1 Introduction

Over the last few years, there has been a continuous increase in the number of European firms having employee share plans. As shown in Figure 1, about 88% of large European companies had employee share plans in 2020 compared to about 57% in 2006. Non-executive employee ownership (EO) is believed to align the interests of employees with those of shareholders (Aoki 1984; Holmstrom and Milgrom 1991; Kong et al. 2024). Supporting this view, the preponderance of prior empirical studies report a positive relationship between EO and corporate outcomes (Bova et al. 2015; Chang et al. 2015; Kim and Patel 2017; Kang and Kim 2019; Adwan 2024; Braam et al. 2024). We add to this literature by examining whether EO can improve investment efficiency. Efficient investment decision-making by managers is vital for firms' value creation and, therefore, enhancing investors' wealth.

Fig. 1
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% of European companies having employee share plans 2006-2020. Source: Mathieu (2020)

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In the neo-classical economic framework, firms continue investing until the marginal return on investment equals the marginal cost of capital (Modigliani and Miller 1958; Hayashi 1982; Abel 1983). Prior literature has shown theoretically and empirically that firms might deviate from the optimal investment level and either overinvest or underinvest because of capital market frictions (e.g., Childs et al. 2005; Garcia Lara et al. 2016). Relatedly, the two main market frictions identified in the investment literature are information asymmetry and agency problems (Chen et al. 2017a; Adwan 2024).

We argue that EO helps improve firms' investment efficiency through two channels: reduced information asymmetry and improved monitoring of management. Non-executive employees have an informational advantage that comes from the first-hand knowledge they gain through interactions with managers, customers, suppliers, creditors, and other stakeholders (Babenko and Sen 2016). Employees tend to have their human capital and personal wealth closely linked to their employing firms. Therefore, EO would incentivise employees to report misconduct and serve as whistle-blowers, reducing the overall information asymmetry with outsiders (Bowen et al. 2010; Chen et al. 2020). In general, employees with shareholding have incentives to reveal value-destroying actions by managers. In addition, employees with shareholding are likely to be motivated to closely monitor management to protect their own interests (Alchian and Demsetz 1972).Footnote 1 This would deter managers from investing in projects with negative net present value or discarding profitable ones.

One may argue that non-executive employee ownership is too highly dispersed to significantly influence investment decisions at the firm level, and even if it does, the influence might be eroded by potential free-rider problems (Park and Song 1995; Pendleton and Robinson 2010). However, the results reported by prior related studies, such as Bova et al. (2015) and Chen et al. (2020), suggest that employee shareholding is sufficiently large to influence employee incentives and firm policies.

To test the impact of EO on investment efficiency, we use a sample of 11,286 firm-year observations relating to listed non-financial firms in 22 European countries over the period 2006–2017. We find a positive (negative) association between EO and the level of investment for firms that are more likely to underinvest (overinvest). Overall, our results indicate a positive association between EO and investment efficiency. Furthermore, we explore two plausible channels through which non-executive employee shareholding improves investment decisions. Specifically, the impact of EO on investment efficiency appears to be more pronounced for firms with lower analyst following and those with lower blockholding ownership. Our result suggests that reduced information asymmetry and improved monitoring of management can be the channels through which EO impacts investment at the firm level. We check the robustness of our findings using an alternative specification of investment efficiency, Heckman's (1979) model for self-selection bias, a two-stage instrumental model, and alternative proxies for information asymmetry and monitoring of management both at the firm and the country level.

This paper adds to a growing body of literature that investigates the impact of non-executive employee shareholding on corporate outcomes such as cost of debt (Chen et al. 2020), financial performance (Richter and Schrader 2017), financial reporting quality (Adwan et al. 2022), social and environmental performance (Braam et al. 2024; Kong et al. 2024), and voluntary disclosure by firms (Bova et al. 2015). To our best knowledge, this paper is the first to address the effect of EO on firm investment efficiency while focusing on EO's role in reducing information asymmetry and agency problems.

Our study also contributes to investment efficiency literature by investigating the influence of one of the under-researched ownership characteristics (i.e., non-executive employee ownership). Prior studies investigating how firm investment decisions are affected by ownership structure have focused primarily on government ownership (Chen et al. 2017a; Wu et al. 2021), institutional and controlling ownership (Richardson 2006; Jiang et al. 2011; Tahat et al. 2022), and director shareholdings (Gugler et al. 2008). The impact of these ownership forms on investment efficiency is likely to differ from that of employee shareholding. For example, government-controlled firms are sometimes associated with inefficiency and often pursue political goals that differ from profit maximisation (Megginson and Netter 2001; Boubakri et al. 2018). Institutional and controlling shareholders are more sophisticated investors and typically have more diverse portfolios and greater influence on managers compared to employees with ownership (Bartov et al. 2000; Jiambalvo et al. 2002). Similarly, the human capital and financial wealth of employees are typically less diversified than those of executives (Chen et al. 2020). Therefore, whether and how non-executive employee shareholding influences firm investment decisions is an empirical question we aim to address in this paper.

Finally, our paper provides empirical evidence using a sample of European firms corresponding to the call for more research on the influence of EO in international settings (Hope 2013; Hope and Vyas 2017). The majority of existing related research focuses on the US market (e.g., Bova et al. 2015; Chen et al. 2020). Utilising the multi-country settings in our paper, we find the impact of EO on investment efficiency to be more pronounced in countries with a weaker information environment and greater agency problems (see section 4.3.4 below). This finding reinforces the view that EO can effectively improve investment decisions, particularly in institutional settings characterised by weak corporate governance.

