2.1.1 Overinvestment

Jensen and Meckling (1976) and Jensen (1986) argue that private benefits of managers are proportional to the firm size. Increasing the size of the firm enhances managers’ reputations in the capital market and increases their discretion over corporate resources. Thus, managers have an incentive to overinvest. This behavior is more likely to occur in firms with small or no ownership of managers because they can enjoy the private benefits while transferring the associated costs and risks to shareholders. Shin and Park (1999) point out that controlling shareholders in Korean ‘chaebols’ have significant control power over all affiliates with only small ownership, and such excessive control can lead to overinvestment. Joh (2003) argues that the disparity between control rights and cash flow rights in Korean firms is one of the causes of the Asian financial crisis, and shows that the overinvestment in other affiliates of the same business group is the main route that weakened firms’ profitability. Jiang et al. (2011) analyze the relationship between the ownership-control disparity and investment-q sensitivity (the sensitivity of investment expenditure to growth opportunities) in East Asian and European countries. Based on the negative (-) relationship, they suggest that overinvestment could occur when the owner-managers exercise excessive control rights with small cash flow rights. Considering the above arguments and findings, if controlling shareholders possess low ownership, then maximizing their utility through pursuing private benefits becomes optimal, and thus overinvestment will increase. On the other hand, if they hold high ownership, then overinvestment is less likely to occur, as controlling shareholders must bear the associated investment costs and potential losses (risks).

Hypothesis 1-1: Controlling shareholders’ ownership will have a negative (-) influence on overinvestment.

2.1.2 Underinvestment

The agency problem based on the ownership structure could also be associated with underinvestment caused by excessive risk aversion (Fama and Jensen, 1983).^2), Holmstrom (1979) argues that the higher the sensitivity between managers’ monetary compensation and the firm’s performance, the higher the managers’ risk aversion tendency because they have to bear the potential investment losses on his own. Smith and Stulz (1985) suggest that managers with high ownership are more likely to use derivatives or diversify corporate investments for risk aversion. Stulz (1988) argues that managerial ownership beyond a certain threshold can strengthen entrenchment behavior, and thus lead to a decline in firm value. Faccio et al. (2011) suggest that firms with shareholders who find it difficult to diversify their investment portfolios are more likely to be risk-averse. Underinvestment^3), due to risk aversion can limit the opportunities for creating future profits, thereby undermining minority shareholders’ wealth (Kim and Lu, 2011). Based on these arguments and findings, we expect that the probability of underinvestment increases as controlling shareholders’ ownership increases.

Hypothesis 1-2: Controlling shareholders’ ownership will have a positive (+) influence on underinvestment.

2.2.1 Private Benefits

Many theoretical and empirical studies focus on the disciplinary effect of product market competition as an external control mechanism. Previous studies find that competition can discipline the agency problem. Hart (1983) argues that managers under competitive pressure will try to reduce costs to reach the profit target to maintain their positions rather than manage the firm negligently, and thus improving management efficiency. Schmidt (1997) argues that competition has the effect of maximizing managerial effort by expanding the distress risks (threat-of-liquidation effect). Managers who care about their reputations, monetary compensation, and positions will make the optimal managerial decisions to minimize the distress risks. Holmstrom (1982) finds that relative performance evaluation can reveal information on managerial behaviors that are difficult to infer from the firm’s absolute performance. This evaluation can be effectively made in competitive markets where it is easy to compare firms (Nalebuff and Stiglitz, 1983). That is, evaluating performance through comparison with many competitors has the effect of eliminating some common factors, which makes it easier to evaluate managers’ true abilities effectively. Guadalupe and Pérez-González (2010) find empirically that the magnitude of managers’ private benefits measured by the control premium is low in competitive markets.

In light of this prior research, we expect the relationship between controlling shareholders’ ownership and investment inefficiency to diminish or disappear if their incentives to pursue private benefits are controlled in advance due to the disciplinary effect of product market competition. Excessive investment spending (i.e., overinvestment) in competitive markets can result in economic loss or failure to secure competitive advantage, increasing the possibility of bankruptcy. In the case of bankruptcy, the controlling shareholder must bear not only the explicit loss of diminishing discretion but also the implicit loss of decline in reputation. Meanwhile, the internal information such as capital availability and growth opportunities of firms in competitive markets can be easily recognized by investors by comparing it with many competitors. In this circumstance, if the controlling shareholder excessively avoids risk (i.e., underinvestment), then disciplinary pressure, such as a demand for greater dividends and the threat of management change by the various stakeholders, will increase. In sum, controlling shareholders’ pursuit of private benefits in competitive product markets will incur too many potential costs to themselves. Therefore, they will recognize to improve the management efficiency to secure competitive advantage as the optimal decision. As a result of this decision, controlling shareholders with small or no ownership can seek to enhance their reputations and maintain their positions, and those with large ownership can maximize their utility by improving the firm value. On the other hand, in non-competitive markets in which the disciplinary effect is relatively absent, controlling shareholders will perceive pursuing private benefits as a rational choice.

