of companies, it is found that family firms make better use of their size, as based on accounting measures. However, the random-effects model suggests that larger family firms benefit from superior market valuations, however this relationship is insignificant. In complete contrast, it is found that non-family firms fail to report a positive relationship with performance, as based on all three measures of performance. Board size again shows a negative relationship for family firms, whereas it is positive for non-family firms as based on accounting measures of performance. Considering board composition, it is found that family firms benefit from superior accounting-based performances, whereas non-family firms report a negative relationship. However, it is interesting to note that the market values firms with a superior composition more highly. Considering growth, it is found that growth has a negative impact on the performance of all firms, although this is minimal. Considering leverage, a significantly negative relationship is reported between higher levels of debt and firm performance for the majority or the samples; the exception is ROE for the non-family firms, for which a positive relationship is reported.
As suggested earlier, the haussman test suggested that fixed-effects better reflect what occurs in Germany. As such, the Fam_Firm variable was dropped by the model; however, based on the sole variable that we have, it is found that family control has a positive relationship on firm performance, as measured through ROE. Considering firm age, panel data analysis suggests that as companies mature in Germany, performance begins to stagnate. However, this is barely significant; the only time significance is found is for non-family firms as based on accounting measures of performance; and for the market based measure of performance for family firms. The relationship between firm size and subsequent performance is negative for all companies (significant as based on TQ for all companies; and for non-family firms as based on performance measured through ROE), thereby suggesting companies fail to make good use of their size. In contrast to the OLS regression results, panel data analysis fails to support a positive relationship between board size and firm performance. Similarly, board composition also fails to show a positive relationship, thereby suggesting that independent directors destroy performance for German companies, given that the dual board system places the majority of directors on the supervisory board. This is found for both family and non-family firms. Sales growth also suggests a negative relationship between growth and firm performance for all companies, although this relationship is insignificant. considering leverage, a significantly negative relationship is reported for non-family firms and accounting-based performance measures; this relationship is also significant for TQ, but is found to be positive. Family firms report similar findings for accounting based performance measures, however the relationship is not significant. Like non-family firms, family firms benefit from a positive relationship between market valuation, and firm performance.
Table 10
Fixed/Random Effects
TQ ROA ROE
ALL
(1)
Family
(2)
Non-Family
(3)
ALL
(4)
Family
(5) Non-Family
(6)
ALL
(7)
Family
(8)
Non-Family
(9)
Panel A.
Egypt
Fam_firm -0.283
(0.250)
Ln ( Firm Age) 0.403