Documenting a relationship between employee ownership and firms' investment efficiency can have both macro-economic (considering the significance of investment as one of the factors driving economic growth) and firm-level implications (as the investment is a key determinant of firm performance). Understanding how EO can influence corporate investment decisions might be of interest to investors and analysts who seek to value equity and predict firms' future performance. Our results can also have implications for policymakers when devising policies to encourage employee ownership plans.

The remainder of the paper is structured as follows: Section 2 reviews related literature and develops the research hypothesis. Section 3 presents the research design and provides sample selection and descriptive statistics. Section 4 presents and discusses empirical results, followed by a concluding remark in Section 5.

2 Literature review and hypothesis development

2.1 Investment efficiency

In the neo-classical economic framework, firms should undertake (avoid) all projects with positive (negative) net present value (Modigliani and Miller 1958). To maximise their value, firms continue investing until the marginal return on investment is equal to the marginal cost of capital (Hayashi 1982; Abel 1983). However, the existing literature suggests that firms may deviate from the optimal level of investment and rather experience underinvestment (investment below the expected level) or overinvestment (investment above the expected level) (e.g., Garcia Lara et al. 2016; Chen et al. 2017a; Adwan 2024). Such findings are typically attributed to two main market frictions: agency problems and information asymmetry.

The principle-agent conflicts and the associated moral hazard problems prevent firms from investing at the optimal level. According to the agency view, managers who are self-interested might not always act in the interests of shareholders (Jensen and Meckling 1976). Instead, managers might overinvest or underinvest to pursue their own interests rather than maximising shareholders' wealth. For example, managers might make investment decisions for perquisite consumption, empire building, and management entrenchment (Aggarwal and Samwick 2006). Empirical studies have reported that managers may use corporate resources for aggressive growth and empire-building that reduce profitability and destroy firm value (e.g., Blanchard et al. 1994; Hope and Thomas 2008).

The agency conflict between managers and shareholders can also lead to underinvestment if, for instance, capital providers track the opportunistic behaviour of management (e.g., empire building) and constrain the supply of funds by increasing the cost of capital (Biddle et al. 2009; Anagnostopoulou and Avgoustaki 2023). Underinvestment could also emerge because of managers discarding projects with positive net present value because they are effort-averse and choose the “quiet life” (Bertrand and Mullainathan 2003). In addition, risk-averse managers who pursue their self-serving actions at the expense of shareholders may consider low-risk projects only, leading to underinvestment (Holmstrom 1979). Reichelstein (1997) shows that underinvestment might arise when the manager's discount rate and time preference differ from the owners.

The information asymmetry and the related adverse selection problems can also lead to distortions in investment decisions. Managers obtain superior information on the firm's true value and might be inclined to issue overpriced capital or raise capital when the firm is overpriced. The survey of CFOs, conducted by Graham and Harvey (2001), shows that managers consider over- and under-valuation as key factors when deciding to issue equity. The managers of overpriced firms who succeed in raising funds may use the excess capital to invest in unprofitable projects, leading to overinvestment (Alzahrani and Rao 2014; Chen et al. 2017b). In line with this view, Fu (2010) documents that firms following seasoned equity offerings are likely to invest more heavily compared to non-issuing firms. This excess in investment is negatively associated with post-issue performance (i.e., overinvestment). Polk, and Sapienza (2009) observe that firms with overpriced equity are likely to overinvest.

Capital providers might become aware or suspicious of such behaviour of managers and react by increasing the cost of external funds of the firm. The higher cost of capital can lead to underinvestment as projects that would otherwise be profitable become unfunded (e.g., Myers and Maljuf 1984; Fazzari et al. 1988). Chen et al. (2017b) argue that such an effect can be pervasive and influence all firms, including those with no overpriced equity. Managers, therefore, might respond by refraining from issuing under-valued equity and thus forgoing profitable projects (Chen et al. 2017a). Consistent with this, Myers and Majluf (1984) suggest that managers of under-priced firms are unlikely to issue new securities. Again, this will lead to underinvestment. Managers' lacklustre efforts in investment decision-making create a huge moral hazard or adverse selection problem.

Chen et al. (2017b) suggest that the negative effects of the adverse selection and moral hazard problems on investment efficiency can be alleviated by improving the firm's information environment and decreasing agency costs. We argue in this paper that non-executive employee ownership can help reduce information asymmetry and improve the monitoring of managers. Reducing information asymmetry and enhanced monitoring will lead to efficient investment decision-making at the firm level.

2.2 The impact of non-executive employee ownership

Non-executive employees are involved in the daily operation of the business. They can impact firms' decision-making through their effort, commitment, and workplace morale. Therefore, it is believed that they can filter firm's investment in projects and influence strategic planning (Aoki 1984; Faleye et al. 2006; Kruse et al. 2010; Chang et al. 2015). Berk et al. (2010) develop a model suggesting that in an economy with perfectly competitive capital and labour markets, employees face substantial human costs of bankruptcy. They also argue that employees can derive substantial incentives from job security to prevent firm bankruptcy. In comparison to owners and executives, employees' human capital is more sensitive to the firm's solvency, while their personal wealth is less diversified (Chen et al. 2020). In addition, Pendleton and Robinson (2018) show that employees with shareholding tend to hold a sizable concentration of their employer's shares, based on a survey of participants in employee ownership schemes in the UK. Employees with shareholding, whose human capital and personal wealth are closely linked to their employer firms, have strong incentives to exercise their implicit claim through ownership to keep the firm solvent and improve its efficiency.

