Keeping it real or keeping it simple? Ownership concentration measures compared

• Published date: 01 September 2020
• DOI: http://doi.org/10.1111/eufm.12249
• Date: 01 September 2020

Eur Financ Manag. 2020;26:958–1005.wileyonlinelibrary.com/journal/eufm958

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© 2019 John Wiley & Sons Ltd.

DOI: 10.1111/eufm.12249

ORIGINAL ARTICLE

Keeping it real or keeping it simple?

Ownership concentration measures compared

Taylan Mavruk

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Conny Overland

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Stefan Sjögren

Department of Business Administration,

University of Gothenburg, Gothenburg,

Sweden

Correspondence

Taylan Mavruk, Department of Business

Administration, University of

Gothenburg, Box 610, SE‐405 30

Gothenburg, Sweden.

Email: taylan.mavruk@handels.gu.se

Funding information

VINNOVA and the Centre for Finance at

the University of Gothenburg

Abstract

We analyze the distributional properties of ownership

concentration measures and find that measures come

from different underlying statistical distributions. Con-

sistent with theory, some measures that are classified

to represent a monitoring dimension have a positive

influence on firm performance; other measures that are

interpreted to represent a shareholder conflict dimen-

sion are negatively related to firm performance. How-

ever, other measures deviate from this pattern, and

therefore, we cannot conclude that simple measures can

replace complicated measures. Some measures are more

suitable for analyzing the relationship between manage-

ment and owners, whereas other measures are more

suitable for analyzing the relationships among owners.

KEYWORDS

distributional properties, monitoring dimension, ownership concen-

tration measures, shareholder conflict dimension

JEL CLASSIFICATION

C18; C46; C81; D74; G34; L25

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We are very grateful to the editor, John A. Doukas, and the anonymous referees for insightful comments on earlier

drafts, which have helped to improve the quality of the paper. We thank Uday Rajan, H. Nejat Seyhun, and M. P.

Narayanan at the Ross School of Business, University of Michigan for their valuable discussions, comments, and

suggestions. We thank Jan Bartholdy and other seminar participants at the 4th workshop of the Nordic Corporate

Governance Network, Reykjavik University, the Copenhagen Business School, and at the World Finance Conference, St

Johns University, New York for their comments and suggestions. We also thank Karin S. Thorburn, Shubhashis

Gangopadhyay, Roger Wahlberg, Ted Lindblom, Mattias Hamberg, Martin Holmén, Evert Carlsson, and Tamir Agmon

at the Centre for Finance and Industrial and Financial Management seminars at the University of Gothenburg for their

valuable comments and advice. We thank Renée Adams for her review and valuable comments. We gratefully

acknowledge Euroclear and SIS Ägarservice for providing data and Dennis Leech for making available the power index

algorithms on his webpage. The usual disclaimer applies. This project was conducted with funding from VINNOVA and

the Centre for Finance at the University of Gothenburg.

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INTRODUCTION

A crucial matter regarding the empirical study of central corporate governance issues is how the

ownership of corporations should be measured. In the corporate governance literature, we find

measures ranging from simple proxies, such as the largest owner's voting share, to the

computation of advanced power indices based on game theory. Earlier studies have examined

the distributional properties of a selection of different ownership concentration measures (e.g.,

Bøhren & Ødegaard, 2006; Leech, 2002) and compared how they are related to firm

performance (e.g., Edwards & Weichenrieder, 2009). To our knowledge, there has been no study

that takes the full range of ownership measures and compares their underlying statistical

properties. We conduct a more detailed examination of the statistical properties of ownership

measures. This examination increases (a) our knowledge regarding whether the simple

measures found in most empirical research are sufficient to capture the role of ownership or if

more elaborate concentration measures are necessary and (b) our understanding of the

ownership dimensions that are reflected in different concentration measures.

The relationship between ownership concentration and firm performance is a common topic

in studies that make use of ownership measures. These studies yield conflicting results. For

instance, Morck, Nakamura, and Shivdasani (2000), Thomsen and Pedersen (2000), Gedajlovic

and Shapiro (2002), Nguyen, Locke, and Reddy (2015), and Bykova, Molodchik, and Shamilova

(2017) find a positive relationship between ownership concentration and firm performance,

whereas Leech and Leahy (1991), Lehmann and Weigand (2000), and, to some degree,

Claessens, Djankov, Fan, and Lang (2002) and Azar, Schmalz, and Tecu (2018) find that

ownership concentration leads to weaker firm performance. Other studies document a

nonlinear (De Miguel, Pindado, & de la Torre, 2004; McConnell & Servaes, 1990), a mixed

(Gedajlovic & Shapiro, 1998; Gugler, Mueller, & Yurtoglu, 2006; Iwasaki & Mizobata, 2019), or

even a nonexistent (Barontini & Caprio, 2006; Demsetz & Villalonga, 2001) relationship

between ownership concentration and firm performance.

