CEO age, shareholder monitoring, and the organic growth of European firms

Why do some firms grow faster than others? This question touches upon a key feature of market economies, which has implications for macroeconomic performance, the evolution of industries, business strategy, and policy-making. From a theoretical perspective, firm growth has been approached from different angles (Geroski, 1999). Starting with stochastic models dating back to the seminal work of Gibrat (1931), much attention has been paid to the question, even in recent times by Hart and Oulton (1996), Bottazzi and Secchi (2006) and Arata (2019), because of the consistent properties of growth rate distributions across countries, industries, and over time (Dosi et al., 2015). Dynamic competitive equilibrium models (Jovanovic, 1982; Ericson & Pakes, 1995; Cabral & Mata, 2003; Cooley & Quadrini, 2004) explain businesses’ growth through the structural characteristics of firms, such as newer or younger and smaller sized firms, a higher level of efficiency, investment, and more effective access to financial resources.¹ Evolutionary models (Dosi et al., 1995; Nelson & Winter, 1982), which are grounded in the Schumpeterian idea of “creative destruction,” have examined the role of innovation in firm dynamics.²

While all these strands of the literature have focused on the role of firms’ characteristics in explaining their episodes of size expansion (e.g., Arrighetti, 1994; Capasso et al., 2015; Yang & Tsou, 2020), the role exerted by managers’ targets and characteristics in firm growth has been much less explored, with few exceptions such as the literature on the impact of the characteristics of the firm founders on the growth of new firms (e.g., Colombo & Grilli, 2005, 2010). This is unfortunate, especially as top executives are the main agents responsible for corporate strategies (Bertrand & Schoar, 2003; Foss & Pedersen, 2016; Hambrick & Mason, 1984).

The principal-agent (P-A) framework, which is traditionally adopted in industrial organization to model the relationship between shareholders and managers’ interests within the firm, sheds light on how firm growth may depend on executives’ choices. Indeed, while the owners of the firm (principals) are interested in the expected present value of the firm’s economic profits, managers (agents) aim at maximizing their utility, which relates more to firm size than to profit (see Baumol, 1959; Marris, 1964; Williamson, 1964). This is because of the positive relationship between managers’ compensation and firm size (Jensen, 1986),³ which has been empirically confirmed by several studies (see Brunello et al., 2001; Cosh & Hughes, 1997; Gabaix et al., 2013; Kato, 1997). Based on the P-A framework, managers are expected to push firm size (through growth) beyond the “optimal” size envisaged by shareholders, thus possibly deviating from profit maximization and creating a conflict of interest within the firm.

This study adopts the P-A framework to show how managers’ targets and characteristics help explain that part of growth rate variability among firms, which cannot be ascribed to the stochastic, structural, financial, and technological characteristics of the firm. We investigate whether firms’ higher propensity to grow may be ascribed to the specific incentives of young chief executive officers (CEOs). We hypothesize that the objective of signaling their managerial talent in the market, and the possibility of receiving a better stream of future compensation benefits, leads younger CEOs to seek higher firm growth in contrast to their older counterparts. This may well create a divergence of interests with shareholders. Consistent with this framework, we expect the incentives for firm growth given to younger CEOs to be hindered in firms with more concentrated ownership, where shareholder monitoring is more stringent (Chaigneau & Sahuguet, 2018; Shleifer & Vishny, 1986).

This study focuses on organic growth, which is usually proxied by the rate of growth of sales or assets. Even if firms achieve their growth through mergers and acquisitions (M&As), we believe that the interest in organic growth is grounded in three facts. First, the majority of actual growth episodes are due to the internal expansion of firms in terms of capacity and output. Second, M&As are usually considered “risky” strategies:⁴ these may be preferred by young CEOs simply because of their lower risk aversion due to their youth (Falk et al., 2018). In this study, we include proxies for CEOs’ risk tolerance and attempt to estimate the role of young CEOs’ incentives and targets in firm growth, “net of” their attitude toward risk.⁵ Third, economic theory has shown that organic growth can generate significant agency problems.⁶