Non-executive employee ownership can help reduce information asymmetry. Employees have access to private information stemming from their interaction with customers, suppliers, lenders, etc. Prior literature has provided evidence supporting the informational advantage of employees. Interestingly, in their experiment at Hewlett-Packard, Plott and Chen (2002) report that the employee prediction market provided more accurate product sales forecasts than the firm's internal processes. Similarly, in an experiment at Siemens, Ortner (1998) has found that employees accurately predicted that the firm would not be able to deliver on a software project on time. However, traditional planning tools predicted that the company would meet the deadline. More recently, Babenko and Sen (2016) suggest that employee share purchase plans can help predict future share returns as firms with more employee share purchases are found to perform better in the year after purchase. They infer from their results that lower-level employees have information about future firm performance.

Employees have informational advantages. Therefore, employees with shareholding are likely to be motivated to unearth the firm's misdeeds in accounting practice and disclosure. In contrast, managers may use discretion over the firm's financial information to hide their opportunistic behaviour (Healy and Wahlen 1999). Dyck et al. (2010) observe that rank-and-file employees are among the most likely actors to blow the whistle on corporate fraud. Moreover, financial rewards can significantly impact an employee's incentives to bring forward information about the misconduct of their firm (Bowen et al. 2010; Call et al. 2016). Driven by their less-diversified human capital and personal wealth, employees with shareholding are likely to have strong incentives to reveal value-destroying actions by managers (both underinvestment and overinvestment activities). That is, employee ownership can lead to improvement in investment efficiency through reducing information asymmetry between managers and outsiders.

In addition, non-executive employee participation in plans that lead to employee shareholding signals to capital providers that employees with the informational advantage are optimistic about the firms' future. Capital providers appreciate such ownership and are more willing to provide capital to firms with financial constraints. Therefore, firms with employee ownership are expected to reduce underinvestment. In a recent study, Chen et al. (2020) examine the link between non-executive employee ownership and the terms and pricing of corporate loans. They find that more employee ownership is associated with lower loan spreads and fewer restrictive loan covenants. In the same line, Jung and Choi (2021) document that firms with more employee ownership tend to enjoy higher share market liquidity. Overall, it is reasonable to argue that employee ownership leads to a reduction in information asymmetry,Footnote 2 and consequently to improve investment efficiency.

Non-executive employee ownership also mitigates the owner-manager agency problems. Given their involvement in day-to-day operations and knowledge of the firm, non-executive employees can collectively play an effective role in monitoring the management's activities. As explained above, unlike the firms' shareholders, employees' financial wealth and human capital are less diversified but closely tied to their firms. Therefore, employees with shareholding have strong incentives to monitor management to protect their interests. There are several mechanisms for employees to monitor managers and influence corporate decision-making. For example, share ownership plans usually provide explicit governance rights to employees, including voting on firm resolutions and attending annual general meetings (Pendleton and Robinson 2011; Braam et al. 2024). In some countries, such as France, employees with shareholding in publicly listed firms can elect one director whenever they hold at least 3% of outstanding shares (Ginglinger et al. 2011).Footnote 3 In addition, shareholding motivates employees to report concerns if they detect dubious practices or shrinking of responsibility, suggesting an improvement in the internal monitoring of management (Kruse et al. 2010; Bowen et al. 2010; Hochberg and Lindsey 2010; Kim and Ouimet 2014). Alchian and Demsetz (1972) concur with this view and discuss that employee ownership improves the monitoring of both managers and employees. Such improvement in internal monitoring deters managers from engaging in activities that are at odds with shareholder interests, such as inefficient investment decisions. Therefore, one can argue that employee ownership constitutes another monitoring and governance mechanism in addition to those used by external claimholders.

In this paper, we argue that shareholding encourages employees to monitor and influence managers' decisions. Employees with ownership are motivated to object or publicly voice concerns if managers invest in poor projects with negative net present value or avoid investing in profitable ones. That is, non-executive employee ownership can reduce both overinvestment and underinvestment for firms.

In light of the above discussions, we hypothesise that, ceteris paribus, shareholding motivates non-executive employees to improve the information environment and effectively monitor managers, resulting in increased firm investment efficiency. Specifically, we expect that employee ownership helps to reduce overinvestment and underinvestment at the firm level. We, therefore, form the following hypothesis:

H1. Non-executive employee ownership is positively associated with investment efficiency.

However, one may also argue for a negative association between non-executive employee ownership and investment efficiency. As firms grant share options to their employees, it might discourage non-executive employees from unearthing firms' fraud. Call et al. (2016) observe that firms that are involved in misreporting tend to grant more share options to their rank-and-file employees relative to a sample of control firms. Furthermore, misreporting firms that grant more employee options during the misreporting periods are more likely to avoid employee whistle-blowing allegations. In addition, there is a view that potential increased entrenchment and free-rider problems may hinder the effectiveness of employee shareholding in aligning employee-shareholder interests and improving firm outcomes (Park and Song 1995; Pendleton and Robinson 2010). Overall, it is still an empirical matter as to whether EO leads to improvement in investment efficiency.

