Achim Buchwald, Raphaela Hotten, Julia Rothbauer and John P. Weche ORCID logo

The Top 100 Companies Panel Database

Five Decades of Aggregate Concentration Surveys in Germany

De Gruyter | Published online: February 28, 2020
Published Ahead of Print / Just Accepted

1 Introduction

The Monopolies Commission has been continually collecting and processing data on the largest companies in Germany since 1974. This data, which includes a ranking of the Top 100 companies according to domestic value added, personnel and capital linkages between these companies as well as other firm-level figures, have recently become available in panel format (1972–2016) to researchers and the public. This paper gives an overview of that dataset, its applicability, and accessibility.

Recently, increasing attention has been paid internationally to the economic and political power of large companies by researchers and policy makers of all parties. For example, a significant overall increase in market concentration and price-cost markups has been observed in some countries over the last decades (e. g. DeLoecker/Eeckhout 2017; 2018; Calligaris et al. 2018; Weche/Wambach 2018) and the OECD recently held a hearing on the topic (OECD 2018). However, the focus is not only on the economic power in specific product markets, but also on competitive advantages for conglomerates that derive from being active on many markets. Such advantages may take the form of entry barriers or political influence and are currently discussed also with regard to large tech companies, such as Amazon and Google. In the USA, for example, The Economist (2016) reported that the GDP share of the Top 100 companies has risen from 33 percent in 1996 to 46 percent in 2013. In this context, economists also advocate considering the political influence of companies more prominently in economic theory and note that the revenues of large companies today often rival those of governments (e. g. Zingales 2017). Also, researchers have criticized the lack of information on the economic weight of top companies (e. g. White 2017; White 2002).

In Germany, the Monopolies Commission—an independent expert committee, which advises the German government and legislature in the areas of competition policy-making, competition law, and regulation—has the legal mandate to report on the degree of business concentration. In this framework, the Monopolies Commission regularly identifies and surveys the development of the Top 100 companies in Germany to assess the business concentration across markets as an indicator for the concentration of economic and political power. In all but the first three reference years, the criterion to rank the Top 100 companies was domestic value added, which has advantages over other rankings based on sales volumes or similar figures, because with it, only the economic contribution of a company is considered, and not the value of its intermediary consumption produced by other firms. A focus of the surveys is on personnel and capital links between the top companies, because at the time of the Monopolies Commission’s first main report in 1976, the German economy was characterized by many cross-holdings and simultaneous director interlockings, which led to strong interdependencies and mutual influence between companies and financial institutions (the so-called “Deutschland AG”).

The next section presents the general aim of surveying the Top 100 companies. Section 3 will then describe the variables and panel characteristics of the dataset and also give an account of the methodological changes over time. Section 4 will then elaborate on existing research published with the data before the paper concludes with Section 5.

2 The motivation of surveying the Top 100

In 1973, the Monopolies Commission was instituted with the purpose of providing independent scientific information and recommendations to the German government and legislative bodies concerning the competitive situation in the German economy.[1] As stated by law (§ 44 Act against Restraints of Competition (GWB)), the Monopolies Commission publishes a comprehensive main report every two years. One of the aims of the report is to give an account of the status and developments of company concentration and competition in Germany.

Competition analysis is most often concerned with competition between firms on a particular product market, which determines the dynamics of this market and may grant positions of power to single firms. Thus, horizontal product market concentration and its increase, for example through a merger between two firms offering very similar products, is a primary concern. However, most large firms are active on a number of markets. This can lead to corporations with limited power in individual markets, but strong aggregated power of disposition. Measuring only concentration in individual markets therefore fails to capture the kind of power based on a firm’s overall position in the economy. Such forms of power may include access to financial and material resources as well as abilities to influence economic and societal processes. That this is problematic in a socio-political aspect was already recognized by the German legislature in the reasoning for the draft to the second amendment to the Act against Restraints of Competition (GWB).[2]

Against this backdrop, conglomerate or aggregate company concentration becomes an important issue. The Monopolies Commission has thus been identifying the Top 100 companies—based on their value added within Germany[3]—and reporting on their economic activities and interlocking since its inauguration. The information indicates the aggregate concentration in Germany and the resulting concentration of political and economic power. A large part of the economy depends on the management decisions of the largest firms: they are a key factor for employment. Many of them also hold a prominent position in their respective industries.