Hypothesis 2-1: The relationship between the controlling shareholders’ ownership and investment inefficiency will decrease or disappear in competitive product markets and will be observed mainly in non-competitive product markets.

2.2.2 Monetary Compensation

Unlike the above perspective, competitive pressure can be a factor that hinders efficient corporate decision-making. Some studies suggest that low profitability in competitive markets can weaken managers’ monetary incentives. Schmidt (1997) suggests that in competitive markets where the marginal profits converge to the marginal costs, it is difficult for managers to extend their monetary compensation by improving firm value or profitability, even if they make the best effort. Raith (2003) argues that if firms are free to enter the market, incoming competitors with low prices in competitive markets could reduce the marginal benefits of cost reduction through efficient management. Hermalin (1992) and Scharfstein (1988) argue that in competitive markets with low marginal profits, managers can establish more aggressive investment portfolios to expand their monetary compensation.

In competitive markets, controlling shareholders will expect low monetary compensation, and will instead pursue private benefits by overinvestment to maximize their utility. Especially, controlling shareholders with small or no ownership, who have little to lose even if the investment ends in failure, will choose to overinvest as a kind of betting tool to generate high returns. Meanwhile, it is also possible that underinvestment incentives will be strengthened in competitive markets. The value of the costs saved through best efforts will not be so great due to the high competitive pressure. Therefore, from the perspective of controlling shareholders with large ownership, avoiding risky investments and minimizing the investment costs could be the best decision to prevent a decline in their monetary compensation. Moreover, low profitability and high bankruptcy risk in competitive markets will further strengthen the incentive to underinvest to minimize the potential investment risks. In sum, competitive pressures will weaken the incentive for controlling shareholders to expand monetary compensation, so increasing private benefits by over- or underinvestment will be optimal to maximize their utility. On the other hand, in non-competitive markets, controlling shareholders have an incentive to manage the firm efficiently, as the monetary compensation increases in proportion to the effort.

Hypothesis 2-2: The relationship between controlling shareholders’ ownership and investment inefficiency will be observed mainly in competitive product markets and decrease or disappear in non-competitive product markets.

3.2.1 Investment Inefficiency

We estimate investment inefficiency based on Richardson’s (2006) measure. To measure investment inefficiency, McNichols and Stubben (2008) use Tobin’s Q and cash flow, and Biddle et al. (2009) use the sales growth rate. However, estimating these measures requires a high number of observations (e.g., more than 20) in a specific industry. This requirement naturally excludes monopoly or oligopoly industries. On the other hand, Richardson (2006) does not limit the number of firms to measure investment inefficiency, which enables us to focus on the difference in product market competition.

Richardson (2006) measures investment inefficiency based on equation (1). Investments that are not related to firm characteristics such as growth opportunities, capital structure, and cash holdings are regarded as inefficient investments (over- or underinvestment). We measure Investment as the sum of capital expenditure and R&D expense divided by total assets. We estimate V/P, a proxy for growth opportunity, firm value (V) divided by the market value of equity (P).^4), Here, V=(1-αr)BV+α(1+r)X-αrd, α=(ω/(1+r-ω)), r=0.12, and ω=0.62. ω is based on Ohlson’s (1995) abnormal earnings persistence parameter. BV is the book value of common shares, d is dividends, and X is operating income after depreciation. Leverage is total debt divided by total assets and Cash is cash and cash equivalents to total assets. Age is the natural log of the age of the firm, Size is the natural log of total assets, and Stock return is the stock returns for one year. We define the residual of equation (1) as investment inefficiency (Residual).⁵⁾

As we explained in the hypotheses development, investment inefficiency based on controlling shareholders’ ownership could be related to both over- and underinvestment. Thus, to rigorously distinguish between these two issues, we use additional variables. As a measure of overinvestment, we set a variable that takes the absolute value if the residual is greater than zero, and a value of zero if the residual is less than zero (Residual Over). As a measure of underinvestment, we set a variable that takes the absolute value if the residual is less than zero, and a value of zero if the residual is greater than zero (Residual Under).