Studies show different results partly because they examine different countries, different time

periods, and use different methods (cf. Wang & Shailer, 2013). Such differences make the

interpretation of the relationship between ownership and performance more difficult (Adams &

Ferreira, 2008). Analyzing ownership concentration, the focus of this study, is also more

difficult when using different concentration measures, as they could capture different aspects of

how ownership drives decision‐making.

Considering ownership concentration, there are at least two potential causes of conflict that

could affect decision‐making in firms: one has to do with the relationship between managers

and owners, and the other relates to the interplay between owners. In line with Jensen and

Meckling (1976), utility‐maximizing managers could give rise to agency costs. Such agency costs

can be reduced through increases in ownership concentration since large shareholders have

stronger incentives to engage in costly monitoring. We call this the monitoring dimension.

However, conflicting interests among owners could also curb firm financing decisions and firm

performance, as concentrated ownership paves the way for large shareholders to expropriate

minority shareholders (Burkart, Gromb, & Panunzi, 1997; Claessens et al., 2002; Croci, Doukas,

& Gonenc, 2011; Shleifer & Vishny, 1997). We call this the shareholder conflict dimension.

A concentration measure could be better suited for analyzing one of the two dimensions but

could be worse for the other. For instance, when studying the monitoring dimension, a measure

such as the voting share held by the largest owner could be a reasonable proxy for

concentration, as having self‐dealing managers is not in the best interest of shareholders. If,

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instead, the shareholder conflict dimension is the main concern, a measure of the largest

shareholder is less likely to contain satisfactory information. The largest shareholder's

opportunity to extract private rent depends not only on the shareholder's own voting share

but also on the influence of the other shareholders. Therefore, previous research may in fact

study different phenomena, despite claiming to study the same. In contrast, we examine what

the distributional properties are of different concentration measures, whether they capture

different dimensions of ownership, and whether they return consistent results when relating

them to commonly used performance measures?

The fact that these conflicts can be of different magnitude can be explained by the separation

of voting rights (control) and cash flow rights. While a higher value of control rights is expected

to increase an owner's ability to extract rents from the firm at the expense of the other owners, a

higher value of cash flow rights might create good incentives for monitoring management.

Thus, one would expect that the controlling owners’alignment with the other owners will

decrease as the voting rights deviates from the cash flow rights (Claessens et al., 2002; Edwards

& Weichenrieder, 2009) and would therefore lead to increased shareholder conflict. The

existence of dual shares should affect the monitoring dimension to a lesser degree.

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In our

analysis, to enhance our understanding of the diverse effects of ownership concentration on

corporate governance, we consider the distinction between control and cash flow rights.

Based on a sample of all Swedish companies listed on the Stockholm Stock Exchange (SSE)

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between 2000 and 2009 and using ultimate controlling owners’information derived from Owners

and Power data (Fristedt & Sundqvist, 2001–2010) and data on share prices and accounting

variables from Bloomberg, we create 20 ownership concentration variables measuring the

ownership structure for an unbalanced panel of 361 firms. By limiting the data set to include only

Sweden, contextual differences are mitigated because all observations are subject to the same legal

institutions and the same time‐specific macro events. Data quality problems are also mitigated as

our data set shows a large cross‐sectional variation in concentration measures and is free from

incompleteness and nonrandom reductions in sample size.

We carry out three stages of analyses. In the first stage, we examine the distributional properties

of the different ownership measures by using the following: (a) the Spearman rank correlation test

to determine whether the ownership concentration measures rank firms differently; (b) the

Wilcoxon matched‐pairs signed‐rank test to determine whether distributions of the concentration

measures come from the same distribution; and (c) the Anderson–Darling test to determine what

distribution best fits each measurement. In the second stage, we perform a principal component

analysis (PCA) and examine whether the two dimensions (monitoring and shareholder conflict) are

discernible in the underlying factors. In the third stage, we relate the ownership concentration

measures to firm performance. Our aim is to providesomeformalreasoningforhowandwhythe

choice of the concentration measure can affect analytical outcomes such as firm performance. We

use different models to carefully examine the endogeneity issues with ownership variables because

the causes of endogeneity in these different ownership measures are uncertain and depend on

which dimension the particular measure represents. We do not expect all models to produce the

same signs for the particular ownership measure; however, our roadmap for the decision criteria is

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Edwards and Weichenrieder (2009), finding that the weakest link principle does not perform well, indicate that it cannot be used to identify the effects of

ownership when there is a separation of voting and control rights. They instead suggest and perform a comparison of voting power indices. There is solid

evidence that control benefits do exist (Adams & Ferreira, 2008; Barclay & Holderness, 1989; Bergström & Rydqvist, 1990; Bertrand, Mehta, & Mullainathan,

2002; Dyck & Zingales, 2004; Franks & Mayer, 2001; Gugler & Yurtoglu, 2003; Johnson, La Porta, Lopez‐de‐Silanes, & Shleifer, 2000; Lauterbach & Pajuste,

2015; Nenova, 2003; Saggese, Sarto, & Cuccurullo, 2016; Zingales, 1994).

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NASDAQ OMX Stockholm.

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