We analyze the role of CEO age in organic growth from a large sample of manufacturing firms from seven European countries (Austria, France, Germany, Hungary, Italy, Spain, and the United Kingdom) in the period 2009–2014. The database we employ results from merging Bureau Van Dijk’s (BvD) Amadeus database with the European Firms in a Global Economy (EFIGE) survey. The EFIGE survey has several unique features. First, it is a sample built to represent the manufacturing sectors of the countries covered. In particular, the sampling design follows a stratification by industry, region, and firm size. A relevant implication of this design of this study is that we can consider a large number of mostly privately held firms (only about 2% of firms in the sample are listed) including over 90% small- and medium-sized enterprises (SMEs; with less than €50 million turnover). This allows us to highlight that agency problems in the relationship between shareholders and managers are not an exclusive feature of large and widely held firms. Indeed, while a firm where one person wields both the ownership and management roles can be considered the base case of zero-agency costs (Jensen & Meckling, 1976), the initial separation between ownership and control takes place precisely when a firm is small (Danielson & Scott, 2007). Second, data from EFIGE are fully comparable across countries, since they are derived from responses to the same questionnaire, administered over the same time span (January to May 2010). Third, EFIGE includes a wide range of questions that allow us to control for a rich set of important firm and CEO characteristics, which is key to limiting omitted variable bias issues. Our final sample includes about 7200 manufacturing firms, across twenty-four 2-digit industries.

Our econometric analysis shows three key results. First, when controlled for industry-country unobserved heterogeneity and a relevant set of firm and CEO characteristics, firms managed by CEOs younger than 45 grow faster (over the period 2009–2014) in terms of both sales and total assets than those managed by older CEOs at the median (50^th percentile) of the conditional growth rate distribution. Through quantile regressions, we also show that the effect is asymmetric along the distribution of growth rates: firms managed by younger CEOs do grow more than their counterparts managed by older CEOs, and this difference is stronger in the highest (75^th and 90^th) conditional percentiles. This result is consistent across all the countries considered. Second, our results show no significant statistical relationship between the growth in operating profits and CEO age. We consider this second result as evidence of a potential divergence of interests between CEOs and shareholders. Third, and consistently with agency theory, we find that in firms characterized by more effective monitoring of managers' decisions (proxied by more concentrated ownership), the relationship between CEO age and firm organic growth is much weaker.

As EFIGE is a cross-sectional survey, we cannot employ an identification strategy based on changes in the longitudinal dimension of the CEO age variable. Nonetheless, we control for different time horizons over which growth rates are calculated, to minimize the risk of biased results due to the (unobserved) turnover of CEOs. Moreover, we take the potential endogeneity issue stemming from CEO selection based on firms’ growth trajectories and other characteristics into account by employing a propensity score matched (PSM) sample analysis. Finally, we show that our results are consistent even with the inclusion of a proxy for the level of education of managers. We conduct several robustness checks on the linearity of the CEO age effect, the role of CEO tenure, and the existence of country specificities in the relationship between CEO age and firm organic growth. The main results are robust to all these checks.

Our study contributes to modern literature on industrial dynamics, by offering some interesting insights on the role played by the age of managers in firm growth. While the growth effect of firm characteristics such as age, size, efficiency, innovative activities, and demand factors have been intensively examined (El Shoubaki et al., 2020; Esteve-Pérez et al., 2021; Foster et al., 2016; Heshmati, 2001), less evidence has been provided regarding the role played by the characteristics of the individuals who lead the firm.

This study also relates to the literature that inquires about the role of managerial characteristics in firms’ strategies (see Cronqvist et al., 2012; Faccio et al., 2016; Malmendier & Tate, 2005, 2008). From this perspective, our study is related to Li et al.’s (2017) work which provided evidence that career concerns explain why younger CEOs take investment decisions that boost firm growth. It is also related to Belenzon et al.’s (2019) work which examines the relationship between firm growth and CEO age in a sample of European companies from BvD’s Amadeus. However, two novel perspectives are contributed by this work. First, unlike Li et al. (2017) who rely on a sample of only large US firms (with an average plant size of about 300 employees), our analysis covers a set of diverse EU countries and is based on a sample that includes over 90% SMEs (with 87 employees per firm on average, and a median size of 26 employees). This is key to highlighting that agency problems are also at work in firms of smaller size. Second, while Belenzon et al. (2019) only focus on owner-managed firms to “[…] eliminate the potential agency problems […], which could affect managerial actions and hence firm growth […]” (p. 924), we focus precisely on this agency problem by comparing the relationship between CEO age and firm growth in firms with different degrees of ownership concentration. Indeed, our empirical design delivers enough variability in governance structures, which allows us to test for the role of concentrated ownership as a monitoring device that can align CEOs’ strategies with shareholders’ interests.

