Executive compensation and agency costs in Germany

Journal of Banking & Finance 27 (2003) 1391–1410 www.elsevier.com/locate/econbase

Executive compensation and agency costs in Germany Julie Ann Elston a b

a,1

, Lawrence G. Goldberg

b,*

Department of Economics, University of Central Florida, Box 161400, Orlando, FL 32816, USA Department of Finance, University of Miami, P.O. Box 248094, Coral Gables, FL 33124, USA Accepted 22 November 2001

Abstract With the growth of international mergers like DaimlerChrysler, interest in executive compensation practices abroad, particularly in Germany, has increased. Using unique data sources for Germany, we find that similar to US firms, German firms also have agency problems caused by the separation of ownership from control, with ownership dispersion leading to higher compensation. In addition, there is evidence that bank influence has a negative impact on compensation.
2003 Elsevier Science B.V. All rights reserved. JEL classification: G30; J33; L20; M10 Keywords: Executive compensation; Corporate governance; Germany; Agency

1. Introduction The differing levels of executive compensation across countries have recently aroused significant public interest as cross-country mergers have increased. While the academic literature has focused mostly on compensation behavior in the US, recent studies have begun to explore compensation practices in other countries, particularly in Germany. Mergers between firms in different countries naturally raise issues of comparability of pay and incentives-for-performance practices between countries. Numerous studies have tried to identify the most important factors impacting *

Corresponding author. Tel.: +1-305-284-1869. E-mail addresses: [email protected] (J.A. Elston), [email protected] (L.G. Goldberg). 1 Tel.: +1-407-823-2078. 0378-4266/03/$ - see front matter
2003 Elsevier Science B.V. All rights reserved. doi:10.1016/S0378-4266(02)00274-1

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executive compensation. Recently several studies have examined the agency problems of firms by relating the level of executive compensation to corporate control measures. Germany is a country of particular interest not only because it has considerably lower levels of compensation than the US, but also because it has a very different corporate governance structure, characterized by concentrated firm ownership and a strong bank presence. In this paper we examine the factors affecting the level of executive compensation in Germany, with particular emphasis on the agency problem created by the separation of management and ownership. Agency problems caused by the separation of ownership from control in large corporations were first popularized by Berle and Means (1932) and have since been examined extensively in both the popular and academic literature. Jensen and Meckling (1976) formalized the agency problem and stimulated interest in executive compensation, the most easily measured way that managers could take advantage of lack of control by owners. Top executive compensation has grown dramatically in the United States, and consequently, public interest in compensation levels has increased. Popular publications regularly reveal the compensation of the top executives and particularly the chief executive officers (CEO) of the large corporations. The Securities and Exchange Commission (SEC) requires companies to reveal compensation components for top executives. Since US executives are the highest paid in the world, the US has the largest economy, and data are readily available in the US, most popular and academic attention has focused almost exclusively on the United States. However, there has been increased interest in executive compensation in other countries, and particularly in Germany. 2 Several bodies of literature have developed in order to determine whether management is taking advantage of the lack of ownership control. The first body of literature examines the relationship between executive compensation and corporate performance, while the second relates corporate performance to the degree of control that owners have over managers. Our study contributes to the relatively smaller third body of literature relating corporate control directly to executive compensation and thus directly tests the agency issue. Section 2 reviews some of the most relevant studies to date. Though we know less about executive compensation in countries other than the US, researchers are currently investigating very similar issues in some of these countries, although data availability has impeded this process. Germany has the third largest economy in the world and consequently is of considerable interest. Internationalization has progressed recently at a rapid pace and German firms are more commonly merging with firms from other countries. Executive compensation becomes a particularly important issue when a German firm merges with an American firm, such as in the case of the Daimler–Benz merger with Chrysler. Corporate structure differs greatly between the two countries. Do American CEOs get paid more

2 Among the most important articles on German compensation are FitzRoy and Schwalbach (1990), Schwalbach (1991), Schwalbach and Grasshoff (1997), and Schmid (1997).

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than their German counterparts? If so, can this be justified? A recent article in the German magazine Focus has claimed that German executives are underpaid despite high performance. The article cites 1997 German salaries of top executives including: • • • •

Jurgen Schremp of DaimlerChrysler at 3 million DM; Bernd Pischetsrieder of BMW at 3.5 million DM; Ulrich Hartmann of VEBA at 2.9 million DM; and Heinrich Von Pierer of Siemens at 2 million DM.

These compensation levels seem low compared to equivalent executives in the US such as: • • • •

Bob Eaton of DaimlerChrysler at 20 million DM; John Welch of GE at 69 million DM; Andrew Grove of Intel at 89 million DM; and Richard Scrushy of Healthsouth at 181 million DM.

Although this difference between the two countries has been narrowing recently as German firms have increasingly turned to granting stock options to top executives (Kroll, 1999), corporate control systems remain quite different in the two countries. 3 One main difference is that many German firms have a 2-tiered board system and also many firms have representation of banks on the supervisory board (SB) of the firm. All the firms in our sample do in fact have a 2-tiered board system. For many reasons then, it is quite important to identify the factors affecting executive compensation in Germany and to assess the effect of corporate control mechanisms on executive compensation. In order to analyze this issue we have compiled a unique and comprehensive data set in order to analyze German executive compensation. This data set is more extensive than data used in previous studies of German compensation. This enables us to contribute to the literature, based largely on American data, by analyzing the factors affecting executive compensation and the effects of ownership control on executive compensation in Germany. The results for German executives are strikingly similar to those found previously for American executives. We find evidence that both sales and ROE are positively correlated with compensation, and that greater ownership dispersion leads to higher levels of executive compensation holding other factors constant. Thus, agency problems appear to exist in Germany as well as in the United States. Further there is evidence that bank influence reduces compensation, and that large block ownership of stock by various groups also has a negative effect on compensation. Section 2 of the paper reviews the previous relevant literature. Section 3 describes the German corporate governance structure, including the two types of boards and the role of banks in corporate control. Section 4 presents the empirical model and the

3

Kroll finds no sensitivity of SB compensation to firm performance.

