Performance of Young Public Firms

Performance of Young Public Firms 

Managerial vs Outside Shareholder Control 

in an international context 

/ Daniel Heinz Klaus Heinrich Richard Walter Bogdanski   

/ 900912-T352   

/ Double Degree MSc International Financial Management / Business and Economics   

/ Faculty of Economics and Business   

/ Rijksuniversiteit Groningen and Uppsala Universitet   

/ Supervised by Dr. Wim Westerman   

/ Co-Assessed by Dr. Halìt Gönenç 

Abstract 

This paper studies the relationship between firm performance, proxied by Tobin's Q, and two distinct        ownership types, managerial owned firms and outside owned firms. The sample consists of 2005 young        firms from Europe and the US that incorporated since the dot­com­bubble 2001. Very similar to the        pre­2001 period, young and highly funded firms are of popular concern. In particular their owners,        founders and CEOs are topic of interest and serve as figurehead for their company, raising the question        whether their firms perform better if they also own them or not and whether that differs with the        institutional framework that the company is situated in. Thus the research question is the following: What        is the effect of having management as majority shareholder(s) on the performance of the young firm in        different environments? To find an answer, I used quantitative data from Orbis and analyzed it using        time­series panel data, recent information using simple OLS as well as multiple analyses of variance. I        find evidence of higher valuations of firms owned by managers, especially in countries with common law        and stronger shareholder rights. I also find evidence of relatively lower valuations of firms owned by their        managers when these are situated in code law countries or countries with stronger creditor rights. A        surprising addition to the findings were extreme values of Tobin's Q that may indicate another bubble in        the   making,   coincidentally   closing   the   circle   of   this   study. 

Key   words:   International,   Financial,   Management,   Ownership,   Firm   Performance 

JEL   Classification: G32,   L25,   L26 

1   Introduction 

It is commonly accepted that managers are largely determining firm performance, but just as        much that firms are largely determining this manager's job safety. These circumstances create uncertainty        potentially leading the managers to alter their behavior. “Unfriend: What drove Zuck to fire Saverin”        (CNET, 2012), “How Elon Musk Fired Tesla CEO and co­founder” (Business Insider, 2014) or the        famous “Apple CEO John Sculley fires Steve Jobs” (Fortune, 1985) were some of the most famous        headlines in past years and history. Those headlines and their background suggest that it is not exclusively        performance that drives founders and managers out of their firms. Usually those stories start with        “[Investor] Carl Icahn wants Yahoo CEO fired” (Fortune, 2008), followed by “Icahn Ramps Up Pressure,        Vows To Get Jerry Yang Fired” (Business Insider, 2008) to end with “Jerry Yang Resigns From Yahoo,        the Company He Founded” (WSJ, 2012), suggesting the power of controlling shareholders and implying        forces other than performance. The question is so current and attracting so much attention, that US TV        network HBO dedicated a whole award winning TV Series towards this topic, calling it “Silicon Valley”        famously quoting “take the money or keep the company”. This raises the question: what is it actually that        lets founders of young companies get into a position of facing to be ousted out of their own company? Do        firms   perform   differently   when   separation   of   ownership   and   control   does   not   exist? 

Recent work in top journals took it upon them to investigate this subject: CEO turnover and their        determinants. Research of Jenter and Kanaan (2015) suggests precisely the issue implied, turnover        decisions irrespective of the pure nature of firm performance. Pointing out an issue that managers mostly        sense one way or another, brings about frictions firms not necessarily desire. Looking at older research of        Morck, Shleifer and Vishny (1989), they actually suggest that industry performance is filtered out of        dismissal decisions, which additionally triggers the question whether this is a phenomenon that only        applies   to   younger   firms. 

In order to grow their company, founders have to make crucial decisions in very early stages.        Capital structures will haunt founders until the end of the days, because they imply control issues. Some        founders therefore choose to base their financing decisions around control, whereas others choose to        neglect   this   issue   and   first   grow   the   company.  

for the investor. Hart (1995) describes the feature of securities to be not only limited to cash flows, but        also includes other rights that these securities give access to, amongst others the right to vote for directors.        These rights become critical to acting managers, because their behavior is determined by the people who        control their job. In the end, dividends are paid because shareholders control the directors and creditors        are   paid   because   otherwise   they   can   demand   their   collateral   (La   Porta   et   al.,   1998). 

News coverage around young firms and startups picked up increasingly and developed into a        trend. Many founders want to be part of the sharing­economy, be the new Uber, Facebook, Google or        AirBnB. The impact of young firms and the trend around it has been growing, fueled by venture capitalist        and early series funding of high potential firms, even without revenues or tangible assets. While those        crucial decisions around financing in young firms mostly happen in the period before public offering, the        capital structure has to be carried with them during the process of going public. The longer the process        takes, the more are shares of managing owners and founders watered down. With that in mind, looking at        venture funding betting on exponential growth of cash­flows, Modigliani and Miller’s findings do not        hold anymore, triggering a new problem of being a young firm, disproportional cost of debt.        “Pre­Revenue” companies with billion dollar valuations (so­called “unicorns”) are not the exception        anymore. Even in 1976, Jensen and Meckling already argued that they believe ”the existence of agency        costs provide stronger reasons for arguing that the probability distribution of future cash flows is not        independent   of   the   capital   or   ownership   structure”,   leading   to   agency   costs. 

The question I ask here is whether it is really a clever decision to give away shares and ownership        early, to fuel fast growth or create more sustainable and potentially flat growth, risking to take too much        time, but be part of the decision making process when the own firm is in the position that the founder        always dreamed about. And how does that differ in between regions? If there are differences, what are        those? La Porta et al. (1998) argue that the intrinsic characteristics inherent to the securities of investors is        not equal across the world. According to their findings, capital structure differs around the world because        of differences in enforcement. This raises the question: Do the findings of La Porta et al. still hold for        determinants   emanating   from   country   regulatory   differences   and   are   they   applicable   to   young   firms?  

just anecdotal evidence to what motivates founders and how they keep track of their ownership and        exercising voting rights, I want to dive into a more generalized view by including the full sample of        young companies that emerged after the dot­com bubble in the most developed regions in the world, the        US   and   Europe.   Is   it   really   worth   passing   on   early   money,   just   to   bootstrap   the   way   up   to   glory? 

  “Lots of companies don’t succeed over time. What do they fundamentally do wrong?                          They usually miss the future. I try to focus on that: What is the future really going to                                    be? And how do we create it? And how do we power our organization to really focus on                                    that and really drive it at a high rate?” ­ Larry Page, CEO Google (FT, 2014) on long                                    term orientation, intrinsic motivation and the resulting inner power of founders who are                          free   to   chase   their   dreams   within   their   own   company. 