The rest of this paper is structured as follows. Section 2 draws the theoretical underpinnings of the relationship between CEO age and firm growth. Section 3 describes the data. Section 4 presents the econometric results, and the robustness checks and Section 5 concludes.

In this study, we rely on a unique source of data which results from merging Bureau Van Dijk (BvD)’s Amadeus with the EU-EFIGE/Bruegel-UniCredit dataset (EFIGE). Amadeus is a well-known and widely used source of economic and financial information on European companies. For the purposes of this study, we were able to gather data on the period from 2001 to 2014. EFIGE is the result of a survey administered within the project European Firms in a Global Economy: internal policies for external competitiveness, which was supported by the Directorate General Research of the European Commission through its Seventh Framework Programme¹⁰. In a first for Europe, EFIGE combines measures of firms’ international activities (e.g., exports, imports) with quantitative and qualitative information on about 150 items ranging from R&D and innovation, labor organization, financing, and organizational activities. Data consist of a representative sample (at the country level for the manufacturing industry) of almost 15,000 surveyed firms (above ten employees) in seven European economies (Germany, France, Italy, Spain, United Kingdom, Austria, and Hungary). Data were collected in 2010, and most questions refer to the year 2008. In some cases, respondents (i.e., individuals who were occupying leading positions in their firms) were asked about the activities of their firms during the years 2007–2009. Considering that the information on the age of CEOs is available for the year 2009, we use the information available in Amadeus, to calculate our dependent variable as the growth rate per unit of time (following Evans, 1987; Variyam & Kraybill, 1992; Moschella et al., 2019):

where SIZE_{i, t} is equal to the operating revenue (sales) of firm i at the end of year t.¹¹ This approach is better suited to analyze medium-run growth profiles of firms, which are more likely to result from CEOs’ strategies and less affected by noise and measurement errors, which can be severe in the case of yearly growth rates (Pieri, 2018). However, growth rates over longer periods, such as our 6-year period, may be more prone to the fallacy of not capturing a change (turnover) in CEO, which cannot be directly controlled in the data. To partially cope with this issue, we will replicate our analysis over shorter periods of time (see Section A.3.1 in the Online Appendix for a discussion on this issue). It is worth mentioning that the information on sales growth derives from unconsolidated accounts, which excludes growth through M&As, hence accurately reflecting organic growth. Since data on firm turnover is not available for all firms for the relevant years, our initial sample is effectively reduced to about 7200 firms.¹² About 93% of our sample firms have turnover values of less than €50 million and are thus SMEs.

The EFIGE survey provides information on the age of the CEO as a categorical variable with seven items (< 25 years old; 25–34; 35–44; 45–54; 55–64; 65–74; >= 75). The frequency distribution of the sample firms across these CEO age bins is shown in Fig. 1.

The histogram shows that the modal value of CEO age corresponds to the category 45–54 years. While it is impossible to have a precise figure for the median and mean age of the CEOs in our sample, an inspection of Fig. 1 suggests that it could be slightly above 50, which is in line with the evidence provided by other academic studies and scientific reports¹³. For example, Faccio et al. (2016) report a mean (median) age of 50.3 (51) for the CEOs of the firms included in their analysis, while in the sample of firms used by Li et al. (2017) and Belenzon et al. (2019) the mean age of CEOs is at 53.6 and 50.6, respectively.

To clearly separate young and old CEOs, and in line with previous studies on the role of CEOs in firms’ strategies, we group the seven categories into two macro-categories: CEOs younger than 45 versus the rest.¹⁴ While about 76% of our sample firms are managed by CEOs who are 45 or older, the share of CEOs younger than 45 is not negligible (24%).¹⁵