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refutable hypotheses. Section 5 describes the data employed. The empirical results are presented and discussed in Section 6. Section 7 concludes with implications for corporate control.

2. Literature review Berle and Means (1932) raised a number of issues about the operation of the modern corporation and noted the problems that arise with the separation of ownership and management. When owners do not control the corporation, managers are able to pursue their own economic interests. Dispersion of ownership reduces the ability of shareholders to remove bad managers and also reduces the incentive for and the ability of shareholders to monitor managerial activity. Ownership dispersion also provides managers incentives to exploit their protected positions and extract benefits for themselves. The most direct benefit managers could obtain is increased monetary compensation, and this benefit is also the easiest one to measure. Non-monetary benefits, such as the size and quality of the support staff, the character of the work environment, and access to corporate assets for personal use, are difficult to measure or compare across companies. Consequently, in this study we follow the practice of previous studies and compare monetary compensation. The earliest empirical studies of executive compensation in the United States used simple correlation coefficients to identify the factors related to the level of compensation. Patton (1951) examines the distribution of pay among different types of executives and finds that executive compensation is positively correlated with both profits and growth of the firm. Subsequent studies usually just used data relating to the CEO because of greater ease in obtaining these data. Roberts (1956) and McGuire et al. (1962) find a stronger relationship between sales and compensation than between profits and compensation. In a more recent study, Jensen and Murphy (1990) find the opposite. Ciscel and Carroll (1980) correct econometric problems in these models by using an instrumental variable for profits to reduce multicollinearity between sales and profits. This literature plus more recent studies conclude that both profits and size are positively related to executive compensation. Executives are paid more when the company is more successful and are also paid more when the company is larger. This provides incentives to executives to improve performance, a goal in line with stockholdersÕ interest, but it also provides incentives to increase the size of the company, a goal that might not be in the interest of stockholders. Other studies have introduced additional explanatory factors. Among these variables are regulatory effects in transportation and utilities (Carroll and Ciscel, 1982), market concentration and barriers to entry (Auerbach and Siegfried, 1974), the gender of executives and capital investment in workers (Bartlett and Miller, 1988), sales growth (Murphy, 1985; Coughlin and Schmidt, 1985), and stock performance instead of accounting performance (Masson, 1971; Murphy, 1985; Deckop, 1988). In this study we follow the lead of previous studies in choosing control

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variables and use the two types of measures, profitability and size, that have been found to be important determinants of executive compensation. A second line of research in executive compensation relates corporate performance to ownership dispersion. Demsetz and Lehn (1985) find no relationship between profitability and ownership concentration using a linear model. However, Morck et al. (1988) find a significant non-monotonic relationship between both ownership concentration and profit rates and ownership concentration and TobinÕs Q––a measure of market valuation. As ownership concentration increases, TobinÕs Q rises, falls, and then rises again. The last series of studies is most closely related to our study. These studies directly test the agency problem with respect to executive compensation. Stigler and Friedland (1983) examine the relationship between shareholder control and executive compensation for a sample of 92 firms for 1937–1938. They find no significant relationship between the average salary of the top three executives and the percent of stock held by the top 20 shareholders. Santerre and Neun (1989) replicate this study, and after including profits as an additional independent variable, find a negative relationship. Both Santerre and Neun (1986) and Dyl (1988) use more recent data to test the agency problem with respect to executive compensation. Using only data for CEOs, both studies find a negative relationship between ownership concentration and CEO compensation. More recently, Goldberg and Idson (1995) examined the agency question for Fortune 500 companies. This study estimated the relationship between the dispersion of corporate ownership and the compensation of top executives across the executive hierarchy and for different components of the compensation package in contrast to the more limited previous studies. The study found a statistically significant agency effect, though it was small relative to company size. The effects were greatest for salaries, the most liquid form of remuneration, and the executive with the strongest effect was the Chairman of the Board. Increased attention has been paid to corporate governance issues recently in other countries. However, there are only a limited number of academic empirical investigations of corporate governance in other countries. Germany has probably been the country in which the greatest interest has been shown. Germany has more of a bank dominated financial system in contrast to the market dominated system in the United States. A number of studies, such as Rubach and Sebora (1998), Kim (1995), and Emmons and Schmid (1998), have discussed corporate governance issues in Germany and compared them to the United States. Chirinko and Elston (1996) systematically evaluate German bank influence and find that bank influence does not lower finance costs nor have any discernable effect on profitability. However, they also find that control problems are addressed by concentrated ownership and bank influence. Weigand and Lehmann (1998) examine the impact of ownership structure on the performance of German firms, as measured by return on assets, from 1991 to 1996. They find that corporate structure only affects performance for firms not quoted on the stock exchange. In addition, they show that blockholder ownership results in higher returns and that there are systematic interactive influences of ownership concentration and the identity of owners on performance

