The difference in performance between privately and publicly owned companies:

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The difference in performance between privately and publicly owned companies:

An empirical research on the private equity market of the United Kingdom.

Abstract

This thesis investigates the difference in performance between privately and publicly owned

companies located in the United Kingdom in the period between 2004 and 2012. Additionally, I have investigated the difference in performance between the two types of companies during economic upturn (2004-2006) and during economic downturn (2007-2012). Privately held companies accomplish higher operating revenue growth, although marginally, during both periods. However, this growth is not paralleled by higher EBITDA margins or return on assets. In general, I have not found significant evidence that privately owned companies outperform their publicly owned counterparts in the United Kingdom.

Key words:

Private equity, portfolio companies, publicly owned companies,

performance, EBITDA-margin, operating revenue growth, return on

assets.

JEL codes:

G24, G32, G34

Acknowledgements: I would like to express my gratitude towards prof. dr. R.E. Wessels for

his input and advice during the writing of this thesis.

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Index

1. Introduction

………

5

2.

Literature review and hypotheses

2.1 Private equity companies and their investments……….

6

2.2 Use of private equity through time………

7

2.3 The choice between private equity and public equity………..

9

2.4 Earlier Research and hypotheses……….

11 3. Research outline and methodology

3.1 Methodology……….

12 4. Data

4.1 Data……….

15

4.2 Definition of variables………..

16

4.3 Descriptive statistics………..

17

4.4 Potential sources for bias………

20 5. Results

………...

20 6. Conclusion

………..

26 7. References

………...

28

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List of tables

Table 1. Difference in performance between portfolio and public companies overall, during

economic upturn and during economic downturn

Table 2. Companies assigned to groups based on sector, revenues, and employees. Table 3. Descriptive statistics of groups based on amount of employees.

Table 4: Descriptive statistics of groups based on operating revenue. Table 5. Descriptive statistics of groups based on market sector.

Table 6. Effect of being privately owned. The effect is measured during the complete investigation period (2004-2012), during economic upturn (2004-2006) and during economic downturn (2007-2012).

Table 7: Difference in performance between portfolio companies financed with Venture capital and buyout capital.

Table 8: Difference in performance explained by private equity ownership, sector, revenues, age, investments, investment opportunity set and debt-to-equity ratio (overall period, 2004-2012)

Table 1: Difference in performance explained by private equity ownership, sector, revenues, age, investments, investment opportunity set and debt-to-equity ratio(during economic upturn and downturn).

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List of figures

Figure 1: European private equity investments in number and value (1982-2010). Figure 2: Value of European private equity investments per country (2008-2010).

Figure 3: Number and value of private equity investments in the United Kingdom (1979-2011). Figure 4: United Kingdom GDP revisions (2005-2012).

Appendix:

Appendix 1: Distribution of operating revenue growth between 2004-2012 (left side = publicly owned companies, right side = privately owned companies).

Appendix 2: Distribution of EBITDA-margin between 2004-2012 (left side = publicly owned companies, right side = privately owned companies).

Appendix 3: Distribution of return on assets between 2004-2012 (left side = publicly owned companies, right side = privately owned companies).

Appendix 4: Distribution of operating revenue growth during economic upturn (left side = publicly owned companies, right side = privately owned companies).

Appendix 5: Distribution of EBITDA-margin during economic upturn (left side = publicly owned companies, right side = privately owned companies).

Appendix 6: Distribution of return on assets during economic upturn (left side = publicly owned companies, right side = privately owned companies).

Appendix 7: Distribution of operating revenue growth during economic downturn (left side = publicly owned companies, right side = privately owned companies).

Appendix 8: Distribution of EBITDA-margin during economic downturn (left side = publicly owned companies, right side = privately owned companies).

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1. Introduction

Since the 1980’s, so called private equity have become more popular. Most of the research concerning private equity is based on the performance of the companies that provide private equity, the private equity companies. Less research investigates the performance of the companies which are part of the portfolios held by private equity companies, referred to as portfolio companies or privately owned companies. This thesis investigates the performance of such portfolio companies in comparison to publicly owned peer companies. In addition, this research investigates why companies would choose private equity over public equity. The European private equity market, where the private equity market of the United Kingdom is the largest, varies strongly in total investments over the years and fluctuates over the business cycle. This research therefore also aims to find evidence of difference in performance during economic upturns and downturns. Since the private equity market in the United Kingdom is the largest private equity market in Europe, the focus of this thesis lies completely on the private equity market of the United Kingdom.