3 Research design and sample

To test the impact of EO on firm investment efficiency, we run our main model following Biddle et al. (2009) and Chen et al. (2017b), and Gan (2019):

$${\text{Investment}}_{it+1}={\beta }_{0}+{\beta }_{1}{\text{EO}}_{it}+{\beta }_{2}{\text{EO}}_{it}\times {\text{Overinvest}}_{it}+{\beta }_{3} {\text{Overinvest}}_{it}+ { \beta }_{n} {\text{Control}}_{n,it}+{e}_{it}$$
(1)

where Investment is the total investments for firm i in year t + 1, estimated as the sum of capital expenditure, research and development (R&D) expenditure, and acquisition expenditure, minus cash receipts from the sale of property, plant, and equipment, multiplied by 100, and scaled by the lagged total assets. EO represents the percentage of shares held by non-executive employees for firm i in year t.

Following Biddle et al. (2009) and Chen et al. (2017b), we create a variable based on firm-specific characteristics that measures the likelihood to overinvest and underinvest. When firms have more cash in hand, they are likely to have higher agency costs, and thus, have a greater inclination to overinvest (Jensen 1986). On the other hand, firms with high leverage and/or a lack of cash are possibly financially constrained and, thus, are more likely to underinvest (Aivazian et al. 2005). Therefore, whether a firm is more likely to underinvest (or overinvest) is associated with its lower cash and higher leverage (or higher cash and lower leverage). In equation (1), the Overinvest measures the likelihood that the firm will potentially overinvest, estimated by first ranking the firms into deciles based on cash balance and leverage of each firm in each industry during a year (we multiply leverage by minus one before ranking so that both cash and leverage are increasing with the likelihood of overinvestment) and then computing the average of ranked values of the two variables. After that, we rescale this variable to range between zero and one. The rescaled variable gives the lowest (highest) ranks to the firms that are most likely to underinvest (overinvest). A firm with a high (or low) score for Overinvest suggests that it is prone to overinvest (or underinvest).

Gao and Yu (2020) review the different research designs adopted to investigate investment efficiency. They argue that using a design that includes estimating the likelihood of overinvestment or underinvestment is suitable to examine whether investment efficiency is enhanced by factors that can reduce information asymmetry between managers and outsiders. Employee ownership can play a non-trivial role in reducing information asymmetry and improving the monitoring of managers. This confirms the suitability of our methodological approach to test the hypothesis on the impact of employee ownership on firm-level investment efficiency.

In equation (1), the coefficient on \({\text{EO}}_{it}\), \({\beta }_{1}\), measures the effects of non-executive employee ownership on next year's Investment among the firms that are most prone to underinvest (when Overinvest = 0). The effects of EO on Investment among the firms that are more prone to overinvest is captured by the sum of the coefficients on \({\text{EO}}_{it}\) and the interaction term of \({\text{EO}}_{it}\times {\text{Overinvest}}_{it}\), which is \({\beta }_{1}\)+ \({\beta }_{2}\). We expect \({\beta }_{1}\) to be positive and the sum of \({\beta }_{1}\) and \({\beta }_{2}\) to be negative, indicating a reduction in underinvestment and overinvestment, respectively.

Following Biddle et al. (2009), Chen et al. (2017b), and Gan (2019), we control for company age and size, performance, volatility of cash flow, sales, and investment. We measure the Age of the firm as the logarithm of the difference between the date of the founding of the firm and the current fiscal year. The firm size is calculated as the logarithm of total assets (Size) to account for the potential size effect on investment. The ratio of the market value of equity to the book value of common shares (market-to-book) is used to control for firm-level performance. We also include the standard deviation of cash flow from operations (CFO), sales, and investment to reflect the volatility of these variables on investment, deflated by average total assets for the period t-5 to t-1, denoted as σ(CFO), σ(Sales), and σ(Investment), respectively. The remaining controls are the ratio of tangible assets to total assets (Tangibility), CFO to sales (CFOsale), dummies for loss-making (Loss) and dividend-paying companies (Dividend), and Altman's Z-score.Footnote 4 The Z-score captures the soundness of the financial health of a firm. A lower Z-score indicates a higher probability of corporate default. We also control for firm's ownership characteristics. Specifically, we add the following ownership related variables: Government_ownership (percentage of shares held by government agencies), Executive_ownership (percentage of shares held by executives), Controlling_ownership (a dummy variable that indicates if the firm has a shareholder with more than 50% of shares), and Institutional_ownership (percentage of shares held by institutional investors). Finally, we add a variable to capture the characteristics of the institutional environment in which a firm operates: Regulatory_quality. This variable is extracted from the Worldwide Governance Indicators (WGI) project and reflects the government's ability to formulate and implement sound regulations and policies.Footnote 5

We use the European Federation of Employee Share Ownership (EFES) database to obtain data on employee ownership of European firms.Footnote 6 The Refinitiv database is used to extract accounting, financial, and corporate governance data at the firm level. We exclude financial firms and firms with missing necessary data to run the estimation in equation (1) below. Our analysis sample comprises 11,286 firm-year observations relating to 985 non-financial firms in 22 countries in Europe between 2006 and 2017.

Table 1 reports the descriptive statistics of the main variables used in the paper.Footnote 7 It includes the mean, standard deviation, lower quartile (25%), median, and upper quartile (75%). In our sample, the average Investment is 6.83 with a standard deviation of 7.82, suggesting a wide investment differential among the European firms. The average EO is 1.22, with a standard deviation of 3.43, suggesting a substantial variation among firms regarding non-executive employee ownership. The correlation matrix shows no cause for concern related to the multicollinearity problem among independent variables used in the main model.