This study revolves around the key requirements set out by the master degree that it is intended to        complete. It follows the papers of Jenter and Kanaan (2015), La Porta et al. (1998 and 2001) as well as        large parts of the methodology and structure of Gönenç and Scholtens (2017). The papers employed serve        individual purposes that are merged within this paper. While Jenter and Kanaan (2015) provide insights        into the determinants of CEO turnover based on the performance of the firm the CEO manages, the papers        of La Porta et al. (1998 and 2001) provide the international fundament that seeks to explain differences        and/or similarities between the regions of the United States and Europe. Those papers introduce the        variables   of   investor   rights   and   legal   origin. 

  The main research question I thus define as follows:  What is the effect of having                  management as majority shareholder(s) on the performance of the young firm in                        different   environments? 

confirming H5. Surprisingly, I found results partly opposing H6, namely negative effects of creditor rights        on firm performance, even though they are rather low and weak. On the other hand, stronger shareholder        rights have a positive effect on firm performance, thus also just partly confirming H6 and providing        support to the findings of La Porta et al. (2001). This study contributes to the literature by giving insights        into effects of who owns companies and how this is in turn affected by the institutional framework, taking        the general findings of La Porta et al. (1997, 1998, 1999a, 1999b, 2001 and 2008) to a further detailed        level. I moreover confirm most of these findings and provide food for thought regarding the current        situation   in   market   valuation   for   a   very   specific   type   of   firms,   young   firms. 

To the best of my knowledge there has been no study trying to find out whether firms perform        better if they are owned by their managers and whether that differs with the institutional framework that        the company is situated in. This is the gap this study is supposed to fill with a fresh dataset of companies        founded since 2001, while focusing on publicly listed firms from the US, Europe and together, to test        effects in between. In order to investigate the research question, I make use of analyses of variance as        defined by Mann and Whitney as well as multiple types of regression analyses and panel data to dig        deeper into the effects of individual variables as well as investigate the effects of other variables affecting        the   findings. 

2   Literature   Review 

Underlying this research is the agent, as in the manager(s), being the performance determinant of        firms. Their impression of long­term ability to strategize and build their ideas depends on job safety,        which I argue to create costs for non­owners, while owners of firms can focus on the job instead of        building safety nets, leading to higher performance in firms owned by its managers. The overall approach        takes strategies by other papers that I then apply to the topic of this paper. To avoid excessive repetition in        literature review and hypothesis argumentation, this section focuses on the broad picture of available        literature and outlines the factors that are relevant for this study per topic by weighing off findings and        giving a wider impression. Specific findings including their hypothesized direction of impact applied to        firm performance will mostly be laid out in section four “Hypotheses and Empirical Models”, which        partly requires assembling multiple topics for the argument, hence requires to be separated from this        literature   review.   Following   literature   builds   the   foundation   of   this   paper: 

2.1   Triggering   Agency   Costs   ­   CEO   Turnover   decisions 

The decision to retain or fire a CEO is often outside the control of managers themselves and that        is because of firm performance outside managerial control (Jenter and Kanaan, 2015), where managers        get blamed for exogenous shocks on performance they can not control. This blame may come from        outside pressure such as shareholders (Fisman, Khurana, and Rhodes­Kropf, 2014), or the inside, whereas        boards appear to be filtering out market shocks (Gibbons and Murphy, 1990; Kaplan and Minton, 2012).        Other studies generally find that turnover decisions are filtered out by market shocks (Barro and Barro,        1990; Morck, Shleifer, and Vishny, 1989), yet not in those with older samples (Warner, Watts, and Wruck,        1988).  

performance and turnover are potentially related, but one does not necessarily cause the other (Comte and        Milhal, 1990). In the light of these circumstances, uncertainty created by conditions out of managerial        power may inhibit managerial performance and lead to agency problems originating from the        circumstances   and   self­protection. 

Interestingly, most literature on CEO turnover does not provide pay­for­performance as        determinant for turnover, namely rather selecting the “optimal” person (Jovanovic, 1979), a type of match        between the candidate and firm (Jenter and Kanaan, 2015). Most literature in the 90s does not focus or        provide good explanations for turnover in good times (e.g Aggarwal and Samwick, 1999; Murphy, 1999).        Under these circumstances CEO compensation surprisingly does not influence the argumentation of this        paper, excluding the paper of Casamatta and Guembel (2010). They argue that legacy potential        significantly determines CEO compensation, strategy and turnover Such legacies then increase        replacement costs and thus strengthen certainty of managers, long term ideas and implicitly then        strengthen their position, leading to similar effects argued to be an important performance determinant of        managerial owners. Legacies are, however, not the norm. This rather provides reason to believe that        family­firms   play   an   important   role   in   describing   ownership   effects   on   firm   performance. 

2.2   Managerial   ownership   and   firm   performance 

Relevant studies regarding managerial ownership and firm performance find a curvilinear        relationship of firm performance and Tobin’s Q (Barnhart and Rosenstein, 1998; Morck, Shleifer, and        Vishny, 1988; McConnell and Servaes, 1990). Stulz (1988) found that an increase in managerial voting        rights leads to an increase in premium offered for takeovers, increasing shareholders wealth. Furthermore,        Morck, Shleifer, and Vishny (1988) find Tobin’s Q to be increasing with larger ownership of board of        directors, most importantly over the 25% threshold. Chen and Yu (2012) go further to base on Shleifer &        Vishny’s findings (1994) for the relevance of ownership structure, that this is precisely what determines        agency problems. Fama and Jensen (1983) argued that ownership of management in firms is        counterproductive due to inability to supervise, which Morck, Shleifer, and Vishny (1988) refute. They        also specifically point out the decrease in Tobin’s Q when the firm is run by a founding family member        compared to outsider, yet only for older firms and second generation family firms. This is of vital        importance for the following section and the line that this paper draws between family­firms, managerial        owners   and   the   relevance   of   findings   in   family­firm   research. 