This research thus aimed to answer the question whether there is a difference in performance between privately owned companies and their publicly owned peers. In most of the existing literature (Cressy et al. 2007; Harris et al. 2012), portfolio companies turn out to outperform the publicly owned companies. Although, there is research that has found that privately owned companies perform worse than their publicly owned peers (Phalippou and Gottschalg 2009; Nielsen 2006; Nielsen 2011). Additionally, there is also research that found no significant differences between portfolio companies and publicly owned companies (Moskowitz and Vissing-Jorgensen 2002; Kaplan and Schoar 2005). The expected outcome of this thesis was that portfolio companies outperform publicly owned companies during economic upturn, economic downturn and as well during the overall period between 2004 and 2012.

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period (2004-2012), It was also possible to indicate which effect the financial crisis had on the performance of privately owned companies relative to publicly owned companies. Moreover, because only private equity investments made after 1997 are included, operational effects of private equity could be determined. Based on existing evidence (Harris et al 2012), portfolio companies tend to (operationally) outperform their public peer companies. Therefore, portfolio companies and their publicly owned peer companies are compared by analyzing the (operational) performance measures operating revenue growth, EBITDA-margin and return on assets (based on profits before taxes). The main findings of this paper are that privately owned companies seem to outperform publicly owned companies, although marginally, based on operating revenue growth. However, publicly owned companies have higher EBITDA-margins and also higher return on assets (both only marginally). In general, the evidence does not support the hypothesis that portfolio companies outperform publicly owned companies. These results are in line with the findings of Leslie and Oyer (2008), Kaplan and Schoar (2005) and Moskowitz and Vissing-Jorgensen (2002), who also did not find significant evidence that portfolio companies outperform their publicly held counterparts. This paper contributes to existing literature by giving evidence that privately and publicly owned companies do not significantly differ in performance in the United Kingdom. Additionally, there are also no significant differences in performance between privately and publicly owned companies during periods of economic upturn or downturn.

This paper continues as follows. In section two, the existing literature is reviewed and the hypotheses are formed. In section 3, the research outline and methodology are presented, section 4 presents the data, the variable definitions and descriptive statistics. Section 5 discusses the results and section 6 concludes.

2. Literature review and Hypotheses

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2.1 Private equity companies and their investments in portfolio companies.

Private equity companies like Kohlberg Kravis Roberts & Co. (KKR), The Carlyle Group, 3i and DB capital partners raise funds in order to invest in portfolio companies which they then reorganize to improve operations. According to Kaplan and Stromberg (2009) economic value is raised because of the restructuring of 3 core elements of the portfolio company, which are financial, governance and operational engineering. After several years, usually 3-5 years, the private equity company will exit through a buyout, by an IPO or recapitalization (Rizzi, 2009). In general private equity funds are structured as limited partnerships, in which general partners (the private equity fund) and limited partners (such as rich individuals or pension funds) together raise money to invest in portfolio companies, although most of the money will be brought in by the limited partners (Jenkinson 2008). These partnerships generally exist for a predetermined period with the option to extend the partnership. The return for private equity companies exists of carried interest, which is a part of income and other capital gains, and fees, which are a payment (a percentage) based on the total funds raised (Gilligan and Wright 2012). In recent literature, the return of private equity companies is often investigated on both the performance of those companies gross and net of fees (Franzoni et al. 2012; Kaplan and Schoar 2005; Axelson et al. 2013; Phalippou and Gottschalg 2009).

To understand where and why private equity companies place their investments in some specific companies, multiple criteria need to be addressed. As to the question where private equity companies invest, there are nine factors (Watson and George 2010) playing an important role: size of the economy, business freedom, transparency, price stability, cultural equality, trade protection, burden of taxation, government size and corruption. To the question why specific companies are chosen, opportunities of the company and gross margins take in an important role.

2.2 Use of Private equity through time

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One of the most important private equity players in the first wave was Kohlberg Kravis Roberts & Co. (KKR), a bank specialized in the buying and selling of corporate control. Companies like KKR make profits by reorganizing and restructuring a company’s assets to improve their operations in such a way that the purchase price will be significantly lower than the buyout price or IPO proceeds (Kaufman and Englander, 1993; Rizzi, 2009). In the beginning of the 1990s, the use of private equity decreased immediately due to the collapse of the junk bond market and the recession. This economic downturn caused several private equity related multibillion bankruptcies (Rizzi, 2009). The second wave started in the late 1990s when the use of private equity increased again. During these years the European market for private equity extended in popularity, as is shown in figure 1, which gives an overview of PE investments in Europe between 1982 and 2010.