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for the non-quoted companies. Franks and Mayer (1998), however, do not find a significant relationship between board turnover and patterns of ownership. Schwalbach (1991) was one of the first studies to examine the effects of management interests and profits on compensation in Germany. Using 468 firms in 1988 from the Bonn Data, he shows that size and industry effects are important in determining executive compensation. Conyon and Schwalbach (1999) examine executive pay outcomes in the UK and Germany. Their study finds a positive and significant relationship between pay and company performance in both countries. Finally, using 83 firms from 1968–1990 and 220 firms from 1988–1992, Schwalbach and Grasshoff (1997) find that firm size and industry are important determinants of compensation for the management board but that performance itself plays only a minor role. The two previous studies most similar to our current study are FitzRoy and Schwalbach (1990) and Schmid (1997). The first study, using annual data for 95 firms from 1969–1985, finds a negative effect of concentrated ownership on the average annual salary of the management board. Ownership is measured by a Herfindahl index of equity capital distribution in 1982. Since these data are only available for one year, the same ownership distribution variable is employed for every year for each company in the sample. Schmid (1997) provides an alternative approach to the issue by examining the relationship for 1991 between compensation on the two boards of 110 of the largest 120 traded German companies and shareholder structure and firm performance. He tests various hypotheses and finds evidence that the compensation of both boards is affected by performance and by the firmsÕ shareholder structures. His measure of ownership concentration uses a Herfindahl index for 110 firms in 1991 and has some advantages over the measure that we use here. However, his study only covers one year while our study contributes to the literature by conducting a dynamic analysis of corporate governance effects on compensation for a broad panel of German firms over a 17-year time period.

3. German corporate governance structure There are two main aspects of the German corporate governance structure that are different from the system in the United States. The first is that many large companies in Germany have a 2-tiered board structure comprised of the Aufsichtrat or SB and the Vorstand or managing board (MB). We are primarily interested in the MB rather than the SB. The SB has oversight responsibilities for the corporation similar to the responsibilities of American boards of directors. The SB appoints the MB and also sets the compensation of the members of the MB. The MB is the top management of the corporation and has responsibility for the day-to-day operation of the corporation. Commercial banks have a significant influence on corporate governance in contrast to the United States where the banks are prohibited in general from directly owning equity in corporations. In Germany only certain legal identities are required to have supervisory and managing boards. These include the common AG (Aktiengesellschaft) or stock held firm,

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as well as the more rare corporate form, the KgaA (Kommanditgesellschaft auf Aktien). 4 German law dictates that if an AG has fewer than 2000 employees, then the employees elect one third of the members of the SB and two thirds are elected by the shareholders. If the AG has more than 2000 employees, the shareholders appoint half of the SB while the firm employees select the other half. The chairperson of the SB is elected by a two-thirds vote of all board members for a maximum term of five years, with the possibility of reappointment. The law dictates the size of the SB for firms with more than 2000 employees. The SB must have 12 members for firms with 2000–10,000 employees, 16 members for firms with 10,000–20,000 employees, and 20 members for larger firms with over 20,000 employees. The owner appointed members are frequently bank representatives and the employee members are frequently labor representatives. Since SB members are paid an honorarium fee, and all members are paid the same, we are more interested in the relationship of MB compensation and performance. Moreover, the members of the MB are comparable to the top executives including CEOs of American corporations that have been studied previously. A controversial attribute of the German corporate governance system is the extent to which the German universal banks impact the governance of the firm. While little empirical evidence exists to measure the precise extent of corporate control of German banks, it is widely believed that these universal bankers have a degree of control that extends beyond the traditional boundaries of the creditor–lender relationship. As specified in Elston (1998), the primary spheres of influence of banks on firms is through (1) bank share ownership and associated voting rights accrued from ownership and proxy votes, (2) through bank representation on the SB (sometimes as chair or deputy chair), and (3) through bank lending and share underwriting. As shareholders, bank representatives regularly participate at annual shareholders meetings, and are frequently represented on the firmÕs SB with one or more representatives. This multi-faceted role provides a direct line of influence between banks and firms that goes beyond the traditional Anglo-Saxon creditor–firm relationship. Through the proxy voting system (Depotstimmrecht), banks can also obtain voting rights from shares in trustee accounts of bank customers. These votes count in general board decisions, including appointments to the firmÕs MB and their salary levels. In fact almost half of the total shares issued are deposited in such bank trustee accounts. Adding the power of the proxy votes to the votes from direct ownership rights, the overall proportion of votes controlled by banks in the largest 100 firms is 36%; and in the top 10 firms this control jumps to over 50%. Thus, though banks may own directly only a small portion of the voting rights of the firm, through the collection of proxy votes, the banks can have a significant influence on the decisions 4 The Gesellschaft mit beschraendter Haftung (GmbH) legal identity is also required to have a supervisory and managing board if the number of employees regularly exceeds 500. However, the rights of the GmbH SB are not as extensive as that of the AG board. For example, the GmbH SB does not appoint the MB. Further, until 1987 only a subset of the GmbHs was even required to adhere to public disclosure law, so that very little information was public before 1987. For these reasons the GmbH firms are not included in this study.

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of the firm, including both the composition and compensation of the SB and MBs. From an agency problem perspective, since banks often hold significant shares of the firms over long periods of time, they also have both the incentive and the ability to engage in extensive and ongoing monitoring of the firm. Therefore in analyzing the factors affecting supervisory and managing board salaries in Germany, it is important to consider the unique structure of the German style system of universal banking. Consequently, we include in our analysis a composite variable measuring bank influence.