Table 1 Descriptive statistics
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4 Empirical results

In this section, we report the regression results. We first show whether the percentage of non-executive employee ownership is associated with firms' overinvestment and underinvestment. We then explore the mechanisms through which employee ownership influences investment. We have also conducted an array of robustness checks, including Heckman's (1979) approach and instrumental variable regressions, to explore the sensitivity of our results. In addition, we rerun our analyses after controlling for various corporate governance indicators.

4.1 The association between employee ownership and investment efficiency

Table 2 shows the regression results based on the fixed effects (FE) estimator specified in equation (1). We first ran the Hausman test to select the appropriate estimator between the fixed and random effects. We could reject the null hypothesis that the random effects model is efficient and consistent. Therefore, we have used a fixed effects model for all our estimations while clustering the standard errors at the firm and country levels. While we use firm fixed effects in column 1, we use year and firm fixed effects in column 2.Footnote 8 We also report the results using country and year fixed effects in column 3.

Table 2 Employee ownership and investment efficiency
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The coefficient on EO is positive and statistically significant at the 5% level in all three columns. In our model, the ranked variable, Overinvest, distinguishes between situations where over- or underinvestment is more likely – Overinvest is increasing (decreasing) in the likelihood of overinvestment (underinvestment). Therefore, the positive coefficient on EO (\({\beta }_{1}>0)\) indicates that for firms that are most likely to underinvest (when Overinvest = 0), the higher level of non-executive employee ownership is associated with a higher future investment. Taking column 2, in terms of the economic significance, increasing EO by one standard deviation (3.43) increases investment by approximately 0.52 (=0.151*3.43) among firms that are underinvesting. Given that the mean investment equals 6.83, this effect represents an increase of investment by 5.78%.Footnote 9 The result implies that a higher EO is associated with a higher future investment for the firms that are most likely to underinvest, in which case the overinvest is almost zero.

In column 2, the coefficient of the interaction term, EOxOverinvest, is −0.426 and statistically significant at the 5% level. The interaction result suggests that there is a decrease in the level of investments for firms that are most likely to overinvest. The sum of \({\beta }_{1}\) and \({\beta }_{2}\) in equation (1) captures the overall effect of EO on investment among the firms that are more prone to overinvest. The joint significance test rejects the null hypothesis (p-value = 0.041) that the sum of the coefficients, −0.275, is zero. In terms of economic significance, when EO increases by one standard deviation (3.43), investment decreases by approximately 0.94 among firms that are overinvesting. Given that the mean investment equals 6.83, this effect represents an increase of investment by 13.8%.Footnote 10 Overall, our results show that non-executive employee ownership is positively associated with firms' investment efficiency.

4.2 The mechanisms of the impact of employee ownership on investment efficiency

We then turn to explore the mechanisms through which employee ownership enhances investment efficiency. In this subsection, we discuss how employee ownership helps reduce information asymmetry and improve the monitoring of managers and thus enhance investment efficiency.

4.2.1 Reduced information asymmetry

To investigate whether information asymmetry can play a role in the relation between EO and investment efficiency, we follow the related literature (Fiechter and Novotny-Farkas 2017; Chen et al. 2020) and employ a commonly used proxy: the number of analysts following a firm each year (Analysts).

Existing literature shows that the reports of financial analysts help reveal information about various facets of a firm (Chen et al. 2017b). For instance, Dyck et al. (2010) find that financial analysts play a major role in detecting corporate fraud. The information contained in analyst earnings forecasts is associated with future share returns, measuring transaction costs, and informed trading in share markets (Kelly and Ljungqvist 2012). Therefore, when a large number of financial analysts follow a share, it helps reduce information asymmetry between the investors and managers. Both individual and institutional investors can make better investing decisions for those shares that are followed by many financial analysts. On the other hand, when a share is followed by a lower number of financial analysts, there might be a higher degree of information asymmetry between the investors and managers. Therefore, we assume that higher employee ownership is going to alleviate the information asymmetry problem more for those firms that are followed by a lower number of financial analysts. In that case, our hypothesis would be more pronounced for firms with lower number of financial analysts.

To identify the channel through which EO influences investment efficiency, we divide firms into two groups: high and low financial analysts based on the sample median of analysts following Fiechter and Novotny-Farkas (2017). Our results in columns 1 and 2 in Table 3 show that the impact of employee ownership is more salient when firms have fewer analysts following. In column 1, taking the High analyst following firms, we find that the EO and its interaction term, EOxOverinvest, have the expected signs (positive and negative, respectively), but both of them are insignificant. However, taking the Low analyst following firms in column 2, we find that the coefficient of EO is positive, but the coefficient on the interaction term, EOxOverinvest, is negative. Both of the coefficients are significant, at least at the 5% level. Our joint significance test (reported at the bottom of the table) rejects the null hypothesis that the sum of \({\beta }_{1}\) and \({\beta }_{2}\), −0.376, is zero at the 5% level. As stated earlier, when a company is followed by a lower number of analysts, there might be a higher degree of information asymmetry. In such a setting, EO seems to play a greater role in improving the information environment. Our results suggest that non-executive employee ownership leads to higher investment efficiency as shareholding encourages employees to reduce information asymmetry and influences managers to make judicious investment decisions.