Figure 1: European private equity investments in number and value (1982-2010)

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Figure 2: Value of European private equity investments per country (2008-2010)

The second wave was characterized by higher levels of risk and an extreme increase in private equity. Between 2003 and 2007, the increase was that high that it exceeded the total industry investments in the forgoing 20 years. As Rizzi (2009) stated: ‘The emphasis shifted from improving operating

earnings to funding the fully-priced deal through financial engineering. The result was excessively leveraged over-priced transactions dependent on continued receptive capital markets both for funding and exits’. Implying that private equity firms were busier with raising capital than investing

wisely. Because of the crisis, which started in 2007, the ease of attracting capital stagnated, private equity investments in the United Kingdom dropped to €25 billion in 2008 and even under €10 billion in 2011 (figure 3).

Figure 3: Number and value of private equity investments in the United Kingdom (1979-2011)

2.3 The choice between private and public equity

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Because the majority of researches point out that portfolio companies perform better than their public peer companies, the question arises why and in which situation companies decide to attract private equity instead of public equity. The choice between these two sources is complicated and takes in several determining variables. However, these variables can be categorized in three major categories. The costs of attracting equity, country characteristics and company characteristics. Because country and company characteristics (partly) determine the costs of attracting equity, the important company and country characteristics are discussed first.

According to the European Private Equity & Venture Capital Association (EVCA 2012), about 80% of private equity funding is invested in relative small and mid-sized companies with less than 250 employees at entry date. Therefore, size and the amount of employees matter for the decision making process of attracting private equity over public debt. Moreover, according to Jenkinson (2008), invested equity is generally used for buyouts and (early stage) expansion, which implies that size and age are a factor. Therefore, size based on amount of employees and operating revenues will be a factor in setting peer groups. According to Katz (2009), another major activity of private equity companies is the backing of mature firms which are already profitable. Therefore I will also include the year of incorporation, so the age of the company, as a control variable in this research. Country specific characteristics also partly determine the choice between private or public equity. These characteristics include, among others: the size of the economy, freedom of doing business and taxation (Watson and George, 2010). Another country specific factor, which could explain why private companies prefer private equity over public debt, is that private companies face less regulations, e.g. that they are not obliged to disclose all (financial) information (Johan et al., 2013). But, since private equity firms in the UK are obliged to disclose their financials and other information e.g. regarding risk management, as disclosed in the Company Act of 1967, this factor is not accounted for in this research.

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Adverse selection costs also arise due to timing differences. In times of economic prosperity this costs ought to be higher (Carpentier et al, 2010). For private companies, the information asymmetry costs are high when revealing information publicly is costly for the company even more so for young and small companies (Aslan and Kumar, 2011). Moreover, according to Dhaliwal et al (2011) and Fidrmuc et al (2013), the adverse selection costs attached to private equity are ought to be lower in low information environments because of the advantage that private lenders have in analyzing and evaluating environments in which the availability of information is low (e.g. low disclosure). Furthermore, attracting public equity often takes months whereas private equity could be attracted (generally) in just a few days or weeks (Carpentier et al, 2010). Indirect costs of private equity arises because private equity entry does not increase stock liquidity, which is priced by the market. To summarize, Firms tend to go public when the cost of sharing information is low and investment needs are high (Aslan and Kumar, 2011) and tend to go private when sharing of information is costly.

2.4 Earlier Research and hypotheses

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H1: Portfolio companies outperform publicly owned companies in the period between 2004 and 2012.

H1a: Portfolio companies outperform publicly owned companies based on operating revenue growth

H1b: Portfolio companies outperform publicly owned companies based on EBITDA-margin. H1c: Portfolio companies outperform publicly owned companies based on return on assets. Because of the dramatic decrease of available funds in times of economic downfall, the ongoing financial crisis is expected to have a huge negative effect on the performance of companies. Loos (2005) found that in times of economic prosperity the positive effect was higher than in times of economic downturn, but that portfolio companies outperform peer companies in both cases. However, Kaplan and Schoar (2005) found some evidence that private equity that is invested during economic upturn lead to lower returns. But, due to the restructuring and managerial impact of private equity companies on portfolio companies, the expected outcome was that portfolio companies suffer less from the financial crisis and will outperform publicly held companies both during economic upturn (2004-2006) as well as during economic downturn (2007-2012).

H2: Portfolio companies outperform the public peer companies during economic upturn.

H2a: Portfolio companies outperform the public peer companies during economic upturn based on operating revenue growth.

H2b: Portfolio companies outperform the public peer companies during economic upturn based on EBITDA-margin.

H2c: Portfolio companies outperform the public peer companies during economic upturn based on return on assets.