The Monopolies Commission regularly publishes the results of the Top 100 surveys in its main reports, for example, the share of the aggregated domestic value added of the Top 100 in the total value added in Germany and also of the top companies in particular sectors. The higher the share, the more the economy depends on its top firms. The data shows that, in contrast to other countries such as the USA, the overall economic weight of the top firms has slightly decreased over the last years in Germany.[4]

3 The top 100 panel database

The surveys of the Top 100 companies in Germany have only recently been made available in panel format. Although the data has already been regularly used in academic research in various contexts (see Section 4 for an overview), information had to be manually taken from published main reports of the Monopolies Commission. Since the beginning of 2020 (latest reporting year 2016), information on the Top 100 companies from 1972 onwards is publicly available free of charge on the institution’s website.[5] The panel may be put to use for a vast spectrum of research questions and may also serve illustrative and descriptive purposes. The individual variables, panel characteristics, and prospective applications of the data are presented in the following.[6]

3.1 Variables and panel characteristics

The panel covers the Top 100 companies in Germany since 1972 at a biannual interval.[7] The dataset provides information on core performance variables, such as value added, cash flow, business volume, fixed assets, and the number of employees. Also, ownership and board information for individual companies is provided, such as the capital and personnel links between the Top 100 and other companies.

Moreover, data on the individual companies’ M&A activity is included based on information from the German competition authority. In particular, the number of M&As of a firm that the Federal Cartel Office assented to in the reporting period is available. Also, some corresponding macro variables are already included in the dataset, which enables an analysis in relation to aggregate figures. For example, the total number of M&As that the German Federal Cartel Office assented to in the reporting period is available. Other macro variables in the dataset are the total value added and the total employment of the German economy. The Top 100 companies’ share in the total economy’s value added, for example, regularly serves as an indicator for the aggregate company concentration in Germany and the resulting concentration of political and economic power (most recently in The Monopolies Commission 2018).

The industries of economic activity are captured at the two- and three-digit NACE classification level.

All in all, the panel covers 2,300 company–year observations, but not all companies are in the sample for the whole of the sample period (1972–2016). The reason is that a company dropped out of the sample in a period if they were not ranked among the 100 largest companies in that period (unbalanced panel). However, if a company drops out of the sample, the reason for this drop-out is indicated in the data (merger, insolvency, etc.). The identification numbers are assigned consistently, meaning that if a company re-entered the sample, it was given the same ID number as before.[8]

3.2 Methodological changes over time

While there have been minor changes in the methodology over the decades, partly due to changes in legislation and reporting standards, the variables and their calculation have in general remained the same. The following paragraphs will give a detailed account of the major changes in the panel over the years. All year specifications in this section refer to the reporting years.

When the ranking started in 1972, the Top 100 companies were listed according to their sales volume. At that time, sales volume was chosen primarily for reasons of practicability, as this figure was readily available from the annual reports of the corporations. In 1978, the ranking variable was changed to value added in Germany, which was also raised for the first time. Compared to the sales volume, domestic value added has some major advantages. It allows considering corporations in the ranking for which sales volume is not a sensible measure, such as companies in banking and insurance, which were not included at all in the ranking before. Additionally, while the sales volume captures the whole revenue of the firm without regard to the cost of its inputs, value added indicates only what the firm is actually responsible for, and thus eliminates intermediate consumption. It is thus generally considered to be more appropriate to use a firm’s contribution to the national output to measure aggregate concentration, which led the Monopolies Commission to choose this measure as a basis for its ranking to improve its informative value.[9] However, considering domestic value added meant more effort in the data gathering process because companies are not legally required to disclose these figures in their annual reports. Therefore, in most cases, the domestic value added had to be additionally surveyed, and in some cases, estimated. As a result of this change, the ranks of the firms shifted considerably in that year.