2.3   Family   firms   and   its   comparability   to   managerial   ownership 

Research on family firms is widely available (Anderson and Reeb, 2003; Miller et al, 2007;        Villalonga and Amit, 2006) and I argue that family firms are very similar to firms owned by the        manager(s), much like Chen and Yu (2012). While there is no commonly accepted consensus as to what        precisely constitutes a “family­firm” (e.g. Kraiczy, 2013; Westhead and Cowling, 1998), two common        uses emerged. Firstly firms with family CEO as successor in at least the second generation (Bennedsen et        al., 2007) and secondly those with family ownership (Anderson and Reeb, 2003; Cronqvist and Nilsson,        2003; Miller, 2013; Villalonga and Amit 2006), whereas Anderson and Reeb (2003) and Villalonga and        Amit (2006) go as far as defining a family firm as those with members of founders’ family or the founder        himself in top management or as major shareholder, without specifying a threshold. This description        builds the foundation for comparing managerial owners to family firms, as such a first generation family        firm. Reversing this argument, managerial ownership would be defined as a family firm. Thus, I argue        family­CEOs are similar or equal to founders and others managerial owners. In that case, characteristics        of   family­firms   are   arguably   features   of   managerial   owned   firms   as   well.  

Benefits of family firms are lower agency cost, reducing those stemming from the separation of        control and ownership (Jensen and Meckling, 1976), and the principle of making long­term decisions        (Gómez­Mejía et al., 2011). The authors found this to be especially significant in firms with concentrated        ownership, which provides the opportunity to push the above mentioned ideas through that underlie        family­firms. Additionally, family­CEOs may behave altruistically with their family in mind (Schulze,        Lubatkin and Dino, 2002) and controlling families are not found to expropriate wealth from minority        shareholders (Croci, Gönenç and Ozkan, 2012), substantiating the similarities between family firms and        managerial   owners   who   are   thus   interested   in   firm   performance.        2.4   Implicit   forces   on   managers,   founders,   family­   and   widely­held­firms   

they were unable to enforce maximization of value, because control is concentrated in the hands of        managers. Jensen and Meckling (1976) then further developed this theory into the principal­agent theory        that constitutes the basis of the now known problem. According to them, it is in the interest of the both        principal and agent to maximize their own interest instead of the others and thus an agent in the form of a        manager does not always work towards the interest of the principals. The work a manager does is then        influenced by his or her own perception of what is the best to save the job. Thus, according to Adams and        Ferreira (2009), shareholders prefer risky project to increase wealth, whereas managers are trying to        reduce   taking   risks   that   could   put   them   in   a   bad   position. 

Stewardship theory differs in the structure of control. While agency theory underlies a separation        of board and CEO, who is put on track by incentive schemes set out by the board, this separation does not        exist in stewardship theory, putting the CEO in full charge, acting as “steward” of the firm. Donaldson        and Davis (1991) find significant improvements in ROE of firms that have combined chair and CEO        positions, compared to companies with separated ones. This separation exists in the same sense when        firms   are   owned   by   their   managers   instead   of   widely   held.  

On the other side this effect of stewardship may be weaker depending on institutional context,        moving to the downsides of family ownership, much like managerial owners could. Even though La Porta        et al. (1999 and 2000) did not explicitly mention the idea, I would like to use these papers to show in what        direction I am pointing here, taking findings of legal origin and the investor rights effects to demonstrate        performance   effects.  

The above mentioned agency problems may, however, also be prevented by controlling        shareholders other than managers as controlling shareholders themselves. Research of Shleifer and Vishny        (1997) as well as La Porta et al. (1998) suggest that such controlling shareholders are able to implement        better controlling mechanisms to balance out governance issues to avoid bad decisions of the firm, much        like the governance mechanisms described in Lin and Hu (2007), emanating from families as controlling        shareholders. Different to agency in families who do not expropriate from the firm (Croci, Gönenç and        Ozkan, 2012) in this case the authors write that it may well be that controlling shareholders act against        other shareholders of a firm. These findings may emphasize again the differences in issues related to        control   and   (long­term)   motivation   of   the   controller. 

Considering the overall picture that I use to proxy family firms for managerial ownership        performance, the relevant points made are those originating from the overall performance determinants of        ownership by the managers. Firstly, control issues leading to uncertainty avoidance. Secondly age, namely        founders and not second­generation or later stage family firm managers. Those aspects firm up the basis        of   this   study   relating   to   family­firms. 

2.5   Entrenchment   as   performance   inhibitor   for   not­owners 

who have not been founder, to engage in entrenchment, especially their intermediate years. Additionally,        their study shows weakening effects over time, which in turn expressly underlines the importance of a        safe   position   and   manager   concerns   of   uncertainty. 

2.6   Regional   differences   and   investor   protection 

Different ownership structures are commonly found in between the regions of the US and Europe,        for example family control is comparatively dominant in continental Europe compared to the United        States (Faccio and Lang, 2002). Multiple papers of La Porta et al. (1998, 1999a, 1999b, 2000, 2001 and        2008) go into more detail of how individual companies finance themselves, what capital structures they        are   using   and   what   determinants   are   responsible   for   these   outcomes. 

La Porta et al. (1998) found strong differences between the legal background of countries and        their legal layout of investor protection. The separation is found to be especially strong between common        and civil law countries, with weakest investor protection in countries with French legal origin and        strongest in those countries whose legal system originates from traditions of the United Kingdom. More        specifically, they found differences in ownership structures depending on the ability of an investor to        enforce their rights. Two types of protection emerged, the first being creditor rights, the second        shareholder   rights.  

Shareholder rights are measured by the authors as the so­called “anti­director­rights”, which        provides an indicator of the ability of minority shareholders to take part in the decision making process        and how the law protects these rights to vote. The index is made up of six dummy variables providing a        range of values from 0 to 6, the latter being the strongest, representing individual rights that the investor        may   use.   One­share   one­vote   practices   are   not   relevant   in   this   study   due   to   the   countries   in   the   sample.  

Next to shareholder rights, the papers of La Porta et al. explain creditor rights, which is again a        number of (five) dummy variables representing a total value, in this case ranging the outcomes from 0 to        4. The difference between the two lies, as mentioned in the introduction, in the security of the investor.        For creditors the security is collateral in the firm's assets and for shareholders their voting rights, whereas        there are more different types of creditors with largely varying aims. The essence is, however, that        creditor security is based around the collateral claim. Making reclaiming of collateral in default        comparably   difficult,   would   disincentivize   an   investor   to   invest   (La   Porta   et   al.,   1998)   . 

these investor rights. Looking at differences in enforcement for creditor and shareholder rights then        explains differences of capital structures in­between countries. This leads to La Porta et al. (1999a), who        partly oppose the picture that Berle and Means (1932) painted of separation of control and widely held        ownership, finding relatively few firms which are widely held outside the United Kingdom and the United        States. To give another example, Edwards and Fischer (1994) find Germany to have strong banks, but a        weak stock market, which is supported by the findings of La Porta et al. (1998) rating Germany with        relatively strong creditor rights and relatively weak shareholder rights, leading to relatively more debt        financing   versus   equity   financing   for   German   firms. 