H3: Portfolio companies outperform publicly owned companies during economic downturn.

H3a: Portfolio companies outperform publicly owned companies during economic downturn based on operating revenue growth.

H3b: Portfolio companies outperform publicly owned companies during economic downturn based on EBITDA-margin.

H3c: Portfolio companies outperform publicly owned companies during economic downturn based on return on assets.

3. Research outline and methodology

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performance during a period of economic upturn (2004-2006) as well as during economic downturn (2007-2012), as stated in hypothesis 2 and 3. To investigate these hypotheses, a database was constituted out of privately and publicly owned companies located in the United Kingdom. The data is subjected to a regression analysis which took in several independent and dependent variables. The different independent variables that are included are meant to explain the variance in performance. The independent variables include sector, age, investment rate, investment opportunity set, operating revenues, amount of employees, a crisis period variable and, of course, a variable which measures the effect of being privately owned. The dependent variables are the performance measures; Operating revenue growth, EBITDA margin and the return on assets (ROA). These measures are also used in existing literature to measure the performance of (privately owned) companies (Acharya et al. 2013; Leslie and Oyer 2008; Hu and Ansell 2007; Boardman and Vining 1989). A regression model is used to test whether the performance of portfolio companies significantly differ from the performance of publicly owned companies.

3.1 Methodology

The method for research and analysis consists of two parts. The first part summarizes the data of the portfolio companies and the publicly owned companies. Means and medians of all groups are calculated and summarized in tables. In order to test whether these means and medians give a good insight, regression tests were used because these test are most commonly used in recent literature (Franzoni et al 2012); Harris et al 2013; Kaplan and Schoar 2005). Acharya et al (2013), used financial and operating ratios to measure the difference in performance between privately and publicly owned companies. Following their model, I also used EBITDA-margin as a measure of performance. My model differs from their operational model by adding ROA and operating revenue growth as operating performance measures. Furthermore, Acharya et al (2013) investigated the performance of privately owned companies during the period between 2003 and 2007, I also took in the crisis period (2007-2012). Also Meles et al (2014) use a regression model to find differences in

performance between privately and publicly owned companies. Although their strategy is more focused on the difference between buyout and venture capital performance, and their variables have a more financial basis, they also used control variables like age and the debt-to-equity ratio.

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equation will determine how the performance of privately and publicly owned companies differ in times of economic up- and downturn. To determine such a difference, a dummy variable was included to separate the pre-crisis period (2004-2006) and the crisis period (2007-2012). The crisis period was set from 2007 onwards because the crisis hit during that year (figure 4). The first three equations together form the simple regression model.

Additionally, as visualized in equation 4, I have also tested whether there is a difference in performance between privately owned companies which attracted venture capital or buyout capital. Following Hellman and Puri (2002), all private equity investments in companies which existed less than 10 years on the date of entry of the private equity investment, were marked as venture capital investments. Kaplan and Schoar (2005) found that firms financed with venture capital outperform firms financed

with buyout capital over the period 1980-2000. However, Harris et al (2012) found that firms financed with venture capital, in contrast to firms that were financed with buyout capital, performed weaker than public companies during the 2000s. Meles et al (2014) found that the effects of venture capital last longer than the effects of buyout capital.

Equation 5 represents the extended regression model in which all control variables and categorical variables were added. In all equations below the term ‘PE’ stands for private equity (so ‘PE.owned’ takes in the effect of being privately owned), the term ‘perf’ represents the different performance measures. The variables concerning operating revenues, sector and employees are groups which are created using dummy variables. The groups concerning operating revenues and employees are created based on amount of operating revenues and number of employees. Furthermore, there are 4

Figure 4: UK GDP revisions (2005-2012)

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different sectors included in this model; manufacturing (man), information and communication (info), wholesale and retail trade (wr), and other services.

4.

Data

4.1 Data

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included in the database along with some general information about the companies. The database only includes companies for which the required information is available for all (but one) years. Moreover, companies for which financial information from 2004 onwards was not available were removed from the database. Furthermore, financial information of the year 2013 was deleted for all companies, since this information was not available for a vast amount of companies. Besides, since this research also investigates differences in performance throughout market sectors, the database only includes companies which were active in the following sectors; manufacturing, information and communication, wholesale and retail trade, and other services. All this selection criteria led to the selection of 41 portfolio companies and 774 public companies, combining to a total of 815 companies.

4.2 Definition of variables

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The performance measures operating revenue growth is measured in a quite straightforward way as visualized in the equation below.