However, sales volume has continued to be captured in the data. As it is only a sensible measure for companies in production, trade, or services, for banks, the panel indicates the balance sheet total instead of the sales volume. For insurance companies, sales volume was replaced by premium income.

Four years after the first report, the ranking started to list the number of persons employed in Germany as an additional variable, which has been included in every report since then. The number of employees is essential for assessing the importance of a company, especially in the context of political weight, and would yield a different ordering of the firms.

In 1978, also the new variables capital assets and cash flow were considered in the survey. Capital assets, which include fixed assets as well as shares of other firms that were meant to improve business operations, was considered to be important to assess the investment behavior of large firms. Cash flow was included in order to have an indicator of the financial strength of the companies in the ranking, but was not considered for banks and insurance companies. Both of those variables were excluded again from the ranking in 2016.

Two other blocks of variables were added to the panel in 1978 to take into account capital and personnel ties between companies against the background of the “Deutschland AG”. Since then, information on the ownership structure of each firm has been provided. To complement the capital ties given by the ownership structure, the Monopolies Commission also started to survey interlocking directorates between the Top 100 companies that year.

4 Previous research applications

The panel data of the 100 largest German corporations has been a widely used dataset in different areas of empirical economic and social research, as well as in policy consultation. Most of the related research focuses on the ownership and board information.

In early studies, Schönwitz and Weber (1980; 1982) discuss the potential anti-competitive effects of interlocking directorates based on the surveys published by the Monopolies Commission. Researchers in the field of corporate governance used the data on the 100 largest companies to investigate the development and the proceeding disintegration of the formerly dense network of cross-shareholdings and interlocking directorships via management and supervisory board seats beginning in the late 90s, the so-called “Deutschland AG”. While Heinze (2002) reports a general high level of continuity in his empirical structural analysis of the director network in the largest German corporations during the period 1989 to 2001, a quantitative decline of representatives of financial firms is observable (Heinze 2004). These findings are in line with an empirical study of Beyer (2006) for the time period 1996 to 2002. Höpner and Krempel (2004) focus on capital ties between the largest German firms and document a process of network erosion from the year 1996 until 2000.[10]Noll et al. (2007) trace this process of disintegration for the years 1996 until 2004. As a consequence of the significant reduction of cross-shareholdings and multiple directorships between financial and non-financial firms, outside control by the market gained in importance (Höpner 2004). This change in the corporate governance structures in Germany also correlated with increasing managerial compensation. However, Balsmeier and Peters (2009) find a positive relation between the number of external supervisory board mandates of executive directors and their remuneration.

Other papers focus on the identification of factors determining the establishment of firm networks via interlocking directorships (Balsmeier/Buchwald 2011; Buchwald 2012). Another stream of the literature in the field of empirical corporate governance research addresses the influence of different inter-firm relations on corporate behavior and outcomes. Höpner and Müllenborn (2010) use data on the 100 largest companies to examine questions of co-determination and find a high degree of co-determination particularly in firms that are part of the capital network of cross-shareholdings. Balsmeier et al. (2010a) find that both CEOs and chairmen of the supervisory board with external board mandates are associated with higher corporate performance. At the same time, forced CEO replacements are less likely and the turnover-performance sensitivity declines with an increasing number of outside board positions of the CEO (Balsmeier et al. 2010b). Balsmeier et al. (2015) are interested in the monitoring intensity of corporate supervisory boards and find evidence that monitoring directors with simultaneous outside board affiliations increase the likelihood of executive turnover. Balsmeier et al. (2012) focus on CEO succession decisions and find that firms with external executive directors on the supervisory board are more likely to appoint an external candidate. Having supervisory board members with additional external monitoring positions is found to increase the likelihood of internal replacements. Balsmeier et al. (2014) concentrate on the significance of multiple directorships for innovative firm activities, finding it to be an important factor for long-term oriented firm performance and growth. They show that having outside directors in the boardroom who are experienced in innovation is associated with a higher number of both patent applications and citations. Balsmeier and Buchwald (2015) find that having internally appointed CEOs is, during their first years in office, associated with a significantly higher number of patents compared to externally appointed top managers pointing to the importance of firm-specific knowledge in terms of innovation.