(0.314) 0.234
(0.173) 0.650
(0.473) -0.314
(0.080) 0.042
(0.037) -0.457***
(0.319) 0.771***
(0.414) #p#分页标题#e#-0.370**
(0.166) -1.331***
(0.723)
Ln (Firm Size) -0.165
(0.121) -0.579
(0.081) -0.219
(0.173) 0.078***
(0.178) 0.042**
(0.017) 0.060**
(0.028) 0.129***
0.036 0.113***
(0.036) 0.134**
(0.062)
Board Size -0.008
0.044 -0.059**
(0.027) 0.020
(0.062) -0.002
(0.012) -0.007
(0.006) -0.018
(0.017) 0.049*
(0.025) -0.022
(0.032) 0.059
(0.038)
Board Comp. -0.159
(0.533) -0.429
(0.368) -0.119
(0.685) 0.155
(0.134) 0.086
(0.080) 0.047
(0.146) 0.074
(0.270) 0.611
(0.480) 0.129
(0.331)
Sales Growth
0.125
(0.116) 0.526***
(0.124) 0.106
(0.139) 0.059**
(0.059)
Leverage 0.433
(0.318) 0.698***
(0.269) 0.352
(0.400) -0.120***
(0.031) -0.068
(0.057) -0.148***
(0.032) -0.201***
(0.063) 0.035
(0.113) -0.261***
(0.073)
Constant 2.081*
(1.190) 1.674**
(0.667) 1.901
(1.798) -0.197
(0.206) -0.300**
(0.143) 0.350
(0.319) -0.310
(0.414) -0.457
(0.425) 0.358
(0.723)
R2 0.009 0.097 0.009 0.172 0.088 0.183 0.163 -0.264 0.202
N
Panel B. Thailand
Fam_Firm
-0.020
(0.275)
Ln (Firm Age) 2.821***
(0.968) 4.105
(2.898) 0.555
(0.468) 0.116
(0.078) -0.043
(0.072) 0.126
(0.091) -0.006
(0.079) 0.067
(0.178) 0.234
(0.342)
Ln (Firm Size) -0.823***
(0.196) 0.112
(0.817) -0.634***
(0.147) -0.058***
(0.016) 0.060**
(0.026) -0.073***
(0.016) 0.058*
(0.033) 0.138**
(0.069) -0.019
(0.061)
Board Size 0.048
(0.039) 0.050
(0.073) 0.059*
(0.033) -0.002
(0.003) -0.007*
(0.004) -0.001
(0.004) -0.009
(0.006) -0.031***
(0.012) -0.003
(0.015)
Board Comp. 0.299
(0.300) 0.328
(0.422) -0.058
(0.571) -0.026
(0.024) -0.036
(0.026) -0.133**
(0.066) -0.050
(0.069) -0.134*
(0.081) -0.261
(0.248)
Sales Growth 0.203
(0.349) 0.024
(0.021) 0.084**
(0.033) 0.062
(0.051)
Leverage -0.450
(0.447) -1.056
(1.069) 0.026
(0.356) -0.131***
(0.036) -0.247***
(0.049) -0.096**
(0.041) -0.217***
(0.068) -0.333**#p#分页标题#e#
(0.133) -0.150
(0.153)
Constant 3.798***
(1.857) -5.882
(5.056) 5.172***
(1.372) 0.482***
(0.149) -0.248
(0.218) 0.631***
(0.171) -0.247
(0.275) -0.692
(0.581) 0.142
(0.639)
R2 0.080 0.090 0.122 0.089 0.163 0.128 0.013 0.091 0.011
N 360 120 240 360 120 240 360 120 240
Table 10 continued
Panel C.
Brazil
Fam_Firm
0.317
(0.268) 0.002
(0.015) 0.010
(0.044)
Ln (Firm Age) 0.218
(0.248) 0.710
(0.702) -0.039
(0.256) -0.091***
(0.024) 0.081***
(0.030) 0.035**
(0.015) 0.118***
(0.041) 0.243***
(0.088) 0.099**
(0.304)
Ln (Firm Size) -0.393*
(0.202) -0.335
(0.512) -0.353*
(0.212) -0.003
(0.011) 0.008
(0.021) -0.010
(0.012) -0.011
(0.032) 0.004
(0.061) -0.032
(0.036)
Board Size -0.065
(0.045) -0.102
(0.113) -0.052
(0.045) 0.002
(0.002) -0.002
(0.005) 0.005*
(0.003) -0.001
(0.007) -0.006
(0.014) 0.006
(0.008)
Board Comp. 0.526
(0.507) 0.361
(1.396) 0.585
(0.503) -0.002
(0.028) 0.021
(0.062) -0.028
(0.030) 0.031
(0.083) 0.143
(0.179) -0.155*
(0.084)
Sales Growth -0.017
(0.031) -0.003
(0.050) -0.093
(0.078) -0.003**
(0.002) -0.003
(0.002) 0.000
(0.005) -0.009*
(0.005) -0.009
(0.006) 0.000
(0.013)
Leverage -1.502***
(0.476) -2.206*
(1.145) -1.171**
(0.478) -0.091***
(0.024) -0.178***
(0.045) -0.054**
(0.027) -0.118
(0.075) -0.470***
(0.134) 0.055
(0.084)
Constant 5.259***
(1.768) 4.888
(5.016) 5.130***
(1.773) 0.052
(0.093) -0.060
(0.202) 0.101
(0.104) 0.180
(0.284) -0.056
(0.594) 0.342
(0.304)
R2 0.041 0.027 0.069 0.055 0.166 0.029 0.025
0.154
0.003
N 215 75 140 215 75 140 215 75 140
Table 10 continued
Panel D.