The EBITDA-margin is calculated as the EBITDA divided by operating revenues, the performance measure return on assets (ROA) is based on profits before taxes and comes directly from the database Orbis. All performance measures are adjusted for outliers.

4.3 Descriptive characteristics

This research aimed at finding evidence that performance of portfolio companies differs from publicly owned companies in the UK. Furthermore, an explanation was sought for the puzzle why portfolio companies tend to outperform publicly owned companies. Table 1 shows the difference in the average performance of portfolio and publicly owned companies. As visualized in table 1, portfolio companies seem to outperform their publicly owned counterparts when we compare both on the overall mean and median scored on operating revenue growth. However if we compare portfolio companies with publicly owned companies based on the ROA, public companies seem to outperform the privately owned companies. Comparison based on EBITDA margin does not give a clear insight. The same preliminary conclusions can be drawn for privately owned and publicly owned companies during economic upturn (2004-2006). Considering the crisis period (2007-2012), the descriptive statistics show that privately owned companies outperform publicly owned companies on operating revenue growth as well as on EBITDA-margin. The distribution of the performance measures for all periods is visualized in appendix 1 to 9.

Table 2: Difference in performance between portfolio and public companies (overall, upturn and downturn) Portfolio companies Public companies

Portfolio - Public

Overall (2004-2012) Mean Median St. Dev Mean Median St. Dev Mean Median

Operating revenue growth .070 .063 .246 .047 .039 .226 .023 .024

EBITDA margin .083 .086 .198 .086 .071 .147 -.002 .015

ROA .025 .049 .210 .053 .054 .136 -.028 -.005

Economic upturn Mean Median St. Dev Mean Median St. Dev Mean Median

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ROA -.001 .047 .260 .059 .059 .144 -.060 -.012

Economic downturn Mean Median St. Dev Mean Median St. Dev Mean Median

EBITDA margin .094 .088 .183 .087 .070 .147 .007 .018

ROA .041 .050 .180 .051 .051 .132 -.010 -.001

The first 3 columns represent the means, medians and standard deviation for the portfolio companies. The columns 4, 5 and 6 give the same information for the publicly owned companies. The last two columns show the difference in means and medians between portfolio and publicly owned companies.

As stated in the previous subsection, the database includes 41 portfolio companies and 774 publicly owned companies. These companies were divided among groups, based on different categories (sector, operating revenues and employees). Table 2 provides an overview of these different categories and the amount of companies that are assigned to them. The tables 3, 4 and 5 show the descriptive statistics for each group per performance measure.

Table 3: Amount of companies assigned to groups based on sector, revenues and employees based on sector Public companies Portfolio companies Total companies

Manufacturing 221 10 231

Wholesale and retail trade 104 5 109

Information and communication 162 8 170

Other services 287 18 305 Total 774 41 815 Based on revenue Revenue <£10,000 253 10 263 Revenue £10,000-£35,000 174 19 193 Revenue £35,000-£100,000 129 8 137 Revenue >£100,000 218 4 222 Total 774 41 815 Based on employees <50 Employees 233 5 238 50-100 Employees 105 13 118 100-1000 Employees 261 19 280 >1000 Employees 175 4 179 Total 774 41 815

‘Revenue <£10,000’ refers to the group of companies that generate less than £10,000 operating revenue a year, whereas ‘revenue £10,000-£35,000’ represents the group of companies that generated between £10,000 and £35,000. The same logic applies to the groups based on employees

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operating revenue has more explanatory power, I removed the variable number of employees from the regression model. The EBITDA margin and ROA tend to increase with the size of the company (higher operating revenues or more employees). This implies that larger companies are more efficient. Table 5 gives the descriptive statistics for the groups based on sector. The companies active in wholesale and retail trade seem to be the least efficient based on EBITDA-margin, however these companies tend to have the highest ROA. The companies that are active in the sector ‘other services’ seem to perform relatively better, on average, than the companies in other sectors.

Table 4: Descriptive statistics of groups based on amount of employees

<50 Employees 50-100 Employees

Performance

measures Mean Median St. Dev N Mean Median St. Dev N Operating revenue growth .051 .039 .259 238 .051 .039 .246 118 EBITDA margin .065 .052 .169 .055 .050 .184 ROA .047 .045 .172 .035 .045 .164 100-1000 Employees >1000 Employees Performance

measures Mean Median St. Dev N Mean Median St. Dev N Operating revenue

growth .051 .039 .220 280 .048 .040 .227 179

EBITDA margin .087 .073 .130 .086 .072 .150

ROA .053 .053 .123 .052 .054 .141

This table gives the means, medians, standard deviation and amount of companies for each subgroup that was created based on the amount of employees of a company.