Using the estimated investment inefficiency has a limitation in that we cannot intuitively grasp how much investment expenditure the firm actually spends. Therefore, for a clearer and more direct measure of investment inefficiency, we use industry-adjusted investment expenditure (Excess investment). We calculate this variable as the firm’s investment expenditure minus the average industry investment expenditure, classified based on the 3-digit KSIC.

3.2.2 Ownership⁶⁾

We focus on the ownership structure of controlling shareholders, who have actual control rights in the management activities. To obtain the ownership structure of the controlling shareholders, we must select the shareholders who have actual control. The controlling shareholders of Korean firms secure control rights using indirect ownership through affiliates. Thus, the largest shareholder of a firm is frequently an affiliate (corporation) rather than a controlling shareholder. In this case, the largest shareholder’s ownership does not reflect the monetary incentive of the controlling shareholders (individuals). On the other hand, Korean firms are usually controlled by the controlling family and should be regarded as the same economic entity. Considering these characteristics, we first make comprehensive use of the annual reports, reports of changes in the firm’s ownership structure, and newspaper articles to identify the controlling shareholders and their relatives. Next, we manually collect the ownership of the controlling family from the annual reports. We use the sum of the ownership of the controlling family (Controlling ownership) in the empirical analysis.

Controlling shareholders can expand their control rights through indirect ownership through affiliates, pyramid ownership structures, and cross-shareholdings, in addition to direct ownership (cash flow rights). That is, we can define the controlling shareholders’ control rights as the sum of direct and indirect ownership.^7), If controlling shareholders exercise excessive control rights relative to their direct ownership, then they could have more incentive to pursue private benefits (Grossman and Hart, 1988). This is because the burden of the decline in the value of shares due to the pursuit of private benefits is relatively small. Therefore, we use the disparity between control rights and cash flow rights as the alternative proxy for the ownership structure of controlling shareholders. Control rights are the sum of direct ownership by the controlling family and the affiliates’ ownership. The cash flow rights are the direct ownership by the controlling family (Disparity).

3.2.3 Product Market Competition

We measure product market competition using the HHI, which is a common measure in the field of industrial organization. HHI is intuitive and easy to understand and is relatively simple to estimate, and therefore suitable for our analysis of many industries. Because of these advantages, many recent corporate governance studies focusing on the disciplinary effect of competition use this index (Giroud and Mueller, 2011; Valta, 2012). To estimate the HHI, we first categorize the sample firms by industry using the KSIC, which is published by Statistics Korea, a central government organization for statistics. Existing studies estimate the competition level based on the 3-digit industry code, considering the comparability between industries (Hou and Robinson, 2006). We use the same criteria. For the robustness check, we additionally use the 2- and 4-digit^8), KSICs to measure the HHI.^9), Ali et al. (2009) point out that using only listed firms to measure the level of competition may not reflect reality correctly. This problem could be more serious in Korea, as its capital market is less developed. Therefore, we measure the HHI using not only listed firms but also unlisted firms that provide reliable financial data (firms that are subject to external audits).¹⁰⁾ We calculate the HHI as the sum of the squares of the market share based on the sales of the firms in the industry (HHI). HHI has a value between 0 and 1. A higher HHI means a concentrated market structure and low competition, while a low HHI implies that there are many firms with small market shares competing in an industry, indicating high competition.

To minimize measurement error, we use additional measures such as the concentration ratio (CR4), entry cost, and price-cost margin. CR4 is the sum of the market share of the top four firms in an industry (CR4). If there is a large deviation in market share among firms in the industry, then competition among firms with a high market share will be intense, while firms with a low market share are more likely not to face competition. We use CR4 to reflect this property (Hou and Robinson, 2006; Giroud and Mueller, 2010). A higher CR4 indicates lower competition.