The EFIGE survey allows us to control for several firm and CEO characteristics that could confound the relationship between firm growth and CEO age, thus limiting the omitted variable bias issue. In particular, we have information on firm age (based on the year of establishment), which is typically associated with firm growth (Barba Navaretti et al., 2014). We also control for the propensity to innovate (Geroski, 1999) and the degree of internationalization (Serra et al., 2012), which are typically associated with risk-taking, hence could result in higher firm growth. Moreover, we can account for firms that have undergone any form of quality certification and widened their product range, as strategies for building a customer base (Foster et al., 2016). We also control for several proxies of economic and financial characteristics of firms, such as firm size (Hall, 1987; Lotti et al., 2009) profitability (Coad, 2007), debt to asset ratio and past sales growth rate, all calculated from BvD’s Amadeus over the period 2001–2008. As for CEOs, we can control for several characteristics associated with their risk-tolerance, including their gender, international experience, and over-confidence. Young CEOs may be more overconfident than their older counterparts (Citci & Inci, 2016): over-confident CEOs systematically overestimate their ability to create value and, in the case of abundant internal financing, tend to overinvest (Malmendier & Tate, 2005, 2008). This may affect firm growth, especially at the early stages of startups (Szerb & Vörös, 2019).¹⁶ A detailed description of the variables used in the empirical model is contained in Table 2.

Table 1 provides some summary statistics on the sales growth rates in the period 2009–2014.¹⁷

Bearing in mind that the 2009–2014 period embraces the years of the Great Recession, which impacted Europe heavily, it is not surprising that the sales growth rates per unit of time at both the 50th percentile and the mean of the distribution have been negative (approximately -0.008 and -0.031 log changes, respectively, as shown in Panel A). In line with our expectations, the median firm managed by a CEO younger than 45 has experienced a negative growth rate but lower (in absolute value) than the median firm managed by an older CEO. To account for possible differences across industries and countries, we also computed the growth rates per unit of time adjusted by industry (2-digit NACE rev.2), country, and year:¹⁸ these are shown in Panel B of Table 1. The growth rate of the group of firms managed by CEOs younger than 45 is around 0.7 points higher than the growth rate of the group of firms managed by CEOs who are 45 or older, at the 50th percentile of the growth rate distribution. This difference is statistically significant as shown in the bottom panel of Table 1 (as per the p value associated with the Wilcoxon; Mann-Whitney test). Moreover, the lower (in absolute value) skewness of the growth rate distribution for the firms managed by CEOs younger than 45 points to fewer episodes of heavy size contraction for this group of firms in the period 2009–2014. Figure 2 confirms these results.

The distribution of sales growth rates for the firms managed by younger CEOs (grey line) shows not only a higher median but also a higher number of episodes of positive and fast growth and fewer episodes of heavy and negative growth (contraction) than the distribution of growth rates of firms managed by CEOs who are 45 or older. It is relevant to underline that the distribution of growth rates is not normal, while better approximated by a Laplace (symmetric exponential) distribution (Bottazzi et al., 2001; Bottazzi & Secchi, 2006). The characteristic tent-shape of this distribution points to the existence of “fat tails”, i.e., the higher incidence of episodes of fast growth and heavy contraction with respect to what a Gaussian (normal) distribution would predict.¹⁹ The presence of fat tails justifies two choices made in the econometric analysis. First, the adoption of a least absolute deviations (LAD) estimator instead of the more common ordinary least squares (OLS) to get insights into the central tendency growth rate of firms managed by CEOs of different ages. Indeed, the first estimator is more robust in the case of a non-Gaussian distribution of the dependent variable (Wooldridge, 2010), like that of sales growth rates. Second, the attention paid to differences in growth between firms managed by CEOs of different ages, which may especially be in the tails of the distribution. To uncover them, we will use a generalization of the LAD estimator, i.e., quantile regressions.

Table 2 shows some descriptive statistics regarding firms’ and CEOs’ characteristics of the European manufacturing firms contained in the Amadeus-EFIGE database.

Firms managed by younger and older CEOs are different in several dimensions, and the last column of Table 2 confirms that these differences are usually statistically significant. The median firm in our sample, managed by a young CEO, is smaller, younger, more profitable, and more indebted²⁰ than its counterpart that is run by an older CEO and more likely to have introduced process innovations, while being less internationalized (in terms of the number of markets served via exports). Moreover, a higher share of females is observed among younger CEOs, who are also found to be more overconfident. Finally, firms managed by young CEOs grew more than their counterparts did in the period 2001–2008. With the two groups of firms being different in several dimensions, we will conduct a multivariate analysis, controlling for firms and CEOs’ characteristics which may well be correlated with both CEO age and firm organic growth.