The key takeaway of this section is the divergence of incentives in each country emanating from        the law and enforcement within its borders, which spills over to the market valuation of firms governed        by these countries. The legal origin that persists in the countries is a strong determinant of these        outcomes. The papers of La Porta et al. emphasize that countries differ and that this difference has an        impact on firms and corporate finance. I would also like to emphasize that incentivization is the red line        that leads through this study and provides the push and pull mechanism that finally leads to performance.        These mechanisms are involved throughout all parties, from binary legal origin providing the direction; to        individual countries using the direction and creating a unique framework; to firms working with the        framework and adapting their capital structure to accommodate their needs; and then the firm’s managers        who are bound by the framework set out by countries and firms, trying to extract as much as possible for        personal needs, loosely adapted from the principle maximum utility function: “if everyone thinks of        themselves,   everyone   is   sought   after”. 

3   Data   and   Methods 

Following Croci, Doukas and Gönenç (2011) and Gönenç, Hermes and van Sinderen (2013), I        collect the data from the ORBIS database on all information I need. Especially the ability to distinguish        between ownership thresholds is convenient for dummy variable creation. I apply a three step approach in        order to increase validity and decrease potential measurement errors. After the first step, data collection in        ORBIS, I secondly, edit the data in EXCEL, which leads to thirdly, the final data analysis in STATA.        Interestingly, I find two datasets of almost equal size. A distribution of countries included in the dataset        can   be   found   in   table   A3.      A   distribution   observations   per   countries   can   be   found   in   figure   A1 

Following the suggestions from Chen and Yu (2012), managerial ownership is created as a        dummy variable where managers either have full (or ultimate) control or not. To do so, I apply filters in        ORBIS for either >50% ownership of managers or <50% ownership of managers. These datasets are then        merged   per   country   and   later   for   the   whole   set. 

3.1   Data   collection   process 

For the international perspective of the research, to obtain comparable data, the same settings are        downloaded into four different sets (each region and each ownership type). The main reason for doing this        is to have four sets that can be analyzed individually and put together into one to analyze the fifth as a        whole. Additionally, Orbis has better internal measures to distinguish between ownership types in their        search strategy options than would be possible to evaluate by hand or judgement of other variables        provided   by   Orbis.   Hence,   following   search   strategy   is   pursued: 

1. Firms are excluded that are in the financial service, gambling and betting, insurance, reinsurance,        (pension) funding, those that are similar and those auxiliary to these services because of their        potentially distorted Tobin’s q values. Their complete code according to SIC categorization (SIC,        2016)   is   excluded. 

2. The year of incorporation is set to between 2001 up to and including 2015, excluding companies        for which the year of incorporation is unknown, to be precise. Data for 2016 is excluded, because        most   of   the   data   is   not   available   yet. 

This concludes the general search strategy that applies to all of the four datasets. Following selections are        created   once   for   each   combination: 

1. The two possible regions are first, the geographical region of the United States, which is at the        same time one political region. This is important to mention, because for the counter variable, the        political region of the all areas that are considered as belonging to the European Union in a wider        spectrum, namely western and eastern Europe as well as Scandinavia, the Baltic, Nordic and        Balkan states are chosen. Currency issues should not be relevant within the framework of this        research as the performance measure, Tobin’s Q, is merely a ratio. Hence, this measure is        independent   of   currencies. 

2. The possible ownership scenarios are twofold here; first scenario are managers owning less than        50% of the business and the second scenario is managers owning more than 50% of the business.        Orbis provides this selection criteria in their selections strategy options and for this I include        companies for which the manager is also the ultimate owner only for companies >50%        managerial   ownership. 

3. Only   absolute   year   values   for   annual   data   are   used   and   all   values   are   denominated   in   US   dollar.   

Final size of datasets is the following: Firstly, US firms with managers owning more than 50%;        before cleaning raw data size is 409 firms. Secondly, US firms with managers owning less than 50%;        before cleaning raw data size is 1117. Thirdly, European firms with managers owning more than 50%;        before cleaning raw data size is 279. Lastly, European firms with managers owning less than 50%; before        cleaning 997. The combined set with added dummy variables for the two different specifications        (ownership and region) includes a raw amount of 2802 firms. The absolute final sample size is 2005        firms. The US dataset includes 1131 and the European dataset 878 firms. The difference of 4 firms stems        from   double   counted   firms   that   are   split   in   two,   but   run   under   the   same   firm   name. 

Finally, I insert the original datasets of La Porta et al. (1998 and 2008), to obtain the        cross­country   variables   of   legal   origin,   anti­director   rights   and   creditor   rights. 

3.2   Treatment   of   missing   data 

not known for what reason no last value is listed. This provides a more realistic number of firms that are        actually in the dataset. This is done by creating a function that gives an output of either 0 (for available        data in 2015) or 1 (for no data available in 2015) and then filtering by 1, which rows are deleted.        Secondly, those that arise because of “late IPO”, namely stemming from late public offering that results in        available data from a later point as this research includes only young firms and not all are going public at        the same time. In these cases regularly data is available from that point on, but not before. This        information is only necessary for panel data. Thirdly, values missing for specific years. It is rare but does        happen that a single year is missing. In these cases the average of the year before and after is taken. This        information is also only needed for panel data and not for the main test, Mann­Whitney U test.        Additionally,   two   extreme   outliers   were   dropped.  

3.3   Treatment   of   outliers 

Only applied to the non­panel data tests, to finalize the data treatment process and avoid outliers        affecting results, trimming to the 5th and 95th percentile is being conducted as the extremity of some        values does not reflect the overall picture of the dataset and it may well be that the data collected is at        times without foundation. I chose trimming in place for winsorizing, because a test with winsorizing led        the medians that replaced the extreme values still be outliers due to the extreme outliers that I want to        correct for. It is also my intention to test for realistic results that others would obtain as well with different        datasets or in different regions. Hence, it appears obvious that this dataset needs to be trimmed. For the        joint dataset the lower threshold is .09, the higher 224.95, leaving 2005 companies. For the European        dataset the lower threshold is .083, the higher 5.62, leaving 878 companies. For the US dataset, the lower        threshold is .1, the higher 651.48, leaving 1131 companies. I left the dataset I use for panel data as is and        only   trimmed   values   for   robustness   and   sensitivity   tests. 

3.4   Empirical   methodology   

In my empirical analysis, I use two measures of firm performance: Tobin’s Q and the natural        logarithm of Tobin’s Q. Adding the natural logarithm of Tobin’s Q gives me the opportunity to normalize        the distribution of the dataset and obtain elasticity results between the variables when conducting multiple        regression   analysis.  