Competitive pressures can be weighted by not only existing firms in the industry but also by potential entrants. HHI and CR4 have a limitation in that they measure the level of product market competition among only existing firms in the current product market. Li (2010) measures the level of potential competitive threats based on the cost of entry to the industry calculated by taking the natural log of the weighted average tangible assets of firms in the same industry (Entry cost). The weighted average is based on market share. A high level of this indicator means a relatively high entry barrier so that the magnitude of the potential competitive threat is small. The price-cost margin reflects product substitutability based on the industry’s profitability (Bena and Xu, 2017). It is the sum of sales divided by the sum of the cost of sales and selling and administrative expenses (SG&A) of firms in an industry (Price-cost margin) (Karuna, 2007). The higher the price-cost margin is, the higher the monopoly profits compared to the input resources are, meaning that it is a relatively non-competitive market.

3.2.4 Other Variables

To mitigate the potential omitted variable bias, we include various control variables that could influence investment inefficiency in the empirical model (Myers, 1977; Jensen, 1986; Biddle and Hilary, 2006; Richardson, 2006). The size of the firm affects external financing capacity, as it is related to information opacity and collateral capabilities. The more stable the funding capacity, the greater the ability to cover the costs to realize the investment opportunity. Therefore, we add the natural logarithm to the firm’s total assets as a measure of firm size (Size). A high leverage ratio can cause underinvestment problems by increasing the bankruptcy risks (Myers, 1977). In terms of agency theory, a high debt ratio has the effect of preventing the overinvestment problem, as it reduces the free cash flow that managers can use (Jensen, 1986). Taking these effects into account, we include the debt-to-equity ratio in the model (Leverage).

It is possible that the firm’s internal funding capacity reduces due to the low profitability, thereby the ability to spend the expenses associated with the investment may decrease. To control these effects, we include net income to total assets (ROA). The firm chooses the optimal level of investment expenditure to realize growth opportunities and to ensure future sustainability. Even if managers have excessive investment spending from the agency theory perspective, it would be difficult to regard it as overinvestment if the goal is to realize growth opportunities. Thus, to control for growth opportunity, we include the market to book ratio, which we calculate as the market value of equity (the number of common shares*the stock price at the end of the year) divided by its book value (Market-to-book) (Biddle and Hilary, 2006).

Free cash flow represents the internal fund available to the manager, and classical agency theory points out that as it rises, the agency problem can increase (Jensen, 1986; Richardson, 2006). We define free cash flow as operating cash flow minus interest costs, dividends, and corporate taxes, divided by total assets (Free cash flow). To obtain a clearer result for the relationship between the ownership structure of controlling shareholders and their investment decisions, we control the controlling shareholders’ incentive to pursue private benefits unrelated to the ownership structure. Almeida et al. (2011) find that controlling shareholders may adjust discretionary accruals to avoid losses due to declining operating performance, which we can perceive as a typical agency problem. We calculate the discretionary accruals variable as the absolute value of the difference between net income divided by total assets and the operating cash flows divided by total assets (Accruals).

Firms diversify their investment expenditures according to their stage in the life cycle, so we include the natural logarithm of the age of the firm (Age). Dividend payments could be a signal to the stock market of stable profitability, so it may be associated with an increase in future investment expenditures. To control these effects, we add the ratio of cash dividends to equity (Dividend). Corporate growth opportunities can be linked to both future growth potential and current growth levels. As we mentioned earlier, growth opportunities are the most important indicators for assessing the adequacy of corporate investment spending. Therefore, we use the average sales growth for the past three years as a proxy for the current growth level (Sales growth). Lastly, liquid assets represent the size of the accumulated internal resources available to managers in the short term. Firms with larger liquid assets will have greater room to cover the investment costs. We control for this effect including liquid assets divided by total assets (Liquidity).

To reduce the endogeneity problem based on the causal relationship between the ownership of controlling shareholders and investment expenditures, we additionally use a 2-stage least squares (2SLS) model. As an instrument variable, we use the standard deviation of monthly stock returns on the ownership of controlling shareholders for the past five years (Stock return volatility). Demsetz and Lehn (1985) argue that the ownership structure is endogenously determined. They suggest that if shareholders or outside investors are risk-averse, then the risk inherent in the firm would have a negative (-) relationship with the ownership structure. Kang et al. (2006) find such a relationship empirically in Korean firms. The controlling shareholders tend to avoid holding ownership in higher risky companies (higher stock return volatility). However, the stock return volatility is a result of the investment and cannot precede the investment. In particular, as stock return volatility is measured based on stock returns over the past five years, this precedent relationship is even more pronounced. Based on this logic, this study employs the volatility of stock returns as an instrumental variable. We discuss the adequacy of the instrument variable with the results of the empirical analysis.