Table 3 Employee ownership and investment efficiency: the information asymmetry and monitoring channels
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4.2.2 Improved monitoring of management

EO incentivises employees to play a significant role in monitoring the activities of managers. For example, employees may report concerns if they detect dubious practices or a shrinking of responsibility (Kruse et al. 2010; Bowen et al. 2010; Hochberg and Lindsey 2010; Kim and Ouimet 2014). To test this governance role of EO, we use the sample median of the percentage of shares held by blockholders to divide the firms into two groups: High and Low blockholdings. Following prior literature (e.g., Hadlock and Schwartz-Ziv 2019), blockholders are defined as shareholders who hold 5% or more of outstanding shares. Given that they have enough capital at stake, blockholders have the incentive to monitor management effectively and the ability to force managers to act in the best interest of shareholders (Shleifer and Vishny 1986; Alhaj-Ismail et al. 2019). We assume that the managers of a firm with high blockholdings tend to be monitored closely compared to the managers of a firm with low ownership by blockholders. Therefore, the relationship between EO and investment efficiency is going to be more pronounced for the sub-sample of firms with low blockholdings. As mentioned above, the firms with high ownership by blockholders already have enough monitoring mechanisms in place; therefore, the effect of employee ownership on investment is going to be ambiguous. The estimated coefficients on EO and EOxOverinvest in column 3 in Table 3 are not statistically significant for firms with high blockholdings. On the other hand, the results in column 4 show that the impact of EO (EOxOverinvest) is positive (negative) at least at the 5% significance level for the subsample of firms with low ownership by blockholders. Our joint significance test rejects the null hypothesis that the sum of \({\beta }_{1}\) and \({\beta }_{2}\), −0.320, is zero at the 1% level. Our findings show that EO is positively associated with high investment efficiency for firms with low blockholder ownership, suggesting the governance role of employee ownership.

4.3 Robustness checks

4.3.1 Alternative measure of investment efficiency

To check the robustness of our results, we run a model examining the impact of employee ownership on investment efficiency. A similar approach is used in prior studies such as Biddle et al. (2009), Chen et al. (2013), and Tahat et al. (2022). Specifically, we estimate the following regression:

$${\mathrm{InvEff}}_{it+1}=a_0+a_1{\text{EO}}_{it}+a_n{\text{Control}}_{n,it}+e_{it}$$
(2)

where all variables have been defined previously, except for the dependent variable. InvEff measures firm-level investment efficiency estimated based on the error term of the regression of future investment on sales growth (see Biddle et al. 2009). In so doing, we estimate the following regression:

$${\text{Investment}}_{it+1}={\theta }_{0}+{\theta }_{1}{\text{Sales}\_\text{Growth}}_{it}+{e}_{it}$$
(3)

where Investment is the total investments for firm i in year t + 1, and Sales_Growth is the percentage growth in sales for firm i from year t - 1 to year t (a proxy for investment opportunity). To control for the industry- and time-related effects, we estimate regression in equation (3) within the industry. Following Biddle et al. (2009) and Rajkovic (2020), we require at least 20 observations for each combination of two-digit SIC and year. The error term in equation (3) represents the deviation from the optimal level of investment (i.e., investment inefficiency). Therefore, we multiply the error term by minus one to measure investment efficiency, so high values reflect more efficient investments.

As shown in Table 4, the coefficient on EO is positive and statistically significant. This model's results confirm our main hypothesis that non-executive employee ownership is associated with improvement in firm investment efficiency.

Table 4 Employee ownership and investment efficiency (alternative measure)
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4.3.2 Addressing potential sample selection bias and endogeneity problems

Firms might voluntarily offer ownership plans to their employees. Therefore, our results could potentially be affected by self-selection bias. We address concerns about potential self-selection bias by following Heckman's two-stage procedure (Heckman 1979). In the first-stage, we run a probit model to measure the value of the inverse Mills ratio (Mills). Specifically, we use a dummy variable as the dependent variable that takes value one if a firm has employee ownership in a particular year and zero otherwise. The independent variables include the controls used in equation (1) above in addition to the identifying variable: the level of employee ownership at the industry level in the same country (EO_Ind). Using the industry average of the key explanatory variable as the identifying/instrumental variable is common in prior empirical studies (e.g., Wen et al. 2020; Alhaj-Ismail and Adwan 2024; Braam et al. 2024). We conjecture that the industry norms with regard to employee ownership are likely to affect employee shareholding at the firm level. Taking a similar conjecture, Kim and Petal (2020) document that employee shareholding varies across industries in Europe. The results of the probit model, as shown in column 1 in Table 5, indeed suggest that the likelihood of a firm having employee ownership is positively associated with ownership at the industry-level.

Table 5 Robustness tests: Heckman two-stage selection model
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In the second-stage, we add the inverse Mills ratio (Mills) as an independent variable in equation (1) which tests the main hypothesis in this research. As shown in column 2 in Table 5, the estimated coefficient on employee ownership, EO, is positive and statistically significant, whereas the coefficient on the interaction term, EOxOverinvest, is negative and statistically significant. Testing the joint significance strongly rejects the null hypothesis that the sum of the two coefficients is zero. That is, our key result on the positive relationship between EO and investment efficiency continues to hold even after controlling for self-selection bias using Heckman's (1979) two-stage procedure.

So far, we have shown that EO impacts investment efficiency positively. However, this relationship might be vitiated by the potential endogeneity. Therefore, our next concern is whether the firms that make more efficient investment decisions could undertake more employee shareholding, raising the possibility that EO and investment efficiency might be jointly determined. To address this possibility, we employ an instrumental variable (IV) regression approach using two-stage least squares (2SLS) estimation. The first-stage regressions show how the IV and control variables explain EO and its interaction term, EOxOverinvest. In the second-stage, we use predicted EO and EOxOverinvest as regressors and apply a generalised method of moments (GMM) estimation to examine the impact of EO and EOxOverinvest on Investment. Prior literature using the potential instruments for EO is relatively scant. Therefore, finding suitable instruments can be challenging. A valid instrument should have an effect on the endogenous regressor but not on the dependent variable. As discussed above, in addressing the sample selection bias, we consider the industry average of EO as one of the suitable instruments. Since both EO and EOxOverinvest need to be instrumented, we explore existing literature to find a second instrument.