5 Concluding remarks and research outlook

The Monopolies Commission regularly identifies and surveys the development of the Top 100 companies in Germany to assess the degree of business concentration across markets as an indicator of the concentration of economic and political power. This data, which includes a ranking of the Top 100 companies according to domestic value added, personnel and capital linkages between these companies, and other firm-level figures, has recently become available in panel format to researchers and the public. To date, the panel provides information on the Top 100 companies in Germany over almost five decades (1972–2016). In all but the first three reference years, the criterion for ranking the Top 100 companies was domestic value added, which has advantages over other rankings, because only the economic contribution of a company is considered, and not the value of its intermediary consumption produced by other firms.

The Top 100 data has already been a widely used dataset in different areas of empirical economic and social research, as well as in policy consultation. However, the Top 100 data offers great scope for future research. For instance, research could address the relevance of director or financial firm linkages on corporate behavior like growth or diversification strategies, particularly in an international context.

Whereas most of the previous research has focused on ownership and board information, another area for future research could be the dependency of macroeconomic developments on individual players at the micro-level. Such a phenomenon, also known as granularity, has not been recognized in the classical macroeconomic theory for a long time, but recent research results have put emphasis on the fact that individual firms or managers are able to determine macroeconomic developments due to their disproportionate economic weight (e. g. Gabaix 2011).[11] Especially, a complementary use of the Top 100 data in combination with other datasets may prove useful for empirical researchers as well as students and journalists.


The authors would like to thank Mert Bakirci and Jana Gieselmann for excellent assistance in the data preparation.


Balsmeier, B., A. Buchwald (2015), Who Promotes More Innovations? Inside Versus Outside Hired CEOs. Industrial and Corporate Change 24 (5): 1013–1045. Search in Google Scholar

Balsmeier, B., A. Buchwald (2011), Motive der Ausübung externer Kontrollmandate durch Vorstandsvorsitzende in deutschen Großunternehmen. Die Betriebswirtschaft 71 (2): 101–119. Search in Google Scholar

Balsmeier, B., A. Buchwald, A. Dilger, J. Lingens. (2015), Executive Turnover and Outside Directors on Two-Tiered Boards. Managerial and Decision Economics 36 (3): 158–176. Search in Google Scholar

Balsmeier, B., A. Buchwald, H. Peters (2010a), Auswirkungen von Mehrfachmandaten deutscher Vorstands- und Aufsichtsratsvorsitzender auf den Unternehmenserfolg. Jahrbücher für Nationalökonomie und Statistik 230 (5): 547–570. Search in Google Scholar

Balsmeier, B., A. Buchwald, H. Peters (2010b), Outside Board Memberships of CEOs: Expertise or Entrenchment? DICE Discussion Paper No. 26. Search in Google Scholar

Balsmeier, B., A. Buchwald, J. Stiebale (2014), Outside Directors on the Board and Innovative Firm Performance. Research Policy 43 (10): 1800–1815. Search in Google Scholar

Balsmeier, B., A. Buchwald, S. Zimmermann (2012), The Influence of Top Management Corporate Networks on CEO Succession. Review of Managerial Science 7 (3): 191–221. Search in Google Scholar

Balsmeier, B., H. Peters (2009), Personelle Unternehmensverflechtung und Vorstandsgehälter. Zeitschrift für Betriebswirtschaft 79 (9): 967–984. Search in Google Scholar

Beyer, J. (2006), Vom Netzwerk zum Markt? Zur Kontrolle der Managerelite in Deutschland. S. 177–198 in: H. Münkler, G. Straßenberger, M. Bohlender (Hrsg.), Deutschlands Eliten im Wandel. Campus Verlag, Frankfurt am Main/New York. Search in Google Scholar