3.5   Dependent   Variable   ­   Tobin’s   Q   and   LN   Tobin’s   Q 

The dependent variable is a proxy for firm performance. For this research, I use the natural        logarithm of Tobin's Q (LNQ), which is market value/total assets and used commonly as a proxy in        similar studies (e.g. Barnhart and Rosenstein, 1998; Gönenç and Scholtens, 2017; La Porta et al., 2001;        Morck, Shleifer and Vishny, 1988). Additionally to following similar studies on ownership, I argue that        using Tobin’s Q as a measure of intrinsic value of a firm reflects future potential better than other types of        accounting based measures because of the young age of firms. Especially in the current times it is        relatively common to have large pre­revenue companies that live off a potential without actual revenues        such as Facebook or Google for a long time, to name prominent examples. Therefore, using ROA or ROE        as firm performance indicators would be wrong, which will be shown and inferred upon in robustness        tests. Note that the assumption holds that Tobin's Q is a measure that implies time (as in expectancy)        within its value, therefore the sets for last years values and panel data should be similar enough to obtain        the same results, which is also found in the robustness tests. To be comprehensive, the main tests will still        be   using   panel   data   analysis. 

3.6   Relevant   Independent   Variables 

The main independent variables are managerial ownership (OWNER) and region (REGION). For        both variables I created dummy variables where the dummy takes one for non­managerial owned firms        and zero otherwise as well as the region dummy, which takes the value for zero if the firm is located in the        US and one for Europe. This separation is based on findings of different concentrations of ownership and        family owners and provides a benchmark for the following variables. To test the international perspective,        this paper follows the papers of La Porta et al. (1998, 1999 and 2001), who developed creditor rights        scores and categorized the legal origins of the countries involved in this research. Within the framework        of this research, investor rights (CR and ADR) are dealt with as a dummy for the individual creditor rights        levels. The same procedure applies to legal origin (CIVIL and COMMON). The reason behind this is that        creditor rights is not a continuous variable in itself. While there is strength indicated by having a smaller        number, the individual dummies that make up the creditor rights value may not be of equal weight (La        Porta   et   al.,   1998). 

3.7   Control   Variables 

Previous research shows that other variables may also influence the outcome of this type of        research. In the regression analyses at a later stage, I therefore control for multiple factors that may        influence the dependent variable firm performance and the independent variables, managerial ownership        and   region.   These   control   variables   are   categorized   into   size   and   country­level   variables.  

With respect to the size­level control variables, I control for firm size (FIRMSIZE), measured as        the natural logarithm of market capitalization. Another firm size proxy is controlled for, employee “size”        (EMPLOYEES), measured as the natural logarithm of number of employees. Further, to include the        managerial aspect into firm size and the focus on employees, I control for number of managers        (MANAGERS)   and   again   use   the   natural   logarithm   for   this   measure. 

Additionally, I will use controls for industry and test with switching firm performance proxies to        see whether the Tobin’s Q is the driving factor instead of other firm performance proxies for the results.        To do so, I use the Standard Industrial Code categorization that can be found in ORBIS. Due to size and        amount   of   variables   within   the   table   as   well   as   their   results,   those   tests   are   moved   to   robustness. 

3.8   Variance   analysis   models 

In order to test whether there are actually significant differences between the means of different        dependent and independent variables, I conduct Mann­Whitney U tests. A similar approach has been        conducted in Gönenç and Scholtens (2017). For hypothesis 1, I check for significant differences between        Tobin's Qs under managerial and under outside ownership. Further, I want to test whether there are        significant differences in means that predict higher values for managerial ownership, compared to outside        ownership, which is hypothesis 2. Additionally I test for variances between regions for managerial        ownership, followed by testing whether one region has a stronger stronger effect of managerial ownership        on Tobin's Q. The selection of this test originates from the significant tests for homogeneity of variance        (Levene’s test) and normality (Skewness/Kurtosis and Shapiro­Wilk) for all datasets and for both each        Tobin's   Q   as   well   as   the   natural   logarithm   of   Tobin's   Q.  

3.9   Log­Log   regression   models 

similar papers again (e.g. Barnhart and Rosenstein, 1998; Gönenç and Scholtens, 2017; La Porta et al.,        2001; Morck, Shleifer and Vishny, 1988). The data utilized within these equations are panel data, which        includes static information that is time­invariant (legal origin, etc.). Throughout the models, I use the        natural logarithm of Tobin's Q (LNQ) as dependent variable. Due to the still extreme values of Tobin's Q        from the United States, further trimming may not be ideal and not be equally possible, hence the        logarithmic   transformation   to   normalize   distribution.   The   methods   are   regressed   using   random   effects.   

3.10   Random   Effects   model 

To avoid STATA dropping time­invariant variables out of the dataset due to collinearity with the        ID, I use random effects models instead of fixed effects. Most of the dependent variables used are        time­invariant and fixed effects do not allow time­invariant variables. Additionally, it is possible that        differences across the firms in the sample have some influence on firm performance. To ensure that the        results   are   valid,   random   effects   are   used   across   firms. 

Table   1 

Definition   of   relevant   variables,   their   respective   measurement   and   part   within   this   study.  Variable  Unit   of   Measurement  Usage  Description 

LN   Tobins   Q  Ratio  Dependent   Variable  The   natural   logarithm   of   Tobins   Q   as   described   below  Tobins   Q  Natural   Logarithm  Alternative   Dep. 

Variable 

ORBIS'   ratio   of   market   capitalization/assets;   Confirmed   by   the   data   specialist   of   ORBIS   ­  Bureau   van   Dijk 

Ownership  Dummy  Independent   Variable  1   if   the   firm   is   owned   by   outside   shareholders   (managers   <50%   ownership)   and   0   if  managers   own   company   (>50%   combined) 

Region  Dummy  Independent   Variable  1   if   the   firm   is   from   the   Europe   and   0   for   companies   from   the   United   States 

Creditor   Rights  Categorical  Independent   Variable  Strength   of   creditor   rights   as   defined   by   La   Porta   et   al.   (1998),   ranging   from   0   to   4;   0   being  low,   4   being   high   investor   protection 

Shareholder   Rights  Categorical  Independent   Variable  Strength   of   shareholder   rights   as   defined   by   La   Porta   et   al.   (1998),   ranging   from   0   to   6;   0  being   low,   6   being   high   investor   protection 

Legal   Origin  Categorical  Independent   Variable  Legal   origin   of   firm   country   as   described   in   La   Porta   et   al.   (1998)  LN   Market   Cap  Natural   Logarithm  Control   Variable  Market   capitalization   of   firm 