4. Model and hypotheses The main objective of this paper is to find the relationship between corporate control factors in Germany and executive compensation. We examine the compensation of members of both the supervisory and the managing boards of German corporations. We are most concerned with the compensation of the MB since its members comprise the top executives of the company. In fact, if there is an agency problem and management is able to extract additional compensation for itself, we would expect this effect to be more pronounced for the MB than for the SB. The methodology, which is well established in the US compensation literature, requires least-squares analysis of the following regression model: logðCompensationÞ ¼ b0 þ b1 ROEjt þ b2 Concjt þ b3 logðSizejt Þ þ b4 Bankjt þ b5 Djt þ et

ð1Þ

where Compensation is the total or per member salaries for the SB or MB, ROE is the return on equity, Conc is the ownership concentration of the firm, Size is the annual firm sales net of value added tax, Bank is the bank influence dummy variable, and D is the vector of industry and time dummy variables. We employ several variants of this model in order to test a series of related hypotheses and insure robustness of results. Non-reported regression variants, which produced consistent results, included use of return on assets as an alternative measure of returns instead of ROE, number of employees and total assets as alternative firm size measures instead of sales, and lagged independent variables. Correlation matrices were estimated to check for the impact of multicollinearity among independent variables. Our main analysis contains four different equations, each with a different independent variable. For each of the two boards, SB and MB, we employ two different compensation measures, total compensation of the board and compensation for the average board member. These measures are chosen because the actual compensation is not available for each individual board member. SB members are compensated equally, but MB members are paid differentially. However, these compensation differentials do not approach the differentials among American executives.

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We hypothesize a positive relationship between log Compensation and ROE and also a positive relationship between log Compensation and log Sales. This is consistent with the findings of previous studies that have found that executives are paid more when the company is more profitable and when the company is larger. We cannot employ a Herfindahl index as done by Schmid (1997) and FitzRoy and Schwalbach (1990) because complete data on ownership structure are not available for each firm for the 17-year span of our data panel. This is because those who own less than 25% of a firm are not required to disclose ownership in Germany. We do, however, have complete interval data on ownership percentages greater than 25% for each firm for every year of the study. We therefore construct an alternative concentration measure based on the ranked categorical source data on ownership concentration. The highest numbered concentration category represents the highest degree of owner concentration. Initially we develop a variable that incorporates the rank of the concentration class, and for this variable we would expect a negative coefficient in the regression model because the agency problem is expected to be most important when ownership is more dispersed. That is, in the categories with greater dispersion, management may be able to extract greater compensation. Since this formulation using the ownership categories might assume a particular relationship, we alternatively employ a model with dummy variables for each category, omitting the category with the most dispersed ownership. The bank influence variable is a dummy variable that takes a value of 1 when a firm is determined to be bank influenced, per our definition in Section 5, and 0 otherwise. The refutable hypothesis is that banks will exert influence and moderate executive compensation. Therefore, a negative coefficient is expected. We also test the effects on executive compensation of different types of ownership. We employ dummy variables to indicate whether the firm is owned by another firm, owned by foreign interests, owned by a bank, or family owned. Government control, mixed ownership, and management control (no large blocks) comprise the omitted category. Because bank influence has a close relationship with bank ownership, we run regressions including these dummy variables both with and without the bank influence variable. We expect executive compensation to be less when there is strong ownership control in these four categories. Since agency problems may differ by industry, there may be some heterogeneity in compensation practices across firms. A final analysis examines bank influence by industry group.

5. Data One of the greatest impediments to measuring the impact of corporate governance on executive compensation in Germany has been the lack of reliable and comprehensive data. This study uses two non-commercially available sources of unique data. The first is a firm-level database that tracks the financial performance of a comprehensive set of German firms from 1961 to 1986. The second data source is derived from various sources, including CommerzbankÕs Wer Gehort zu Wem?, Handbuch

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der Grossunternehemen, Leitende Maenner und Frauen der Wirtschaft, Aktienfuehrer, various annual reports of the firm, and Boehm (1992). The combined information in these collected data exceeds the depth and breadth of commercially available data for Germany, enabling us to directly examine the importance of corporate governance on compensation. The bank influence variable for example is a composite measure using information on percent of bank ownership of the firm, percent of bankers on the SB and whether they are chair of the SB, and total number of votes exercised by banks at annual shareholder meetings. 5 We operationalized this information by defining a dummy bank influence variable. A firm is characterized as bank influenced rather than independent if the bank owns more than 25% of the shares of the firm, if total votes of banks at shareholder meetings (including proxy votes) are greater than 50%, or if total votes are between 25% and 50% and the chair of the SB is a banker. 6 This discrete measure is possibly an imperfect measure of the influence of banks on firms, however it does succeed in incorporating all of the available information on bank–firm relations for each of these firms over each of the 17 years, thereby enabling a dynamic empirical analysis of compensation behavior. 7 As mentioned above, the data used also include a subset of the Bonn Data that is based on a collection of financial reports of about 700 German industrial corporations quoted on the German stock exchange. 8 Because of mergers, bankruptcies, acquisitions, changes in legal status, and double listing of consolidated and nonconsolidated information, about 295 unconsolidated firms remained in 28 industry groups as of 1986. 9 We had information on the ownership identity and concentration for exactly 100 firms over the full time period. This was reduced to 91 firms in the analysis where we had both balance sheet and bank relationship data. Thus we used all firms for which the appropriate data were available rather than using a random sample of firms. 10 We need to focus on these listed firms in order to study the phenomenon of executive compensation since these are the types of firms for which supervisory and 5 Appendix A reports descriptive statistics for bank influence variables. Note that there is a substantial difference between the independent firms and the bank influenced firms. See Seger (1997) for a detailed study of governance effects on the performance of German firms. 6 Voting data are available for 1986 only. Ownership identity and concentration are available for each firm for every year of the study. 7 As a secondary check for accuracy of the bank influence measure, we also checked the results of this characterization on a firm by firm basis over the sample period and found it remarkably consistent with all available information on bank–firm relationships. 8 The main sources for the data was the Bonn Data, constructed at the Business and Economics Institute of the University of Bonn. 9 We use unconsolidated data although there is no theoretical reason to believe that the compensation performance relationship is impacted by the existence of a parent company nor are we aware of any previous research addressing this issue. In fact, Bond et al. (2002) compare investment estimations for both consolidated and unconsolidated firms using these data and fail to find a significant difference in estimation results between groups when examining investment sensitivity to liquidity constraints. 10 Our data represent nearly 20% of what Edwards and Fischer (1994, p. 77), report as the listed stock held by AG firms in Germany in 1980.