We later examine the possibility that the firm expands investment expenditures to defend against potential predation risks. We expect the potential predation risks to have a close relationship with the size of market dominance. Therefore, as a proxy of market dominance, we set a dummy variable equal to one if the firm has the largest market share¹¹⁾ in the industry and zero otherwise (Dominant firms).

4.2.1 Regression results

We examine the effect of the controlling shareholders’ ownership and product market competition on investment inefficiency using ordinary least squares (OLS) regressions. Considering the time-lag between the investment decision and independent variables, we adopt the values for all independent variables one period (t-1) before. Since our sample consists of panel data, errors due to the time-series correlation and heteroscedasticity may arise. Petersen (2009) suggests that using the firm-level clustered standard error can reduce such errors considerably. Therefore, we test our hypotheses using OLS regressions with a clustered standard error at the firm-level. To control for the year and industry effects to reduce the potential endogeneity, we include the year (Year effect, η) and industry dummies (Industry effect, λ) in the model. Equation (2) represents the main empirical model, and we provide the definitions of each variable in <Appendix>.

To examine the effect of controlling shareholder’s ownership according to the level of product market competition, we set three dummy variables based on the tertile of competition. High is a dummy variable that takes the value of one when the competition measure is in the highest tertile (non-competitive product markets), Median is a dummy variable that takes the value of one when the competition measure is in the median tertile, and Low is a dummy variable that takes the value of one when the competition measure is in the lowest tertile (competitive product markets). Using the interaction variables between these dummy variables and controlling shareholder’s ownership, we analyze how the effect of controlling shareholder’s ownership changes depending on the level of competition, following Giroud and Mueller (2011). As <Table 1> shows, the division based on the tertile of competition is generally similar to the classification of the monopoly regulation,¹⁴⁾ so we expect that the analysis will reflect the reality.

<Table 3> presents the results of the regression analysis. Model (1)¹⁵⁾ is the result of verifying the effect of controlling shareholder’s ownership on investment inefficiency. The coefficient of Controlling ownership is significantly negative (-) at the 5% level. This result implies that, as discussed theoretically, controlling shareholders with low ownership tend to overinvest to maximize their private benefits (Hypothesis 1-1). On the other hand, controlling shareholders with large ownership tend to underinvest as they are more risk-averse (Hypothesis 1-2).

<Table 3>

Effect of Controlling Shareholders’ Ownership and Product Market Competition on Investment Inefficiency

This table presents the effect of the controlling shareholders’ ownership and product market competition on investment inefficiency using OLS regressions. The dependent variable is Residual in models (1)-(4) and Excess investment in models (5) and (6). Models (1), (2), (5), and (6) show the result for the total sample. Model (3) is the result using the sample of firms in the upper 33% of HHI, and Model (4) is the result using the sample of firms in the lower 33% of HHI. To remove outliers, each variable is winsorized at the 1% and 99% levels. The definitions of variables are in Appendix. The numbers in square brackets are z-statistics computed by standard errors clustered at the firm level. ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively.

Model (2) is the analysis of whether the influence of the controlling shareholder’s ownership on investment inefficiency changes according to product market competition. The coefficient of the interaction variable between Controlling ownership and High has a statistically negative (-) value, suggesting that controlling shareholders change investment expenditures to pursue private benefits only in non-competitive product markets. Notably, the magnitude and statistical significance of the coefficient of the interaction variable is larger and more significant than is the coefficient of Controlling ownership in model (1). Thus, our results for the overall sample are mainly driven by the behavior in non-competitive product markets. The interaction variables between Controlling ownership, and Median and Low are not statistically significant, implying that controlling shareholders do not change investment expenditures according to their ownership due to the disciplinary effect of competitive threats. The coefficient of HHI is insignificant, meaning that we find a moderating effect of the controlling shareholders on management decisions, rather than a direct effect of competition. The above results support Hypothesis 2-1.

Among the control variables, the debt-to-equity ratio (Leverage) has a significant negative (-) effect, which we can interpret as an increase in interest costs and a relatively high risk of bankruptcy, making aggressive investment difficult. The market-to-book ratio (Market-to-book), which is a substitute for growth opportunities, has a positive (+) coefficient, as firms with relatively high growth opportunities actively expand investment spending. Free cash flow also has a positive (+) impact because firms with high internal funding capacity can cover the cost of investment. The age of the firm (Age) has a positive (+) coefficient, as older firms have low information asymmetry and can secure external financing. Liquidity has a positive (+) effect because firms with a large number of assets to use in the short term can actively invest.