Table 5: Descriptive statistics of groups based on operating revenue

Operating revenue <10,000 Operating revenue 10,000-35,000 Performance

growth .056 .039 .258 263 .056 .046 .230 193

EBITDA margin .057 .063 .191 .074 .061 .123

ROA .034 .038 .182 .052 .055 .136

Operating revenue 35,000-100,000 Operating revenue >100,000 Performance

growth .038 .035 .220 137 .039 .041 .185 222

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ROA .055 .053 .110 .071 .065 .095 This table gives the means, medians, standard deviation and amount of companies for each subgroup that was created based on the amount of operating revenues of a company.

Table 6: Descriptive statistics of groups based on market sector

Manufacturing Information and Communication Performance

growth .039 .033 .216 231 .055 .035 .253 109

EBITDA margin .085 .085 .134 .095 .077 .178

ROA .044 .056 .144 .048 .048 .182

Wholesale and retail trade Other services Performance

growth .039 .035 .200 170 .058 .051 .238 305

EBITDA margin .058 .045 .071 .098 .079 .177

ROA .066 .059 .105 .052 .050 .137

This table gives the means, medians, standard deviation and amount of companies for each subgroup that was created based on the sector in which the company is active.

4.4 Potential sources of bias

All the financial data that has been collected comes from the database Orbis, this gives cause to a potential selection bias because it is possible that not all companies located in the United Kingdom are represented in the database. Furthermore, although Orbis is a database designed for the analysis of privately owned companies, it is not clear to what extent all the private equity companies are represented. Another source for potential bias stems from the amount of privately owned companies that are analyzed in this research. Since only privately owned companies that attracted private equity from 1997 onwards could be included, the sample could be biased. The time period increases the probability that the sample doesn’t accurately represent the private equity market in the United Kingdom. In general, databases including privately owned companies can be biased towards large companies or public-to-private transactions, since it is more likely that they have to report their financials. However, this research includes only companies located in the United Kingdom, a region in which all companies (public and private) are obliged to report their financials.

5. Results

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Table 7: Effect of being privately owned. The effect is measured during the complete investigation period (2004-2012), during economic upturn (2004-2006) and during economic downturn (2007-2012).

Overall (2004-2012) Coefficient Std. error P-value R2

Operating Revenue growth

constant .047 .003 .000 .000

Private equity ownership .023 .012 .066*

EBITDA margin

constant .086 .002 .000 .000

Private equity ownership -.002 .008 .766

ROA

constant .053 .002 .000 .002

Private equity ownership -.028 .008 .000***

Economic upturn (2004-2006)

Operating Revenue growth Coefficient Std. error P-value R2

constant .101 .005 .000 .001

Private equity ownership .041 .022 .060*

EBITDA margin

constant .084 .003 .000 .001

Private equity ownership -.027 .014 .060*

ROA

constant .059 .003 .000 .007

Economic downturn (2007-2012) Coefficient Std. error P-value R2

constant .021 .003 .000 .000

Private equity ownership .015 .015 .319

EBITDA margin

constant .007 .010 .479 .000

Private equity ownership .087 .002 .000***

ROA

constant .051 .002 .000 .000

Private equity ownership -.010 .009 .282

*,** and *** represents significance levels of 10%, 5% and 1%, respectively. The ‘constant’ measures the impact of being a public company on performance, whereas the variable ‘Private equity ownership’ measures the difference in performance between portfolio companies and public companies.

Table 8: Difference in performance between portfolio companies financed with Venture capital and buyout capital Performance measures Coefficient Std. error P-value R2

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constant .093 .014 .000 .117

Venture capital -.143 .021 .000***

*, ** and *** represents significance levels of 10%, 5% and 1%, respectively. The ‘constant’ reflects the impact of being a company which attracted buyout funds, whereas the variable ‘venture capital companies’

reflects the difference in performance between venture capital companies and buyout companies.