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managing boards are mandatory. We used data from 1970 to 1986 because prior to 1970 there were too many missing key variables. 11 Even for this time period, some variables were missing, thus requiring running regressions on smaller subsets of the full sample. Data after 1986 are not used because of the substantial changes in the German accounting laws, which make it impossible to compare the data without considerable adjustment. 12 The sample time period of 1970–1986 is important not only as point of comparison with current stock of US studies available for this period, but also to understand the pay–performance relationship during this period for Germany. The number of firms in the sample is also fairly representative because the German exchange is considerably smaller than its American counterpart. For example in 1980 there were only about 459 listed firms incorporated as AG and KgaA. 13 For these 91 firms we have annual firm-level information detailing the identity of firm owners. These discrete data are reported in mutually exclusive categories defining the identity and concentration of the ownership structure for the firms. Firms categorized as ‘‘Firm Controlled’’ are those in which another domestic firm either owns more than 50% of the outstanding shares or another firm owns at least 25% and no one else owns more than 25%. ‘‘Foreign Controlled’’ firms are those with more than 50% ownership by foreigners. ‘‘Bank Controlled’’ firms are those with more than 50% ownership by financial institutions. ‘‘Family Controlled’’ firms are those with more than 50% ownership by family members, groups, or individuals. ‘‘Government Controlled’’ firms are those with more than 50% ownership by any county or state. ‘‘Management Controlled’’ firms are those which have no block ownership percentage over 25%. Finally ‘‘Mixed Control’’ denotes a situation where different types of the above owners exist, each owning anywhere from 25% to 50% of the shares. We combine the last three groups as the omitted category in the empirical analysis. Most firms in this omitted group have no block ownership over 25%. The concentration of firm ownership is measured from one to five, where five defines the highest degree of concentration, with a single stockholder holding more than 75% of the firmÕs shares. If two or three stockholders hold more than 75% of the shares and the firm does not qualify for the higher concentration level, then concentration is set at four. Concentration is set at three if a single stockholder holds more than 50% of the shares, and two, if two or three stockholders own more than 50% of the shares. Concentration is set at one for all cases in which the concentration level is lower than for category two. 14 Note that if the firm satisfies two or more 11 We use data after 1965 because of the Corporation Act of 1965, under which the accounting rules for the valuation of plant, equipment, and inventories, as well as profits, were tightened. For example, if BASFs 1981 equity was valued under US–SEC rules rather than under German law, the valuation would be 40% higher than reported according to the new German rules. 12 An accounting law provision passed on December 12, 1985 that stated that unconsolidated firms must comply with the new standards by 1/1/1986. 13 See Edwards and Fischer (1994, p. 77) for a detailed discussion on legal incorporations. 14 Note that 25% is a key percentage because it represents a minority blocking vote at shareholders meetings and German law requires disclosure of ownership for any party owning 25% or more of outstanding stock.

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concentration levels, the firm is placed in the higher concentration category. 15 SB and MB pay is defined as total salaries paid to supervisory and managing board members by the firm for which they provided this service. 16 Sales is measured as sales of the firm net of taxes. The data for variables are measured in terms of logs of millions of Deutsche marks. The estimations were run with both time and industry dummy variables in order to control for macroeconomic shocks and industry-specific effects in the model. 6. Empirical results The means and standard deviations of the main variables are presented in Table 1. The number of observations at the bottom of the table indicates the maximum number of observations for each variable; however, the actual regressions generally used fewer observations because of missing data. Note that there appear to be substantial differences across variable means for the levels of ownership concentration. This justifies the separate analysis of each category of ownership concentration. It should be noted that average compensation per board member is lower for the higher concentration ownership categories 3–5. Thus without controlling for other factors, there is some evidence that higher levels of ownership concentration help to control the agency problem. Table 2 contains the results of OLS fixed-effect regressions on the log of compensation measures of the two boards. We are most interested in the results dealing with the MB. Panel A of Table 2 reports results for regressions using the log of average salary of a management board member and the log of total salaries of the management board members of each firm as the dependent variables. The results for both measures of compensation are quite similar indicating that we are capturing the same compensation process with either definition and can proceed to report results only for the average salary per board member in the following tables. The ownership concentration variable has a negative coefficient and is statistically significant in both equations as predicted by the agency hypothesis. Firms with more concentrated ownership provide less compensation for MB members. ROE has a positive and significant coefficient for the average MB member salary but is insignificant for the firm total MB salary. The Sales variable has a positive and statistically significant coefficient in both equations indicating that larger size leads to greater compensation for the members of the MB. 17 The bank influence dummy variable is negative in both cases at the 5% level. Bank influence appears to reduce management compensation. 15 We do not include data from consolidated annual reports because it represents a different level of firm activity from non-consolidated firms. 16 Note that salary data are reported annually by firms only as a total. Individual salaries were calculated by dividing the corresponding salary by the number of board members. While this was the only option available for these estimations, it makes particular sense in the German context where SB members are paid the same amount (honorarium) and MB have less variation in salaries as compared to US firms. 17 Using sales that were lagged produced essentially equivalent results and these results are available from the authors on request.