Germany
Fam_Firm
0.101
(0.140)
Ln (Firm Age) -0.444
(0.308) -1.329*
(0.759) -0.405
(0.297)#p#分页标题#e# -0.123**
(0.061) -0.068**
(0.034) -0.117*
(0.069) 0.185
(0.132) -0.010
(0.070) -1.633*
(0.883)
Ln (Firm Size) -1.345***
(0.174) -0.874***
(0.264) -1.323***
(0.197) -0.022
(0.035) -0.022
(0.017) -0.004
(0.046) 0.130
(0.115) -0.001
(0.094) -0.987*
(0.586)
Board Size -0.012
(0.015) 0.040
(0.029) -0.021
(0.016) -0.003
(0.003) -0.001
(0.002) -0.004
(0.004) 0.006
(0.013) -0.002
(0.005) -0.022
(0.047)
Board Comp. 0.134
(0.365) -0.553
(1.343) 0.114
(0.016) -0.204***
(0.073) -0.056
(0.103) -0.219***
(0.085) -0.238
(0.465) -0.103
(0.252) -0.567
(1.083)
Sales Growth -0.166
(1.023) -0.026
(0.046) -0.004
(0.046) 0.296
(0.193) -0.029
(0.094)
Leverage 0.346**
(0.146) 0.587*
(0.328) 0.035**
(0.161) -0.062**
(0.029) -0.038
(0.030) -0.067*
(0.037) -0.501**
(0.242) -0.078
(0.090) -0.952**
(0.479)
Constant 13.849***
(1.741) 11.577***
(2.738) 14.742***
(1.972) 0.669**
(0.348) 0.425**
(0.184) 0.501
(0.459) -1.475
(1.127) 0.460
(0.444) -0.113
(5.873)
R2 0.161 0.150 0.169 0.051 0.053 0.055 0.107 0.024 0.040
N 480 126 354 480 126 354 480 126 354
Table 10 continued
* denotes significance at the 10% level or better. This table presents regression results for individual markets. The Dependent variables: Fam_Firm, a dummy variable that equals one if the company is a family firm, else zero; TQ, as calculated by market capitalization + net debt over total assets; Return on Assets (ROA), as based on net income; Return on Equity (ROE), as based on net income; Ln (Firm Size); Ln (Firm Age) which takes the natural log of the firm age, in years; Board Size (total directors); Board comp. (number of independent directors/total directors); Sales Growth covering the period 2008 to 2011 (4 years); and Leverage (net debt/total assets). Note: when fixed-effects are reported, growth and Fam_firm is dropped by model due to collinearity, as shown in the table.
4.5 Summary of Empirical Findings
In the preceding sections, the results derived from the employment of my dissertation model were presented. In order to ensure sound understanding, table 11 presents a summary of my key findings. As mentioned, I find that family firms do not outperform non-family firms in every market.
Table 11
Summary of Empirical Findings
________________________________________
Market Superior Performance
________________________________________
TQ ROA ROE Overall
________________________________________
Egypt Non-Family Non-Family Non-Family Non-Family
Thailand Family Non-Family Non-Family Non-Family
Brazil Family Non-Family Family Family
Germany Family Family Family Family
________________________________________
As answers to the supplementary questions, I find that family firms only out-perform non-family firms in the fully developed markets. Further, I find that family firms experience their best performance within the German market. Considering the final question, my study provides evidence to suggest that the performance measure used is indeed important, with some markets suggesting different results, across different measures of performance.
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