Beyer, J. (2003), Deutschland AG a.D.: Deutsche Bank, Allianz, und das Verflechtungszentrum des deutschen Kapitalismus. S. 118–146 in: Streeck, W./Höpner, M. (Hrsg.), Alle Macht dem Markt. Fallstudien zur Abwicklung der Deutschland AG. Campus Verlag, Frankfurt am Main. Search in Google Scholar

Beyer, J., M. Höpner (2003), The Disintegration of Organised Capitalism: German Corporate Governance in the 1990s. West European Politics 26 (4): 179–198. Search in Google Scholar

Buchwald, A. (2012), Welche Unternehmen berufen Vorstandsvorsitzende und andere Vorstände als externe Kontrolleure? Eine empirische Analyse der Präsenz von externen Vorständen in den Aufsichtsräten deutscher Großunternehmen. Die Unternehmung - Swiss Journal of Business Research and Practice 66 (2): 93–126. Search in Google Scholar

Calligaris S., C. Criscuolo, L. Marcolin (2018), Mark-ups in the digital era. OECD Working Paper No. 10/2018, April 2018. Search in Google Scholar

DeLoecker, J., J. Eeckhout (2018), Global Market Power. CEPR Discussion Paper No. 13009, June 2018. Search in Google Scholar

DeLoecker, J., J. Eeckhout (2017), The Rise of Market Power and the Macroeconomic Implications. NBER Working Paper No. 23687. Search in Google Scholar

Gabaix, X. (2011), The Granular Origins of Aggregate Fluctuations. Econometrica 79 (3): 733–772. Search in Google Scholar

Heinze, T. (2002), Die Struktur der Personalverflechtung großer deutscher Aktiengesellschaften zwischen 1989 und 2001. Zeitschrift für Soziologie 31 (5): 391–410. Search in Google Scholar

Heinze, T. (2004), Dynamics in the German System of Corporate Governance? Empirical Findings Regarding Interlocking Directorates. Economy and Society 33 (2): 218–238. Search in Google Scholar

Höpner, M., L. Krempel (2004), The Politics of the German Company Network. Competition & Change 8 (4): 339–356. Search in Google Scholar

Höpner, M. (2004), Was bewegt die Führungskräfte? Von der Agency-Theorie zur Soziologie des Managements. Soziale Welt 55 (3): 263–282. Search in Google Scholar

Höpner, M., T. Müllenborn (2010), Mitbestimmung im Unternehmensvergleich. Ein Konzept zur Messung des Einflusspotentials der Arbeitnehmervertreter im mitbestimmten Aufsichtsrat. Industrielle Beziehungen 17 (1): 7–29. Search in Google Scholar

Monopolkommission (2018), XXII. Hauptgutachten: Wettbewerb 2018. Nomos, Baden-Baden, forthcoming. Search in Google Scholar

Monopolkommission (1982), IV. Hauptgutachten. Fortschritte bei der Konzentrationserfassung. Nomos, Baden-Baden. Search in Google Scholar

Noll, B., J. Volkert, N. Zuber (2007), Zusammenhänge zwischen Unternehmensverflechtungen und -gewinnen, Rekrutierung von Führungskräften und deren Einkommenssituation. Bericht an das Bundesministerium für Arbeit und Soziales Vb 4-52061-26. Pforzheim/Tübingen. Search in Google Scholar

OECD (2018), Market Concentration. Issues Paper by the Secretariat, DAF/COMP/ WD(2018)46, April 2018. Search in Google Scholar

Schönwitz, D., H.-J. Weber (1980), Personelle Verflechtungen zwischen Unternehmen. Eine wettbewerbspolitische Analyse. Zeitschrift für die gesamte Staatswissenschaft 136: 98–112. Search in Google Scholar