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Table 9: Difference in performance explained by private equity ownership, sector, revenues, age, investments, investment opportunity set and debt-to-equity ratio (overall period, 2004-2012)

Performance measures Coefficient Std. error P-value R2

constant .123 .014 .000 .010

Manufacturing -.005 .007 .495

Information/communication -.011 .009 .199

Wholesale and retail trade -.011 .008 .143

<£10,000 revenues .002 .008 .838

£10,000-£35,000 revenues .003 .008 .739

£35,000-£100,000 revenues -.006 .009 .475

Age -.023 .004 .000***

Investments .004 .004 .336

Investment opportunity set .327 .112 .004***

Debt-to-equity ratio -.131 .061 .031**

EBITDA margin Coefficient Std. error P-value R2

constant .155 .009 .000 .054

Manufacturing -.017 .005 .000***

Information/communication .001 .006 .864

Wholesale and retail trade -.045 .005 .000***

<£10,000 revenues -.070 .005 .000***

£10,000-£35,000 revenues -.046 .005 .000***

£25,000-£100,000 revenues -.024 .006 .000***

Age -.006 .002 .013***

Investments .017 .003 .000***

Investment opportunity set .015 .017 .393

Debt-to-equity ratio -.042 .039 .284

Return on assets (ROA) Coefficient Std. error P-value R2

constant .064 .009 .000 .013

Manufacturing -.010 .004 .018**

Information/communication .001 .005 .854

Wholesale and retail trade .008 .005 .095*

<£10,000 revenues -.034 .005 .000***

£10,000-£35,000 revenues -.015 .005 .002***

£25,000-£100,000 revenues -.014 .005 .011**

Age .002 .002 .290

Investments .001 .002 .754

Investment opportunity set -.012 .016 .444

Debt-to-equity ratio -.005 .037 .888

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Table 9 summarizes the effects that all variables have on the performance measures during

economic upturn as well as during economic downturn. For both periods, private equity ownership doesn’t have a significant impact on the performance measures. Except for the return on assets, private equity ownership is negatively, and significantly so, related to the return on assets during economic upturn. Therefore, the hypotheses that portfolio companies outperform publicly owned companies during economic upturn or downturn cannot be accepted. Furthermore, smaller companies, based on revenues, tend to grow faster during upturn (significantly) and also during downturn (although marginally). However, the opposite effect is found regarding the EBITDA margin (significantly) and the return on assets (marginally), for both periods. Age is significantly negatively related to operating revenue growth and EBITDA margin during both periods. The investment opportunity set is positively related to the EBITDA margin and operating revenue growth.

Table 10: Difference in performance explained by private equity ownership, sector, revenues, age, investments, investment opportunity set and debt-to-equity ratio (during economic upturn and downturn).

Performance measures during economic upturn during economic downturn Operating Revenue growth Coefficient Std. error P-value R2 Coefficient Std. error P-value R2

constant .218 .024 .000 .061 .041 .017 .016 0.003

Private equity ownership .033 .026 .203 .012 .015 .432

Manufacturing -.047 .014 .001*** .004 .008 .602

Information/communication -.052 .017 .003*** .002 .011 .865

Wholesale and retail trade -.052 .015 .001*** -.001 .009 .913

<£10,000 revenues .030 .015 .049** .001 .009 .952

£10,000-£35,000 revenues .002 .016 .895 .008 .009 .411

£35,000-£100,000 revenues -.003 .017 .865 -.004 .010 .714

Age -.030 .007 .000*** -.007 .005 .128

Investments .072 .021 .000*** .003 .004 .533

Investment opportunity set 3.371 .685 .000*** .283 .112 .012**

Debt-to-equity ratio -.018 .134 .894 -.117 .067 .079*

EBITDA margin Coefficient Std. error P-value R2 Coefficient Std. error P-value R2

constant .155 .016 .000 _.063 .157 .011 .000 .054

Private equity ownership -.020 .017 .242 .007 .010 .463

Manufacturing -.030 .009 .001*** -.011 .005 .033**

Information/communication -.020 .011 .075* .008 .007 .246

Wholesale and retail trade -.049 .010 .000*** -.043 .006 .000***

<£10,000 revenues -.075 .010 .000*** -.068 .006 .000***

£10,000-£35,000 revenues -.050 .010 .000*** -.045 .006 .000***

£35,000-£100,000 revenues -.025 .011 .025** -.023 .007 .000***

Age -.004 .004 .336 -.008 .003 .014**

Investments .037 .014 .007*** .017 .003 .000***

Investment opportunity set .742 .340 .029** .012 .017 .486

Debt-to-equity ratio -.014 0.087 0.877 -0.044 0.043 0.311

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constant .091 .016 _{.000 0.032} .049 .010 .000 0.011

Private equity ownership -.061 .017 .000*** -.006 .009 .515

Manufacturing -.033 .009 .000*** -.003 .005 .486

Information/communication -.017 .012 .146 .007 .006 .234

Wholesale and retail trade -.002 .010 .877 .010 .005 .049*

<£10,000 revenues -.046 .010 .000*** -.030 .005 .000***

£10,000-£35,000 revenues -.010 .011 .321 -.016 .006 .003***

£35,000-£100,000 revenues -.010 .011 .382 -.015 .006 .015**

Age .001 .004 .904 .005 .003 .098*

Investments .003 .014 .816 .001 .002 .735

Investment opportunity set -.227 .343 .509 -.011 .016 .473

Debt-to-equity ratio .020 .089 .822 -.011 .040 .791

*,**,*** represents significance levels of 10%, 5% and 1% respectively.

the first column represent the variables, column 2, 3 and 4 give the regression summary for the variables during economic upturn, whereas column 5, 6 and 7 give the regression summary for the variables during economic downturn.