LN   Employees  Natural   Logarithm  Control   Variable  Number   of   employees   in   firm   (estimation)  LN   Managers  Natural   Logarithm  Control   Variable  Number   of   managers   in   firm 

4   Hypotheses   and   Empirical   Models 

In this study I focus on publicly listed firms that incorporated after the dot­com­bubble 2001,        which I call “young firms”. I use data of firms from the United States and Europe. The structure applied is        a funnel approach. In the wake of having a large amount of comparable and potentially pivotal proxies for        the international perspective, empirical testing will be done stepwise, introducing variables successively        and adopt different combinations to better comprehend their influence. Using this strategy aims to        improve the validity from a reader’s view. In the following I use the findings outlined in the literature        review to point into a direction, which then creates hypotheses. Additionally, for ease of read and to        prevent repetition of theory, I include the regression equations and analyses methods following from the        hypothesis, whose methodology is explained in section three and is applied in section five. This way it        should become clear immediately how this section (four) is put into practise in the following section        (five). A definition of variables can be found in Table A1 and a description of the variables utilized in the        model can be found in the respective table descriptions. Equations using analyses of variance testing are        denoted   (1)   thru   (5)   and   panel   data   regressions   are   denoted   (6)   thru   (13). 

4.1   Null   Hypothesis 

4.2   Ownership   Difference   and   Direction   Model   and   Hypotheses 

As discussed before, there are multiple forces affecting behavior of the agents, which leads to the        hypothesis of difference between the two groups. The forces of ownership types mostly lean on tacit and        soft facts. Principal­Agent theory (Jensen and Meckling, 1976) provided evidence that managers as agents        not always work toward the same goals as their principles, especially if governance does not align these.        Stewardship theory (Donaldson and Davis, 1991) argues too, that there are differences in firm        performance when goals are automatically aligned by having the manager in full charge. Both agency and        stewardship theory are leaning on Berle and Means (1932), that the self­interest of managers combined        with their ability to set directions, may affect firms. Additionally, Morck, Shleifer, and Vishny, (1988),        Chen and Yu (2012) and Fama and Jensen (1983) provide plenty evidence that firms with different types        of owners are not performing equally. Due to the effects of agency cost, stewardship theory and past        research on family firms, especially insights into the comparable first generation family firms, I argue that        there are also differences when managers own a firm, much like there are differences when families own        firms,   compared   to   non­family   firms.   Consequently,   I   hypothesize   the   following: 

H1:  There are differences in firm performance between firms owned by managers and those who are                              not   owned   by   managers 

Hence, for hypothesis 1, I check for significant differences between Tobin's Q under managerial        and   under   outside   ownership: 

  μ  Q_{1 * M}anagerialOwnership =   Q

_/

that goes the “extra mile”, outperforming others, consequently creating a positive effect. These findings        are heavily inspired by findings on family­firms, who have lower agency costs (Jensen and Meckling,        1976), think more long­term (Gómez­Meija et al., 2011), resulting in a potentially more altruistic course        of conduct (Schulze, Lubatkin and Dino, 2002) and still are not found to be expropriating wealth from        minority shareholders (Croci, Gönenç and Ozkan, 2012). Rounding up the argumentation, agents may        entrench themselves into the company, with exclusively negative repercussions, creating another type of        friction through agency costs (see section 2.6). By implication, I argue that on one hand negative effects        of agency costs and on the other hand positive effects of stewardship benefit one side more than the other,        not only explaining that the groups are different, but also that there are significant firm performance        differences   in   favor   of   those   that   are   owned   by   the   managers.   Thus,   I   hypothesize   that: 

H2:  Managerial   owned   firms   perform   better   than   outside   owned   firms 

Hence, I want to test whether there are significant differences in means that predict higher values        for   managerial   ownership,   compared   to   outside   ownership,   which   is   H2: 

  μ  Q_{1 * M}anagerialOwnership> μ  Q_{2 * O}utsideOwnership    (3) 

Further, I argue that there is a significantly positive and economically relevant relationship for        ownership on firm performance in a simple model that serves as benchmark for following tests, leading to        following   panel   regression   equation,   estimated   using   random   effects: 

  LN Q   _i,t =  α   ₀ +  γ1OW N ER  ′_i +  γ2REGION   ′_i +  (c _i+ u  )  _i,t   (6) 

4.3   International   Perspective 

Europe (4.3.1), the legal origin hypotheses follow (4.3.2), finalized by investor protection, which is both        creditor   and   shareholder   rights   (4.3.3). 

Even in the hypothetical case of not finding differences in firm performance by purely separating        ownership types in the whole dataset, these findings may still be swayed by the regions used. If there are        differences in ownership effects on firm performance, but with different directions, they would not be        visible in the tests before, balancing each other out. Hence, the international perspective testing adds        another   significance   level   and   robustness. 

4.3.1   Ownership   Country   Difference   and   Direction   Model   and   Hypotheses 

Additionally to ownership, I argue that there are differences between the region in which the firm        is located. I derive this argument from the same studies that focused on family firms and managerial        ownership, who also limited or compared their data sets to regions. However the main focus for this part,        using the plain regional separation, serves as methodological and theoretical benchmark for the following        sections   and   the   separations   according   to   La   Porta   et   al.   (1997,   2001   and   2008).   Here,   I   hypothesize   that:   

H3:  There   are   differences   between   managerial   owned   firm   performances   in   US   and   European   firms 

Hence, I want to test whether there are significant differences in means of managerial ownership        in   the   United   States,   compared   to   managerial   ownership   in   the   Europe,   which   is   H3: 

  μ  Q3 * ManagerialOwnershipU S =   Q

/

provide a ground to argue for international differences. The basic panel regression is estimated using        random   effects: 

  LN Q   _i,t =  α   ₀ +   γ1OW N ER  ′_i +  γ2REGION  ′_i +  γ3OW N ER′_{i* R}EGION  ′_i +  (c _i+ u  )  _i,t   (7) 

Leading further, I argue that the effects of managerial ownership are stronger for firms owned by        managers   in   the   United   States,   again   serving   as   benchmark.   Thus,   I   hypothesize   that: 

H4:  Managerial   ownership   effects   are   stronger   for   US   firms   than   European   firms 

Hence, I want to test whether there are significant differences in means that predict higher values        for   managerial   ownership   in   the   US,   compared   to   managerial   ownership   in   Europe: 

  μ  Q_{3 * M}anagerialOwnershipU S> μ  Q_{4 * M}anagerialOwnershipEurope    (5) 