We show that the age of CEOs is significantly associated with firm organic growth. In a large sample of mostly small and medium privately held European manufacturing firms, we find that, at the median of the conditional growth rates distribution, the growth in sales (and total assets) per unit of time over the period 2009–2014 was 0.66 (0.52) log points higher in firms managed by CEOs younger than 45. This difference is twice as large if observed at the 90th percentile, suggesting that firms with younger CEOs are more likely to be very fast-growing firms. Our results are robust to the inclusion of a large vector of firm and CEO characteristics, industry-country unobserved heterogeneity, and a wide set of robustness checks, including issues relating to the time horizon and the appointment of CEOs, the educational attainment of younger cohorts of managers, and endogeneity.

The relationship between CEO age and growth could be explained by the higher risk-taking propensity of young CEOs (Falk et al., 2018)—which has already been associated with firms’ risky strategies, such as R&D investments and M&As (Serfling, 2014; Yim, 2013)—or by other individual characteristics such as over-confidence, stamina, higher brain-process capacity, and a lesser rule-of-thumb approach to decision making (Besedeš et al., 2012). Indeed, our findings reveal that some CEO and firm characteristics that are typically associated with risk-taking and over-confidence are also correlated with firm organic growth. However, we argue that, conditional on these characteristics, the negative relation between CEO age and firm organic growth can be explained by the incentive for younger CEOs to boost firm sales and assets, possibly at the expense of profit margins. Indeed, young CEOs want to signal their value and increase firm size, so that an increase in their compensation can be justified. Clearly, this is unlikely to be in the interests of shareholders. Consistent with this interpretation, we find no significant statistical relationship between CEO age and the growth in operating profits. We also provide evidence that in firms characterized by more effective monitoring governance (more concentrated ownership), the relationship between CEO age and firm organic growth is much weaker. We contend that if our results were driven by CEOs’ individual characteristics, other than their greater incentive to achieve fast growth, there would be no reason to find weaker results in more closely monitored firms.

This study contributes to the modern literature on industrial dynamics, by offering insights on the role played by the age of the top executive in firm growth, exclusive of the growth effects ensured by the stochastic, structural, financial, and technological firm-level characteristics. Indeed, while the growth effect of firm characteristics such as age, size, efficiency, innovative activities, and those associated with demand factors has been deeply studied, less evidence has been provided on the role played by the characteristics of the individuals who lead the firm.

These results bear many implications both for policy and governance. First, in many European countries, the management, including board members, is old. In our sample, around 80% of the firms have CEOs older than 45. This could be a sign of insufficient turnover in management. This gerontocratic approach to firm management, combined with the evidence that firms run by younger CEOs have been growing more (especially in the complex times of the aftermath of the financial crisis of 2009), could explain why European firms are less dynamic than their US counterparts (Bravo-Biosca et al., 2016). Given that the small size of European firms is closely related to the slow path of productivity growth in Europe, faster turnover in management could help reduce allocative inefficiencies and improve gross domestic product (GDP) growth in the aggregate. Furthermore, as firm growth among incumbent firms is the most important source of job creation among OECD countries (Criscuolo et al., 2014), our results suggest that rejuvenating the management can have important aggregate employment and welfare effects.

Second, our evidence supports the view that governance with independent management from shareholders (and looser supervision by the latter) improves firm performance and should be fostered and implemented as a best practice. Of course, policy-makers do not have the power to rejuvenate management, yet a gradual spread of a corporate culture that increasingly emphasizes management turnover, and independence in management will certainly benefit firm performance and the growth of firms (and SMEs in particular) in the long run.

It is worth laying out a few caveats about our analysis. First, even if the main results of our work are robust to checks and provide the readers with a specific channel of causation, the identification of the causal effect of CEO age on firm growth could be sharpened if we had more precise information on the time of CEO appointment and turnover. Indeed, longitudinal information on CEOs may prove useful for future research on this topic. Second, even if the quantile regression model allows us to appreciate the heterogeneity of the relationship between CEO age and firm growth along the entire distribution of growth rates, the results provided only hold for the group of firms that “survive” (do not exit the market) during the entire period (2009–2014). The field of research about quantile regression models with sample selection is very promising (Arellano & Bonhomme, 2017), but their application is still not fully developed and it is certainly out of the scope of this study. Third, our study would have benefitted from more information on the psychological and cognitive traits of CEOs. This would have allowed us to better disentangle the role of age, from other traits that may be correlated with age and may impact how managers lead their firms.