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Table 1 Decriptive statistics 1970–1986 Variable

All firms Bank influenced

Indepen- Conc ¼ 5 Conc ¼ 4 Conc ¼ 3 Conc ¼ 2 Conc ¼ 1 dent (high) (low)

ROA

0.0239 (0.0230) ROE 0.0555 (0.2168) Net sales 1453.04 (3869.95) Total assets 1149.83 (3136.83) Number of 9701.93 employees (25957) SB salaries 0.2215 (0.2511) MB salaries 1.4761 (2.2285)

0.0254 (0.0166) 0.1013 (0.3474) 808.869 (1890) 399.2058 (862.966) 6747.21 (15974) 0.2306 (0.2315) 1.1722 (1.8093)

0.0337 (0.0238) 0.0494 (0.1921) 1551.32 (4080.08) 1263.91 (3335.37) 10148.93 (27126) 0.2202 (0.2539) 1.5208 (2.2808)

0.0197 (0.0155) 0.1109 (0.4269) 965.950 (2245.39) 558.223 (946.81) 5731.71 (11665) 0.1363 (0.1349) 0.9477 (1.1923)

0.0260 (0.0184) 0.0396 (0.0369) 659.265 (1129.85) 732.51 (1202.29) 3122.28 (4405) 0.2014 (0.2333) 1.2038 (1.9360)

0.0224 (0.0172) 0.0355 (0.0315) 294.522 (974.26) 242.6478 (654.896) 1891.28 (3914) 0.1555 (0.1628) 0.7049 (1.0046)

0.0251 (0.0341) 0.0377 (0.0695) 1111.32 (1968.99) 672.0945 (937.13) 9802.26 (17112) 0.3031 (0.2478) 1.6876 (1.8959)

0.0239 (0.0639) 0.0363 (0.0639) 915.88 (1845.21) 564.98 (941.51) 7299.25 (12950) 0.2492 (0.2453) 1.3918 (1.6029)

Observations 1683

221

1462

517

192

288

257

429

Standard deviation in parenthesis below means. Net sales, total assets, and average board salaries are in logs of millions of DM. Conc stands for ownership concentration: Conc 5 ¼ highest concentration, Conc 1 ¼ lowest concentration. Bank influence is a composite measure of bank influence on the firm, incorporating information on: Ownership structure and concentration, proxy voting by banks, bank representation, and position on SB. Data sample covers 17 years for 100 firms; however, not all firms have data for each year for every variable. Therefore, actual observations used in calculations vary.

Table 2 OLS fixed-effects regressions of (Panel A) MB salaries and (Panel B) firm-level SB salaries ROE

Sales

Ownership concentration

Bank influence

Adj R2

Panel A Average MB member salary Firm total MB salary

0.049 (2.326) 0.027 (1.100)

0.210 (20.403) 0.502 (42.408)

0.036 (3.419) 0.0841 (7.020)

0.108 (2.338) 0.191 (3.594)

0.4184

Panel B Average SB member salary Firm total SB salary

0.094 (2.648) 0.111 (2.937)

0.1577 (9.096) 0.410 (22.079)

0.114 (6.471) 0.098 (5.185)

0.002 (0.019) 0.1310 (1.570)

0.3425

Variable

0.8072

0.5304

All equations use time and firm dummies, and WhiteÕs error correction for obtaining heteroskedastic parameter estimates.  t-Value indicates variable significant at 5% level and  significant at the 10% level. Observations ¼ 1365.

Panel B of Table 2 presents results for the SB. In both the average salary equation and the total salary equation, the ownership concentration variable again has a

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negative coefficient that is statistically significant. Greater ownership concentration leads to lower compensation for SB members, confirming the hypothesis that lack of ownership control permits greater personal rewards. Both ROE and Sales are positive and significant in the two regressions, indicating that better performance and larger size lead to greater compensation for the members of the SB board. However, the bank influence variable is negative and not significant in the average SB member salary equation and positive and significant at the 10% level in the firm total SB salary equation. Since bankers sit on the SB they may have conflicting motives regarding controlling compensation. Clearly bank influence is more important in controlling compensation on the management board. In results not reported here, we have substituted ROA for ROE and Assets or Employees for Sales. The results including these variables were essentially the same as those reported here. In Tables 3 and 4 we add additional explanatory variables to the analysis. Instead of using a single summary variable to measure ownership concentration, we employ four dummy variables in order to examine the importance of the different ownership concentration categories and omit the least concentrated category, Conc 1. We also include dummy variables for groups that have ownership control. 18 Table 3 analyzes management board salaries and Table 4 analyzes SB salaries. In both tables three equations are estimated using OLS fixed-firm effects and generalized method of moments using instrumental variables (GMM IV). All reported coefficients are heteroscedastic-consistent parameter estimates. Time dummies were also included in the regressions. The first equation in each set of equations includes the concentration dummies and four ownership dummy variables but excludes the bank influence variable because it is highly correlated with bank ownership. The second equation excludes the concentration dummies and the third excludes the ownership dummies. The results in Tables 3 and 4 provide strong support for the agency hypothesis, though the traditional variables, ROE and Sales, do not perform as well as before. For the regressions with the MB average salary, ROE has a positive but non-significant coefficient while Sales is positive and significant in half of the equations but negative and significant in the other half of the equations. The bank influence variable however, has a negative and significant coefficient in all four equations in which it is included. As expected, the more highly concentrated ownership categories 3–5 have negative coefficients in all but one case and many of the coefficients are significant. All of the ownership dummies are negative as expected and all are statistically significant. The results are similar for the SB average salary regressions reported in Table 4. ROE has a positive coefficient in all cases and is statistically significant in two equations. Sales is positive in four equations and is negative in two, and it is statistically 18