Prior literature shows a strong correlation between wage/compensation and employee ownership. Using 1995 employment and wage data from the Washington State Employment Security Department, and by matching ESOP (Employee Stock Ownership Plan) firms with non-ESOP ones, Kardas et al. (1998) find that the median hourly wage in the ESOP firms was 5% to 12% higher than the non-ESOP ones. According to Blasi et al. (1996), firms with broad-based employee ownership plans have 8% higher average compensation levels than comparable companies, and remuneration grows with employee stock ownership percentage. Other studies also find a positive correlation between employee ownership plans and higher wages (see Renaud et al. 2004). Therefore, we collect information on the minimum wage (NMW) from the OECD/AIAS ICTWSS database.Footnote 11 Specifically, we use a dummy variable set to 1 if the firm is domiciled in a country in which a statutory national minimum wage (cross-sectoral or inter-occupational) exists.

The NMW would be an appropriate second instrument for our IV regression, which would have a positive association with EO but no effect on firm-level investment efficiency. There are a few reasons for expecting the national minimum wage to be associated with employee ownership. First, firms frequently seek methods to augment productivity and bolster employee commitment in response to heightened labour costs triggered by a minimum wage increase. Employee share ownership plans are proposed as one possible strategy because they are associated with increased productivity and a stronger sense of employee commitment and engagement (Kruse et al. 2010). Second, when the labour market is tight, employers may compete to recruit and retain talent in nations with high minimum wages. Therefore, firms may offer a competitive compensation and employee ownership package to attract and retain workers (Aldatmaz et al. 2018). Finally, when the legal minimum wage increases, employees have greater bargaining power with their employers. This may result in increased demands for employee ownership, as employees desire a larger share of the ownership and profits of the businesses they work hard for. Consistent with the argument, Park et al. (2022) find evidence that the higher bargaining power of labour unions is linked to a higher level of employee ownership.

The first-stage result is reported in columns 1 and 2 of Table 6. We test the validity of our instrumental variables using the under-identification Kleibergen and Paap LM test and the Hansen-J over-identification test. The results of these tests show that the instruments used are valid. We include the predicted values of EO and EOxOverinvest obtained from the first-stage in the second-stage regression. The first-stage results reported in column 1 show that both the EO_Ind and NMW are significantly associated with EO. The estimated coefficients on EO_Ind and NMW are positive and significant at the 1% level, suggesting that the industry average EO and the statutory national minimum wage increase employee ownership at the firm level. The second-stage results are presented in column 3 in Table 6. We find that the sign and significance levels of the 2SLS estimates are consistent with the main results in Table 2. In other words, the empirical results of the instrumental variable regressions are robust, and the coefficients of EO, Overinvest, and EOxOverinvest remain unchanged. Our joint significance test rejects the null hypothesis that the sum of \({\beta }_{1}\) and \({\beta }_{2}\), −1.60, is zero at the 1% level. The IV results confirm our earlier findings.

Table 6 Robustness tests: Instrumental variable regressions
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4.3.3 Alternative proxies for information asymmetry and monitoring of management

To further investigate the robustness of our findings on the channels through which employee ownership affects investment efficiency, we partition the sample using alternative proxies for information asymmetry and monitoring of management both at the firm level.

We use three alternative measures for firm-level information asymmetry. First, we divide our sample into opaque and non-opaque firms based on a proxy for earnings management. We use the absolute value of residuals from the Jones (1991) model as modified by Dechow et al. (1995) as a measure of earnings management. The model is run for each combination of two-digit SIC-year with at least six observations (see Baik et al. 2011; Garcia Lara et al. 2017). Higher absolute residuals represent more discretionary accruals and, thus, a higher level of earnings management. The subgroup of non-opaque (opaque) firms are those with below (equal to or above) the sample median of discretionary accruals. As shown in columns 1 and 2 in Table 7, our results show that the impact of employee ownership is more salient for opaque firms (i.e., firms with higher information asymmetry). Second, we partition our sample into large and small firms. Prior studies suggest that large firms are likely to have less information asymmetry compared to small firms (Lehavy et al. 2011). Large firms are those who have total assets above the sample median, whereas small firms have total assets equal to or below the sample median. In line with our expectation, columns 3 and 4 in Table 7 show that the association between EO and investment efficiency is significant only for the subsample of small firms. Third, the sample firms are divided into no-R&D versus R&D firms. Information asymmetry increases with more investment in R&D (Aboody and Lev 2000). As shown in columns 5 and 6, the impact of employee ownership on investment efficiency is more pronounced for the subsample of firms that report R&D in their financial statements (i.e., R&D firms).