4.3.2   Legal   Origin   Models   and   Hypothesis   

Additionally to ownership direction and the regional hypothesis, I want to go into more detail and        argue that the legal origin of a company is a performance determinant of a company. In the legal origins        theory of La Porta et al. (1997 and 2008), the authors argue that two different types of legal tradition,        common and code law, affect economic outcomes based on their legal specific determinants; better        protection of investors, less government regulation, less government ownership and better enforcement        through judicial systems that are more independent and less formalized. In the outlined scenario, common        law countries outperform code law countries. The stronger protection of investors that La Porta et al.        found in common law countries determines a better breeding ground for investors with better developed        capital markets (La Porta et al., 1997), because enforcement of their rights incentivizes these investors to        finance firms. On the other hand, weaker rights in for example french law somehow pose a bottleneck,        which is supported by the findings of higher concentration of ownership in french civil law countries.        Following   these   findings,   the   fifth   hypothesis   is   formulated   as   follows: 

H5:  The effect of managerial ownership firm performance is positive for firms located in countries with                             

Hence, I am creating dummy variables for each legal origin to obtain individual results, which        can then be assessed upon economic relevance and significance. To prevent overloading this model with        too similar variables, I replace REGION with the two variables, COMMON and CIVIL to be region        indicators: 

  LN Q   i,t =  α   0 +  γ1OW N ER′i+  γ2COM M ON  ′i + γ3CIV IL    ′i +  (c i+ u  )  i,t   (8) 

Further, to assess the specific effect to managerial ownership, I again create an interaction        variable of ownership with the other relevant independent variable, common law and civil law,        respectively. To further substantiate potential findings, I include the control variables FIRMSIZE,        MANAGERS   and   EMPLOYEES   to   determine   the   impact   of   legal   origin   on   firm   performance: 

  LN Q   _i,t =  α   ₀ +   γ1OW N ER′_i+  γ2COM M ON  ′_i +  β3F IRM SIZE′_i,t+  β4M AN AGERS    ′_i,t  

β5EM P LOY EES   γ6OW N ER OM M ON (c    )   +   ′_i,t +   ′_{i* C} ′_i+   _i+ u_i,t  

(9) 

  LN Q   _i,t =  α   ₀ +   γ1OW N ER′_i+  γ2CIV IL  ′_i +  β3F IRM SIZE′_i,t+  β4M AN AGERS    ′_i,t  

β5EM P LOY EES   γ6OW N ER IV IL (c    )   +   ′_i,t +   ′_{i* C} ′_i+   _i+ u_i,t  

(10) 

4.3.3   Creditor   and   Shareholder   Rights   Models   and   Hypothesis 

Additionally to investor protection and legal origins, the missing puzzle piece following from the        famous papers of La Porta et al. (1997, 1998, 1999a, 1999b, 2001 and 2008) are investor rights. While the        regional separation model differs from code vs common law mainly in switching the United Kingdom        from one side to the other (compared to dummy REGION), investor rights are specific to their respective        countries. Creditor rights are ranging from 0 to 4 and shareholder rights are ranging from 0 to 6, each        indicating stronger rights of investors with increasing values (La Porta et al., 1998). Further, the authors        explain weaker investor rights to penalize firms with lower valuations, which is crucial to this study, using        Tobin's   Q   as   firm   performance   proxy.   Consequently,   I   hypothesize: 

In the following models, CR are used as continuous variable as the methodology of La Porta et al.        (1998) may be laid out. A high value for creditor rights being strong, a low value of creditor rights being        weak. Hence, the higher the CR coefficient, the stronger the effect of creditor rights, while the sign        indicates the direction, e.g. negative signage indicating weak creditor rights to be bad for firm        performance and vice versa. Further, to assess the specific effect to managerial ownership, I again create        an interaction variable of ownership with the other relevant independent variable, creditor rights (CR) and        shareholder rights (ADR), respectively. To further substantiate potential findings, I include the control        variables FIRMSIZE, MANAGERS and EMPLOYEES to determine the impact of investor rights on firm        performance: 

  LN Q   _i,t =  α   ₀ +   γ1OW N ER′_i+  γ2CR  ′_i +  β3F IRM SIZE′_i,t+  β4M AN AGERS    ′_i,t  

β5EM P LOY EES   γ6OW N ER R (c    )   +   ′_i,t +   ′_{i* C} ′_i+   _i+ u_i,t  

(11) 

To test the effects of shareholder rights and obtain directly comparable results, I switch creditor        rights   with   shareholder   rights 

  LN Q   i,t =  α   0 +   γ1OW N ER′i+  γ2ADR  ′i +  β3F IRM SIZE′i,t+  β4M AN AGERS    ′i,t  

β5EM P LOY EES   γ6OW N ER DR (c    )   +   ′_i,t +   ′_{i* A} ′_i+   _i+ u_i,t  

(12) 

Lastly, all variables employed in this study combined into one regression equation to substantiate        potential   economic   significance   of   the   variables: 

  LN Q   _i,t =  α   ₀ +   γ1OW N ER′_i+  γ2OW N ER′_{i* R}EGION  ′_i + γ3COM M ON  ′_i + γ4CIV IL    ′_i

5F IRM SIZE   6EM P LOY EES   7M AN AGERS 8CR   9REGION    (c    )   + β ′_i,t + β ′_i,t + β ′_i,t+ γ ′_i+ γ ′_i+   i+ ui,t  

(13) 

5   Empirical   results 

This part of the study presents the results of the aforementioned analyses carried out. Descriptive        statistics begin with an impression of the data at hand by showing the summary statistics as well as        correlation matrix of the selected relevant variables of the panel data in table 2. A full description can be        found in table A1. In the following, I start with testing the distributions and variances combined, because        they deliver the same results for the US and Europe (5.1). Afterwards, individual samples for the US        firms are tested (5.2), then the European firms are tackled (5.3), to get a first individual impression of        their results, following the research of La Porta et al. (1998) suggesting that different countries are        heterogeneous. These two sections paint the dry picture of the results received, which are interpreted        subsequently. After doing so, I dig deeper and explain further, based on the whole sample. The same        strategy applies to the explanation of empirical results that was laid out in section four; I am building up        the argumentation stepwise to empirically explain the independent variables used and understand their        impact, finally leading to a conclusion. The intention is to let the reader observe how the variables and        setups affect ownership impacts on firm performance, which is the main aim of this study. The dummy        “ownership” is thus the only variable that stays constantly in the regressions. The empirical results are        concluded   by   various   robustness   tests   in   different   setups. 