6. Conclusion

This thesis investigated the difference in performance between privately and publicly owned

companies. Moreover, it also analyzed whether these differences vary between periods of economic upturn and downturn. Furthermore, control variables as amount of revenues, sector, age,

investments, investment opportunity set and the debt-to-equity ratio were added to the regression model. Besides, I also investigated whether private companies that attracted venture capital (younger or startup companies) differed in performance from private companies that attracted buyout capital (older or mature companies).

I have analyzed the difference in performance between privately and publicly owned companies using regression models based on 3 (main) hypotheses. The results on these hypotheses are summarized in table 10.

Table 10: Hypotheses and conclusions

Hypotheses

Simple regression model

Extended regression model 1. Portfolio companies outperform publicly owned

companies in the period between 2004-2012

Inconclusive Inconclusive

- Based on operating revenue growth Yes Yes (marginally)

- Based on EBITDA margin No (marginally) No (marginally)

- Based on return on assets no No

2. Portfolio companies outperform publicly owned

companies during economic upturn (2004-2006) Inconclusive Inconclusive

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- Based on EBITDA margin No No (marginally)

- Based on return on assets No No

3. Portfolio companies outperform publicly owned companies during economic downturn (2007-2012)

Inconclusive Inconclusive

- Based on operating revenue growth Yes (marginally) Yes (marginally)

- Based on EBITDA margin Yes Yes (marginally)

- Based on return on assets No (marginally) No (marginally)

I have to reject all three main hypotheses because there is no significant evidence that privately owned companies outperform publicly owned companies (or vice versa).These results are in line with the findings of Leslie and Oyer (2008), Kaplan and Schoar (2005) and Moskowitz and

Vissing-Jorgensen (2002) who also did not find significant evidence of difference in performance between privately and publicly owned companies. However , the evidence seems to point out that, in general, privately owned companies enjoy larger operating revenue growth, whereas publicly owned

companies tend to have higher EBITDA margins as well as higher return on assets. Which could imply that privately owned companies grow faster, but that publicly owned companies are more efficient. During economic downturn, it seems that privately owned companies enjoy higher operating revenue growth as well as higher EBITDA margins. The return on assets, however, remains higher (although marginally) for the publicly owned companies. To conclude, I did not find (enough)

significant evidence that portfolio companies outperform their publicly owned counterparts. There is only significant evidence that publicly owned companies outperform privately owned companies based on the return of assets during economic upturn and the complete period of this research. This does not hold during economic downturn. Therefore it seems that the evidence, regarding the private equity market of the United Kingdom, points out that publicly owned companies, although marginally, outperform privately owned companies.

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8. Appendix

Appendix 1, 2 and 3 show the distribution for each performance measure over the complete research period (2004-2012). The graphs on the left represent the distribution for the publicly held companies, whereas the graphs on the right represent the distribution of the privately held companies.

Appendix 1: Distribution of operating revenue growth between 2004-2012 (left side = publicly owned companies, right side = privately owned companies)

Appendix 2: Distribution of EBITDA-margin between 2004-2012 (left side = publicly owned companies, right side = privately owned companies)

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Appendix 4, 5 and 6 show the distribution for each performance measure over the period of

economic upturn (2004-2006). The graphs on the left represent the distribution for the publicly held companies, whereas the graphs on the right represent the distribution of the privately held

companies.

Appendix 4: Distribution of operating revenue growth during economic upturn (left side = publicly owned companies, right side = privately owned companies)

Appendix 5: Distribution of EBITDA-margin during economic upturn (left side = publicly owned companies, right side = privately owned companies)

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Appendix 7, 8 and 9 show the distribution for each performance measure over the period of economic downturn (2007-2012). The graphs on the left represent the distribution for the publicly held companies, whereas the graphs on the right represent the distribution of the privately held companies.

Appendix 7: Distribution of operating revenue growth during economic downturn (left side = publicly owned companies, right side = privately owned companies)

Appendix 8: Distribution of EBITDA-margin during economic downturn (left side = publicly owned companies, right side = privately owned companies)