Table 7 Employee ownership and investment efficiency: alternative measures for information asymmetry at the firm level
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In terms of monitoring of management, we use three alternative indicators at the firm level. First, we divide our sample based on the percentage of independent directors on the firm board. Specifically, firms are divided into high and low board independence. The subsample of high (low) board independence includes firms with above (equal to or below) the sample median of the percentage of independent directors. More independent directors are likely to improve the monitoring function of the board and the overall governance quality (Hu et al. 2017). In line with our results above, columns 1 and 2 of Table 8 show that the statistically significant impact of EO on investment efficiency is observed only for the subsample of firms with a low percentage of independent directors (i.e., firms with greater agency problems). Second, following Alhaj-Ismail and Adwan (2024), the sample is partitioned based on the sample median of corporate governance score, provided by Refinitiv, into high and low corporate governance scores. Again, our results in columns 3 and 4 indicate that the association between EO and investment efficiency is significant only for firms with low governance scores. Third, we partition our sample based on the percentage of female executive members. High (low) diversity is the subsample of firms with the percentage of female executives above (equal to or below) the sample median. A number of prior studies document that increased female representation in corporate boards is associated with improved monitoring (e.g., Adams and Ferreira 2009; Post and Byron 2015). Columns 5 and 6 show that the effect of EO on investment efficiency is more evident for the subsample of firms with a low percentage of female executives (i.e., firms that are likely to have weaker monitoring of management).

Table 8 Employee ownership and investment efficiency: alternative measures for monitoring of management at the firm level
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Overall, our results using various firm-level indicators confirm that reducing information asymmetry and improving monitoring of management are potential channels through which EO leads to improvement in investment efficiency.

4.3.4 Country-level analysis

Information asymmetry and agency problems can be driven by the institutional environment in the country in which a firm operates. We, therefore, perform further analysis to examine whether our results hold using country-level variables.

We investigate first whether the impact of EO on investment efficiency depends on the development of the stock market in a country, a proxy for the information environment. The information environment is likely to be weaker in less developed economies (Fiechter and Novotny-Farkas 2017; Song et al. 2021). Following Boubakri et al. (2020), we measure market development by the number of listed firms in a country.Footnote 12 A country is considered to have a high (low) number of listed firms and thus a strong (weak) information environment if the total number of listed firms in that country is above (equal to or below) the sample median. Columns 1 and 2 of Table 9 indicate that the impact of employee shareholding is significant only for firms domiciled in countries with a low number of listed firms (i.e., weaker information environment).

Table 9 Employee ownership and investment efficiency: alternative measures for information asymmetry and monitoring of management at the country level
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In addition, we use two other country-level variables that are believed to influence the extent of agency problems and monitoring of management: the rule of law and regulatory quality (e.g., Bao and Lewellyn 2017; Alvarez-Botas and Gonzalez 2021). We divide the sample based on the medians of these two variables into: high rule of law versus low rule of law, and high regulatory quality versus low regulatory quality. The reported results in Table 9 indicate that the association between EO and investment efficiency is more apparent for the subsamples of firms in countries with low rule of law and low regulatory quality.

Overall, our results suggest that employee ownership plays a greater role in improving investment decisions in countries with weaker information environments (less developed markets) as well as in countries with weaker legal systems where agency and monitoring problems are more manifested. Again, this gives further support to our inference that the reduction in information asymmetry and enhancing monitoring of management are two channels through which EO can improve corporate investment decisions.

4.3.5 Further robustness tests by adding more control variables

Although our main model in equation (1) includes an array of control variables typically used in prior related studies (e.g., Biddle et al. 2009; Chen et al. 2017b), there are other governance and managerial characteristics that could affect the efficiency of corporate investment decisions. To ensure our results are not affected by the omission of such variables, we rerun our analyses for the impact of employee ownership and the channels of impact after adding the following controls: the percentage of independent directors (Independent), the percentage of female executives (Diversity), a dummy variable that equals to one if the CEO simultaneously chair the board (CEO_duality), the number of directors on the board (Board_size), and Refinitiv's governance pillar score (Governance_score).Footnote 13 As shown in Tables 10 and 11, our results largely hold across these tests despite the significant drop in the number of observations due to missing data on corporate governance variables in Refinitiv's database. Overall, the results suggest a significant positive association between non-executive employee ownership and investment efficiency; they also suggest that information asymmetry and management monitoring could be two possible channels.

Table 10 Robustness I: Adding controls for corporate governance
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Table 11 Robustness II: Adding controls for corporate governance
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4.3.6 Other robustness checks

As a further robustness check, we test the effect of EO on investment efficiency at different levels of EO. Firstly, we replace EO with a dummy variable that equals one if a firm has EO and zero otherwise. Secondly, we consider the impact of EO for firms that have less than the sample median of EO versus those with no EO. Thirdly, we examine the impact of EO for firms that have above the sample median of EO versus those with no EO. Finally, we consider the impact of EO for firms that have above the third quartile of EO versus those with no EO. In all these analyses, our results (untabulated) continue to show that employee ownership – at different levels – positively impacts investment efficiency.

5 Conclusion

Drawing on a large sample of European firms, we provide new evidence on the effect of non-executive employee ownership on the efficiency of investment decisions. We find a positive (negative) association between EO and investment for firms that are more likely to underinvest (overinvest). We also observe that the strength of this association is more prominent among firms characterised by higher levels of information asymmetry and greater owner-manager agency problems. Our results continue to hold after using different specifications, Heckman's (1979) self-selection model, two-stage instrumental variable analysis, different firm-level measures for information asymmetry and monitoring of management, various measures for information environment and agency problems at the country level, and more control variables related to corporate governance.

Our robust findings support the view that non-executive employee ownership can enhance firms' investment efficiency through two channels: reduced information asymmetry and improved monitoring of managers. Overall, we provide evidence that non-executive employee shareholding helps align the interests of employees with those of shareholders.