We test the hypotheses empirically using interaction variables, but we can also use a separated sample approach. The separated sample approach assumes that there is a difference in the effect of all independent variables between different samples, while the interaction variables approach assumes that there is a difference only in the effect of controlling shareholders’ ownership. Model (3) shows the effect of controlling shareholders’ ownership on the investment inefficiency in firms in non-competitive product markets (HHI upper 33%, High), and model (4) shows the result of the sample of firms in competitive product markets (HHI lower 33%, Low). The coefficient of Controlling ownership in model (3) has a significantly negative (-) value at the 5% level, while the significance in model (4) disappears.

Models (5) and (6) show the results of the same analysis as in models (1) and (2), but using industry-adjusted investment expenditures (Excess investment) as the dependent variable. The coefficient of the controlling shareholders’ ownership in model (5) is negative (-), but not significant. The interaction variables between Controlling ownership, and Median and Low are not significant. The results have the same interpretation as in the results of model (2).

4.2.2 Overinvestment Versus Underinvestment

We further analyze investment inefficiency by examining overinvestment and underinvestment separately for a more rigorous examination of the path of the agency problems. Models (1) and (2) in <Table 4> focus on the overinvestment problem. The dependent variable is Residual Over. In model (1), the coefficient of Controlling ownership is significantly negative (-) at the 1% level. In model (2), the interaction variable between Controlling ownership and High is significant and negative (-), but that between Controlling ownership and Median and Low is insignificant. Models (3) and (4) focus on the underinvestment problem, and the dependent variable is Residual Under. The coefficient of Controlling ownership in model (3), as well as the coefficients of the interaction variables in model (4), are insignificant. These results imply that the results in <Table 3> are mainly due to the overinvestment problem. That is, the main path by which controlling shareholders pursue private benefits is overinvestment based on low ownership. The disciplinary effect of competitive threats affects this overinvestment behavior.

<Table 4>

Overinvestment Versus Underinvestment

This table presents the effect of controlling shareholders’ ownership and product market competition on overinvestment and underinvestment. The dependent variable is Residual Over in models (1) and (2), Residual Under in models (3) and (4), and Residual Dummy in models (5) and (6). Models (1)-(4) use OLS regressions and models (5) and (6) use a Probit model. To remove outliers, each variable is winsorized at the 1% and 99% levels. The definitions of variables are in Appendix. The numbers in square brackets are z-statistics computed by standard errors clustered at the firm level. ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively.

Models (5) and (6) present the result of the probit model using Residual Dummy as a dependent variable to examine whether the incentive for overinvestment or underinvestment is more related to the controlling shareholders’ ownership and product market competition. The Residual Dummy is a dummy variable that takes the value of one if a firm is an overinvestment firm. This approach focuses on the probability of over- or underinvestment rather than their scales. It compares the tendencies to overinvest or underinvest and alleviates the concern about overestimation due to the scale of over- or underinvestment. In model (5), the coefficient of Controlling ownership is significant and negative (-), which suggests that controlling shareholders with low ownership tend to overinvest. In model (6), the coefficient of the interaction variable between Controlling ownership and High is significantly negative (-), implying that we mainly observe the overinvestment tendency found in model (5) in non-competitive industries.

4.3.1. Alternative Model Specifications

<Table 5> presents the result of a robustness check using alternative model specifications. Panel A shows the results of the regression analysis proposed by Fama and MacBeth (1973). After deriving the coefficients from the regression analysis based on the cross-sectional data for each fiscal year, we calculate the average of the coefficients and verify the statistical significance. We thus reduce the limitation of the OLS regression due to cross-sectional correlation considerably. Models (1) and (2) are the results of this cross-sectional regression using Residual as a dependent variable. Similar to the main result, the coefficient of Controlling ownership is significantly negative (-) in model (1), and only the coefficient of the interaction variable between Controlling ownership and High is significant and negative (-) among the interaction variables in model (2). This result is the same as that in <Table 3>. Models (3) and (4) use the Residual Over and models (5) and (6) use the Residual Under as the dependent variable, respectively. The results of models (1) and (2) are consistent with those in models (3) and (4), reaffirming that controlling shareholders’ pursuit of private benefits based on their ownership is mainly related to overinvestment.