Schönwitz, D., H.-J. Weber (1982), Unternehmenskonzentration, personelle Verflechtungen und Wettbewerb. Eine Untersuchung auf der Grundlage der hundert größten Konzerne der Bundesrepublik Deutschland. Baden-Baden. Search in Google Scholar

The Economist (2016), The rise of the superstars. Special Report, 17. September 2016: 3–16. Search in Google Scholar

Wagner, J. (2012), The German manufacturing sector is a granular economy. Applied Economics Letters 19 (17): 1663–1665. Search in Google Scholar

Wagner, J., J.P. Weche (2020), On the granularity of the German economy – first evidence from the top 100 companies panel database, Applied Economics Letters, DOI: 10.1080/13504851.2020.1722790. Search in Google Scholar

Weche, J.P., A. Wambach (2018), The Fall and Rise of Market Power in Europe. ZEW Discussion Paper No. 18-003. Search in Google Scholar

White, L.J. (2017), What has Been Happening to Aggregate Concentration in the U.S. Economy in the 21st century? SSRN Working Paper: April 2017. Search in Google Scholar

White, L.J. (2002), Trends in Aggregate Concentration in the United States. Journal of Economic Perspectives 16 (4): 137–160. Search in Google Scholar

Zingales, L. (2017), Towards a Political Theory of the Firm. Journal of Economic Perspectives 31 (3): 113–130. Search in Google Scholar

Article note

The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors and should not be attributed in any manner to their employers or affiliations.


Table 1:

Overview of variables.

Variable Description Year
id_mc Individual ID number. In case of M&A, the resulting company was usually given the ID of the largest party. In case of large restructuring measures, a new ID was given. 1972–today
rank Rank by domestic value added between 1 and 100. 1978–today
rank_s Rank by sales 1972–1978
year Reporting year 1972–today
name Name of the corporation 1972–today
failure Indicates whether the company will fail to appear in the Ranking in the following year (equal to 1). Note that there may be missing entry information in 1976 when observations do not appear in the value added ranking due to methodological changes. 1972–today
failure_type Reason for the drop-out: 1. External shrinkage (sale, separation) 2. Internal shrinkage (decline in sales/employees with equal scope of consolidation) 3. Stagnation/general rise of the level of value added 4. Methodology 5. M&A 6. Other (e. g. insolvency) 1972–today
va Domestic value added within Germany in million EUR. Data gathered from either the annual reports or in an additional survey. In some cases, figures had to be estimated. Note that the calculation may vary slightly over time and depending on the type of company and/or availability of the data. For a detailed description of the methodology, see the respective reports, e. g. the Appendix to Chapter II of Monopolkommission (2018). 1978–today
bv Business volume in million EUR. For corporations active in production, trade, or services (non-financial corporations), this value is equal to sales. In the years before 1978, it is equal to 75 % of sales for trading companies in order to improve the comparability to other companies in those years. For banks, the value is equal to the balance sheet total and for insurance companies, it is equal to gross premium income. All values are gathered for corporate divisions within the country. 1972–today
assets Domestic fixed assets in million EUR, including immaterial assets. For insurance companies, capital assets were indicated. For numerous companies, no figure for domestic fixed assets was available. For some of them, the worldwide figures are indicated instead. 1978–2014
employment Number of employees with mandatory social security contributions within Germany. 1976–today
cashflow Domestic cash flow in million EUR. Generally used as an indicator for the liquidity and internal financial strength of a company. Calculated by taking annual net profit/annual net loss + amortizations + changes in pension provisions compared to the previous year. Values were taken from the P&L statements. As usual, this value is not available for banks and insurance companies. If domestic cash flow was not available, it was estimated with the same relation as value added (For details on estimation methods, see the annex of the Monopolies Commission’s main reports). 1978–2014
ma Number of mergers and acquisitions of the firm that the German Federal Cartel Office has assented to in the reporting period (year under review + following year, for 1974 in addition the previous year). From 2006 onwards, this may also include M&As that were declared and permitted, but not implemented (a change due to the 7th amendment to the GWB). Before 2006, this number only covers M&As declared, permitted, and implemented. Therefore, the comparability before and after 2006 is limited. Note that this variable also includes attachment cases between 1972–1998 (before the 6th amendment to the GWB), which are also given separately in the next variable and can therefore be subtracted. Attachment cases are cases which had to be indicated to the Cartel Office, but were not subject to review under § 24 II Nr. 8 GWB, because the acquired firm was too small to be above the necessary thresholds. Note that the thresholds have slightly changed over time. 1972–today
attachment Indicates how many of the M&As were attachment cases (see description above). 1972–1998
ma_100 Indicates the number of M&As with participation of at least one Top 100 company. Note that this is not equal to the sum of all the individual values for the Top 100, because cases in which two or more firms were involved in an M&A were counted only once, but will appear for every individual firm participating in it. 1972–2002
branch Economic branches as listed by the German Federal Statistical Office according to the most recent classification. Starting in 2010, the industry classification from 2008 (WZ2008) is used, between 2004–2008, the WZ2003 is used, between 1994–2002, the WZ1993 is used, between 1978–1992, the WZ1979 is used, and between 1972-1976, the WZ1970 is used. Until 1978 (incl.), only the branch with the highest sales is indicated. 1972–today
branch_hg Indicates the broad sector. Categories are manufacturing, construction, trade, services, insurance, and banking. 1972–today
legal Legal form of the corporation. 1972–2014
va_econ Total value added of the German economy that year in million EUR. Until 2002, net value added, and from 2004, gross value added. Excluded are the public sector, non-profit organizations, and real estate and housing. Source: German Federal Statistical Office. 1978–today
employment_econ Total number of employees with mandatory social security contributions in the German economy as a whole that year. Excluded are non-profit organizations, private households, regional authorities, public administration, and social insurances. Source: German Federal Employment Agency 1976–today
ma_econ Total number of M&As that the German Federal Cartel Office assented to in the reporting period (year under review + the following year, for 1974 the previous year additionally). Note the change due to the 6th amendment to the GWB as in the description of ma. 1974–today