We examine the correlation between the summary concentration measure and each of the dummy variables for groups that have ownership control. The highest correlation coefficient was 0.3416 between Conc and Firm. The correlation coefficients were respectively 0.2755 for Foreign, 0.1225 for Bank, and 0.0422 for Family. Thus we do not appear to have a multicollinearity problem. A full correlation matrix for all relevant variables is available from the authors.

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Table 3 Managing Board (MB) salaries Dependent variables

OLS MB salaries 1

2

3

1

2

3

ROE

0.0091 (0.23) 0.1372 (7.01) – –

0.0092 (0.23) 0.1555 (8.16) 2.6262 (27.77)

0.0136 (0.27) 0.1495 (16.52) 0.4831 (7.96)

0.0885 (0.62) 0.0907 (7.99) – –

0.2061 (1.59) 0.2596 (10.01) 2.4381 (18.19)

0.0514 (0.34) 0.0754 (7.87) 0.1113 (1.80)

0.2138 (2.96) 0.3070 (2.79) 0.7625 (13.73) 0.09256 (1.06)

0.3204 (3.50) 0.1392 (1.25) 0.5086 (8.88) 0.1858 (1.61)

– – – – – – – –

0.0552 (0.74) 0.0742 (0.71) 0.6557 (12.47) 0.0699 (0.62)

Sales Bank influence

Concentration (1 ¼ low, 5 ¼ high) Conc 5 0.1045 – (1.43) – Conc 4 0.1182 – (1.21) – Conc 3 0.2085 – (3.81) – – Conc 2 0.1614 (1.65) – Ownership Firm Foreign Bank Family Adj R2 Sargan (p-Value)

GMM MB salaries

2.3419 (18.41) 2.3792 (11.32) 2.3848 (20.73) 2.2640 (19.18)

2.5311 (21.98) 2.6496 (14.72) – – 2.4781 (24.07)

– – – – – – – –

0.2597 (3.25) 0.5550 (3.93) 0.2618 (3.50) 0.2715 (3.83)

2.5152 (16.70) 3.0891 (12.52) – – 2.4527 (17.57)

– – – – – – – –

0.7583 – –

0.7530 – –

0.5935 – –

0.7994 146.693 (0.2503)

0.8339 121.2323 (0.2069)

0.7705 168.1391 (0.2869)

All equations use time and firm dummies, and average MB salary. OLS fixed-effects model reports estimates corrected for heteroskedasticity. GMM heteroskedastic-consistent estimates use instruments of lagged ROE, ROA, and Sales variables from t  2; . . . ; t  7. The Sargan statistic tests for over identifying restrictions in the model. Regressions 2 and 3 do not have the Bank ownership variable because of the high correlation with the composite bank-influence variable.  t-Value indicates variable significant at 5% level and  significant at the 10% level. Observations ¼ 1365.

significant in each case. The bank influence variable is negative in all four equations and is statistically significant in three of the equations. The ownership concentration dummies are negative in all but one case for the three most concentrated groups and are significant in many cases. Note that Conc 2 is positive and significant in three of the four cases where it is included. The ownership categories are again negative and significant in all cases. Table 5 reports regressions for MB salaries by industry using three independent variables. While ROE is insignificant in all five equations, Sales is positive and

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Table 4 Supervisory Board (SB) salary Dependent variables

OLS SB salaries 1

2

3

1

2

3

ROE

0.0889 (1.36) 0.0839 (2.62) – –

0.0900 (1.36) 0.1073 (3.44) 4.4983 (29.54)

0.1180 (1.34) 0.5055 (35.09) 0.3908 (4.14)

0.4408 (1.88) 0.1570 (2.96) – –

0.4130 (1.74) 0.1414 (3.01) 4.3470 (18.24)

0.1113 (0.37) 0.4828 (26.25) 0.0638 (0.58)

0.9720 (8.32) 1.1946 (7.95) 1.3873 (15.07) 0.0178 (0.13)

0.0365 (0.27) 0.0597 (0.43) 0.1708 (1.57) 0.8345 (4.43)

– – – – – – – –

0.8975 (6.84) 1.0521 (6.81) 1.1206 (10.94) 0.4230 (1.90)

Sales Bank influence

Concentration (1 ¼ low, 5 ¼ high) Conc 5 0.1452 – (1.31) – – Conc 4 0.3126 (2.45) – Conc 3 0.2517 – (2.81) – – Conc 2 0.5086 (3.40) – Ownership Firm Foreign Bank Family Adj R2 Sargan (p-Value)