<Table 5>

Robustness Check 1: Alternative Model Specifications

This table presents the results for the effects of controlling shareholders’ ownership and product market competition on investment inefficiency through alternative model specifications. Panel A shows the results of the Fama and MacBeth (1973) model, Panel B shows the result of the firm fixed-effect model, and Panel C shows the result of the 2SLS model. Each panel uses three dependent variables (Residual, Residual Over, and Residual Under). To remove outliers, each variable is winsorized at the 1% and 99% levels. The definitions of the variables are in Appendix. The numbers in square brackets are t-statistics. ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively.

Panel A: Fama and MacBeth (1973) cross-sectional regression

Panel B presents the results using a firm fixed-effect model. This model mitigates the endogeneity problem due to the omitted variable bias by reflecting unobservable firm characteristics in the constant term.^16), In model (1), which uses Residual as a dependent variable, the coefficient of Controlling ownership is negative (-), but insignificant. However, in model (2), the coefficient of the interaction variable between Controlling ownership and High is significantly negative (-). Models (3) and (4) are the results using Residual over as a dependent variable. The results are similar to those in <Table 4>.

Lastly, panel C shows the results of the 2SLS analysis.^17), The 2SLS method reduces the endogeneity problem based on reverse causality. On the potential reverse causality between investment inefficiency (Residual) and Controlling ownership, we conduct the analysis using a one-period time-lag between the two variables. Nevertheless, given the claims in prior studies that the ownership of controlling shareholders could be determined endogenously, it cannot be completely free from the endogeneity problem (Demsetz and Lehn, 1985). Model (1) presents the results of the first stage model. The coefficient of Stock return volatility is significant and negative (-). In general, the instrument variable is adequate by the rule of thumb if its t-value is 3.3 or higher. Stock return volatility fulfills the criteria, thus confirming its adequacy. Models (2) and (3) are the results using Residual as a dependent variable. The coefficient of Controlling ownership in Model (2) is not significant, but the coefficient of the interaction variable between Controlling ownership and High in Model (3) is significant. This result supports our main finding. Models (4) and (5) use Residual Over and models (6) and (7) use Residual Under as the dependent variable, respectively. Only the coefficient of the interaction variable between Controlling ownership and High in model (5) is negative (-), confirming that controlling shareholders’ pursuit of private benefits is mainly related to overinvestment.

4.3.2 Alternative Measures of Product Market Competition

<Table 6> shows the results of repeating the analyses in <Table 3> and <Table 4> using alternative measures of product market competition to reduce the potential measurement error from both the original measures of competition and the industry classification. Panel A presents the results of the analysis using three alternative measures. Models (1) - (3) use CR4, models (4) - (6) use Entry cost, and models (7) - (9) use Price-cost margin to measure the level of competition. In most models, we find a negative (-) influence of Controlling ownership on investment inefficiency mainly in non-competitive markets (High), which disappears in competitive markets (Low). In addition, investment inefficiency is mainly related to overinvestment, but not to underinvestment. These results confirm that our main results do not change with the selection of the measure of competition and are robust.

<Table 6>

Robustness check 2: Alternative Methods of Calculating Product Market Competition

This table presents the results of the OLS regression analysis of the effects of controlling shareholders' ownership and product market competition on investment inefficiency using alternative measures of product market competition. Panel A shows the result using alternative methods to calculate product market competition. Models (1)-(3) use CR4, models (4)-(6) use Entry cost, and models (7)-(9) use Price-cost margin as an alternative measure. Panel B shows the result using different industrial classification criteria to measure the level of competition. Models (1)-(3) use the 2-digit KSIC (HHI 2digit) and models (4)-(6) use the 4-digit KSIC (HHI 4digit). Each panel uses three dependent variables (Residual, Residual Over, and Residual Under). To remove outliers, each variable is winsorized at the 1% and 99% levels. The definitions of the variables are in Appendix. The numbers in square brackets are z-statistics computed by standard errors clustered at the firm level. ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively.

Panel A: different measures

Panel B presents the results using HHI calculated by applying another industry classification standard. Models (1) - (3) use the 2-digit KSIC (HHI 2digit) and models (4) - (6) use the 4-digit KSIC (HHI 4digit) to estimate HHI. The results are consistent with those in <Table 3> and <Table 4> and confirm the robustness of the main results.