5.1   Overlap   US   and   Europe   for   Homogeneity   of   Variance   and   Normality 

For both data sets I begin by testing for normality. Both the regular as well as natural logarithm of        Tobin's Q show significant results for their normality tests, therefore I reject the null hypothesis of normal        distribution. Additionally, I conduct a Levene’s test for equality of variances, for which I also obtain        significant results and thus again fail to reject the null hypothesis, affirming homoscedasticity (see tables        Appendix­C). Based on the findings, I conduct nonparametric tests instead, to compare the two        independent groups of ownership types, namely the Mann­Whitney U, which does not assume normality.        To test robustness, I also include t­tests. To get a clear picture of the values in this study, both panel and        single year values of both the logarithmized and raw values of Tobin's Q are used to visualize their        comparability. The assumption holds that Tobin's Q implies time within its value. To be precise and        comprehensive,   the   main   regressions   are   using   exclusively   panel   data. 

Table   2 

Descriptive statistics in panel A report and compare number of observations (N), mean, standard deviation, minimum values and maximum values for the whole        sample, with manager as an owner and for outside owners. This sample comprises 2005 observations for both US and European firms with a sample period between        2001   and   2015.   A   full   description   of   variables   is   presented   in   table   A1.   Panel   B   of   this   table   reports   the   correlations   of   the   relevant   variables,   defined   in   table   1.  Panel   A:   Summary   Statistics   of   the   variables   used   in   the   joint   sample   after   reshape   for   panel   analysis 

  All   Sample    Manager   as   Owner    Outside   Owner 

Variables  N  Mean  Std.  Dev.  Min  Max    N  Mean  Dev.Std.   Min  Max    N  Mean  Dev.Std.   Min  Max  LNTobinsQ  26,065 0.534  1.544 ­2.386 5.412    4,511 0.927  1.953 ­2.333 5.412    21,554 0.452  1.430 ­2.386  5.403  LNMarketCap  26,065 16.806 3.110  ­1.833 26.387    4,511 15.444 3.196 ­1.833 26.387    21,554 17.091 3.015 2.259  25.204  LNEmployees  21,333 4.121  2.608 0  13.323    3,289 3.116  2.516 0  11.043    18,044 4.304  2.582 0  13.323  LNManagers  25,766 2.139  0.802 0  4.812    4,407 1.671  0.829 0  4.812    21,359 2.236  0.761 0  4.804  Ownership  26,065 0.173  0.378 0  1    4,511 1  0  1  1    21,554 0  0  0  0  Region  26,065 0.459  0.498 0  1    4,511 0.450  0.498 0  1    21,554 0.461  0.499 0  1  Owner   x   Region  26,065 0.078  0.268 0  1    4,511 0.450  0.498 0  1    21,554 0.000  0.000 0  0  Shareholder   Rights  17,108 4.521  1.049 0  5    3,016 4.375  1.236 0  5    14,092 4.553  1.002 0  5  Creditor   Rights  25,428 1.708  1.282 0  4    4,316 1.283  0.860 0  4    21,112 1.794  1.335 0  4  Common   Law  25,558 0.762  0.426 0  1    4,342 0.608  0.488 0  1    21,216 0.794  0.405 0  1  Civil   Law  26,078 0.203  0.403 0  1    4,511 0.360  0.480 0  1    21,554 0.171  0.376 0  1    Panel   B:   Correlations   matrix      1  2  3  4  5  6  7  8  9  10  11  1 LNTobinsQ  1.0000        2 LNMarketCap  ­0.1606  1.0000        3 LNEmployees  ­0.3513  0.6771  1.0000        4 LNManagers  ­0.3643  0.6414  0.6068  1.0000        5 Ownership  0.1165  ­0.2004  ­0.1645  ­0.2653  1.0000        6 Region  ­0.3355  0.1922  0.1783  0.4396  ­0.0090  1.0000        7 Owner   x   Region  ­0.1338  ­0.0554  ­0.0189  0.0037  0.6349  0.3151  1.0000          8 Shareholder   Rights  0.2201  ­0.1600  ­0.1145  ­0.3290  ­0.0645  ­0.9109  ­0.4407  1.0000        9 Creditor   Rights  ­0.2156  0.2371  0.2298  0.3643  ­0.1497  0.5956  ­0.0212  ­0.4064  1.0000      10 Common   Law  0.2164  ­0.0007  0.0145  ­0.1657  ­0.1638  ­0.5997  ­0.4170  0.9173  0.2052  1.0000    11 Civil   Law  ­0.2145  ­0.0206  ­0.0307  0.1318  0.1781  0.5484  0.4313  ­0.8342  ­0.1905  ­0.9155  1.000    5.2   US   Firms   

results indicate that the medians are different with a significance level of 1%, I thus reject the null        hypothesis that the means of managerial ownership and outside ownership on Tobin's Q are equal,        indicating differences between the two types of ownership, showing z = 8.404 (7.649), p = 0.000 (0.000).        Additionally, the output shows a p­order value of 0.596 (0.668), indicating that in 59.6% (66.8%) of        random draw cases, Tobin's Q performance would be higher if there is managerial ownership present,        providing support for hypothesis 2 in the US sample. The same results are received for the logarithmized        as well as raw forms of Tobin's Q and also show the comparability of Tobin's Q values at one point in        time   to   time­series   panel   data. 

Panel B of table 3 adds some robustness to the rank sum tests performed and further substantiates        the findings. The results of the two­tailed t­test on the natural logarithm of Tobin's Q show that in the        United States, firms with owners who are also managers have statistically significant higher Tobin's Q        (1.9815 +/­ 2.26682) than those owned by outsiders (1.1562 +/­ 2.0651), t(4889) = ­9.569, p=0.000.        Those results are also supported by testing the original value of Tobin's Q on last year’s values, obtaining        statistically significant higher Tobin's Q (70.1332 +/­ 131.1039) than those owned by outsiders (20.3622        +/­   67.0274),   t(876)   =   ­7.889,   p=0.000.  

5.3   European   firms 

I am testing a sample of 4766 (878) observations, of which 601 (145) are management owned and        4165 (733) outside owned. The results indicate that the medians are different with a significance level of        1%, thus I reject the null hypothesis that the means of managerial ownership and outside ownership on        Tobin's Q are equal, indicating differences between the two types of ownership, showing z = ­2.884        (­2.985), p = 0.004 (0.003). Additionally, the output shows a porder value of 0.464 (0.422), indicating that        in only 46.4% (42.2%) of random draw cases, Tobin's Q performance would be higher if there is        managerial ownership present, thus not providing support for hypothesis 2 in the European sample and        indicating   differences   for   the   meaning   of   managerial   ownership   in   between   those   regions.