GMM SB salaries

5.0138 (24.01) 6.0995 (17.83) 4.2251 (22.52) 4.3604 (22.80)

5.1999 (27.59) 6.4531 (21.87) – – 4.3692 (28.37)

– – – – – – – –

5.3364 (15.71) 6.6204 (11.63) 4.5323 (14.18) 4.7789 (14.88)

5.1337 (18.80) 6.5132 (14.57) – – 4.6326 (18.79)

– – – – – – – –

0.7285 – –

0.7200 – –

0.5065 – –

0.7950 403.2899 (0.6655)

0.7865 422.5238 (0.6972)

0.6568 681.5953 (0.1247)

All equations use time and firm dummies, and average SB salary. OLS fixed-effects model reports estimates corrected for heteroskedasticity. GMM heteroskedastic-consistent estimates use instruments of lagged ROE, ROA, and sales variables from t  2; . . . ; t  7. The Sargan statistic tests for over identifying restrictions in the model. Regressions 2 and 3 do not have the Bank ownership variable because of the high correlation with the composite bank-influence variable.  t-Value indicates variable significant at 5% level and  significant at the 10% level. Observations ¼ 1365.

statistically significant in three of the five industries. Bank influence is negative and significant in five of the seven industries. Thus, even within most industries banks appear to temper compensation when they have significant influence. 7. Conclusion We have analyzed data on the compensation of members of the supervisory and managing boards of large German corporations in order to satisfy the heightened in-

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Table 5 Managing Board (MB) salaries by industry Dependent variables

Metals and Chemicals Electronic minerals and fiber and precision instruments

Motor vehicles

Food and tobacco

Textiles

ROE

Bank influence Adj R2

1.765 (0.56) 0.0426 (0.29) 0.657 (1.66) 0.5344

0.035 (0.06) 0.078 (5.41) 0.948 (5.36) 0.8864

0.253 (0.32) 0.181 (8.64) 0.948 (10.00) 0.8025

0.063 (0.35) 0.076 (1.74) 0.780 (2.89) 0.0966

0.099 1.442 (0.30) (5.91) 0.002 0.213 (0.01) (9.29) 0.204 2.057 (0.12) (19.62) 0.0167 0.5276

Observations

102

323

102

235

102

Sales

0.024 (0.56) 0.148 (3.32) 0.204 (1.11) 0.9472 221

Other

595

All equations use time and firm dummies, and average MB salary. OLS fixed-effects model reports estimates corrected for heteroskedasticity.  t-Value indicates variable significant at 5% level and  significant at the 10% level. Observations ¼ 1683.

terest in the compensation of German executives. Most of the empirical work on executive compensation has dealt with the United States. This study extends one important aspect of the research done on American executives to Germany. We find, as do studies on the US, that the greater the ownership concentration the less the ability of executives to extract higher levels of compensation. The agency problem caused by the separation of ownership and control appears to exist in Germany as well as elsewhere. We also find that performance and size are generally positively related to compensation, similar to previous studies in the United States. There is evidence that banks serve as monitors of executive compensation for the MB and some evidence with respect to the SB. Block ownership by various groups also restrains compensation. The results of this study are consistent with findings of Schmid (1997) and indicate that in a different institutional setting the same types of economic problems relating to executive compensation hold––that is, there is evidence of agency problems caused by the separation of ownership and control. When ownership is dispersed management can obtain greater monetary compensation. Unfortunately, we do not have information on non-monetary compensation, but we might also expect that lack of control by ownership may enable management to extract greater non-monetary compensation. This study shows that the agency impact on executive compensation in Germany is similar to that in the United States. In addition we find that bank influence reduces executive compensation and that ownership structure can affect executive compensation practices.

Acknowledgements We would like to thank Joachim Schwalbach, Frank Seger, and three anonymous referees for their insightful suggestions on this research. We would also like to thank

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conference participants at the May 2000 Financial Management Association meetings in Edinburgh Scotland, the July 2000 Western Economic Association meetings in San Diego, CA, and the November 2000 Southern Finance Association Meetings in Savannah, GA for their useful comments. The first author acknowledges support from the American Institute for Contemporary German Studies for this research. Appendix A. Means of bank influence variables Bequity: Bank percentage equity ownership of firm. Bsuper: Percent of bankers on the firmÕs SB. Big Votes: Big 3 banks total percentage of votes at shareholder meetings. Bchair: Dummy variable ¼ 1 when banker is chair or deputy chair of SB, ¼ 0 otherwise. All Votes: Total percentage votes of all banks at shareholders meetings.

All Firms Bank influence Independent

Bequity

Bsuper

Big Votes

Bchair

All Votes

0.0550 (0.1233) 0.1748 (0.1698) 0.0188 (0.0742)

0.0889 (0.0755) 0.1724 (0.0770) 0.0630 (0.0550)

0.0952 (0.1743) 0.3206 (0.2033) 0.0271 (0.0842)

0.2235 (0.4172) 0.7342 (0.4446) 0.0654 (0.7477)

0.2072 (0.3111) 0.6825 (0.2224) 0.0627 (0.1476)

Own calculations from multiple sources. (See Section 5 for details.) Standard deviations in parenthesis. Above data are available for all firms for 1986, except Bequity which is available for all firms over each of the 17 years. A firm is considered bank influenced if: Bequity > 25% or if (All Votes > 50%) or (25% < All Votes < 50%) and (Chair or Deputy Chair of the SB is a banker). A firm is Independent if it is not bank influenced. Big 3 banks include: Commerzbank, Deutsche, and Dresdner.

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