    Note: All currency values are in Euro. Values that were originally in DM were transformed using the irrevocable fixed conversion rate of 1.95583 DM = 1 Euro.

Table 2:

Overview of variables – Capital Shares.

Variable Description Year
cap100 Capital shares held by other Top 100 corporations (cross holdings). Includes direct holdings as well as indirect holdings, where the latter are weighted with the respective indirect proportions. 1978–today
capfo Capital shares held by foreign investors (foreign ownership). 1978–today
cappu Capital shares held by the public sector (public ownership). 1978–today
capfam Capital shares held by individuals, families or family foundations (family ownership). 1978–today
freefloat Capital shares in free float. 1978–today
capother Capital shares held by companies not in the Top 100, institutional investors incorporated in Germany, cooperatives, unions, as well as unidentified owners. 1978–today

    Note: Capital shares held by different groups in percent. Values refer to the end of the reporting period. App. stands for approximately. Starting in 2004, preferred shares are excluded from this value. Before 2004, percentages include both preferred shares and ordinary shares. For the legal form vag, capital shares cannot be indicated, values are missing (.).

Table 3:

Overview of variables – Interlocking Directorates.

Variable Description Year
interlock_out Number of companies (not persons) within the Top 100 to which there exist linkages through persons from the own managing board sitting in the other firm’s supervisory board. 1978–today
interlock_in Number of companies within the Top 100 to which there exist linkages through persons of the other firm’s managing board sitting in the own supervisory board. 1978–today
interlock_fin Number of banks and insurance companies included in interlock_in. In 1978, banks only. 1978–today
interlock_other Number of companies within the Top 100 to which there exist linkages through other mandate holders in both firm’s supervisory boards. 1978–today
Published Online: 2020-02-28

© 2020 Oldenbourg Wissenschaftsverlag GmbH, Published by De Gruyter Oldenbourg, Berlin/Boston