adjustments in managerial ownership and changes in firm value

Adjustments in managerial ownership and changes in firm value

Ming-Yuan Chen⁎Graduate Institute of Human Resource Management, National Central University, No.300, Jhongda Rd., Jhongli City, Taoyuan County 32001, Taiwan

a r t i c l e i n f o a b s t r a c t

Article history:Received 17 April 2011Received in revised form 25 April 2012Accepted 25 April 2012Available online 2 May 2012

This paper investigates the relation between adjustments in managerial ownership andchanges in firm value from two perspectives. First, we examine whether moving toward theoptimal level is an important concern for managers when they adjust their ownership. Second,we analyze the effect of changes in managerial ownership on changes in Tobin's q by focusingon how the market reacts differently between the adjustments toward optimal ownership andother discretionary adjustments. Using panel data of non-financial companies listed on theTaiwan Stock Exchange, we find evidence to show that managers significantly increase theirownership when there are below-optimal deviations, whereas reductions in ownership forabove-optimal deviations are not significant. Empirical results also show that the marketreacts positively to changes in ownership for removing deviations on either side of the optimallevel. Discretionary increases or decreases in managerial ownership are detrimental to firmvalue. Our findings are robust to using different measures of changes in managerial ownershipand to certain modifications in the empirical model.

© 2012 Elsevier Inc. All rights reserved.

JEL classifications:G32G34

Keywords:Managerial ownershipOwnership adjustmentsFirm value

1. Introduction

The effect of managerial ownership on firm value is a central issue to corporate organization and finance researchers.However, there is no theoretical or empirical consensus on this issue in the literature. Morck, Shleifer, and Vishny (1988) andseveral studies using a similar approach such as McConnell and Servaes (1990, 1995), Hermalin and Weisbach (1991), Short andKeasey (1999), Anderson and Reeb (2003), and Adams and Santos (2006) found evidence to support a cross-sectional correlationbetweenmanagerial ownership and firm value. Demsetz (1983) developed another methodological approach and argued that theobserved levels of managerial ownership are an endogenous outcome of a profit-maximizing process in which the influence ofshareholders and of market trading for shares is balanced to arrive at the optimal ownership structure of the firm. Firms are attheir optimal ownership levels and the levels vary across firms. The cross-sectional relation between managerial ownership andfirm value is thus spurious. Studies by Demsetz and Lehn (1985), Agrawal and Knoeber (1996), Loderer and Martin (1997), Cho(1998), Himmelberg, Hubbard, and Palia (1999), Core and Guay (1999), Demsetz and Villalonga (2001), and Villalonga and Amit(2006) either apply the simultaneous equations model to cross-sectional firm data or use the panel data model and theinstrumental-variables technique to control for the alleged endogeneity problem. Their findings are empirically consistent withDemsetz's (1983) view.

Core and Larcker (2002) indicated that these two schools of thought have different assumptions about the nature oftransaction costs in adjusting the ownership structure. In Demsetz's (1983) view, a firm is assumed to continuously recontractand maintain managerial ownership at the optimal level because there are no transaction (adjustment) costs. A firm's ownershiplevel is always optimal so there will be no systematic relation between ownership and firm value. Core and Larcker (2002) arguedthat firms choose optimal managerial ownership when they contract, but transaction costs prohibit continuous recontracting,

International Review of Economics and Finance 25 (2013) 1–12

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giving rise to gradual ownership deviations from the optimal level. Because optimal ownership is endogenously determined tomaximize firm value (Demsetz, 1983), the deviations on either side of optimal ownership reduce firm value. For a cross-sectionalstudy, a subset of firms always has poor performance because ownership is not continuously re-optimized. Core and Larcker(2002) suggested that an effective sample to examine the link between managerial ownership and firm value is to find a set offirms for which managerial ownership levels are too low (high), but then recontract to increase (decrease) ownership. For thesefirms, required adjustments in managerial ownership, either increases or decreases, should increase firm value because firmsdecide to recontract only when the benefits associated with recontracting are greater than its costs.

Despite the reconciliation by Core and Larcker (2002), empirical studies in the literature examining whether optimal leveldeviations are an important determinant of the changes in managerial ownership, and how the market reacts to these changesaimed at moving toward the optimal level, are scant. McConnell, Servaes, and Lins (2008) focused on the relation betweenchanges in managerial ownership and changes in firm value and found a negative relation between the amount of managerialshare purchases and the amount of pre-purchase ownership subtracted from predicted optimal ownership. This result,unfortunately, is opposite to what is expected if the share purchases are meant to attain optimal ownership. Their study also givesno evidence that the market reacts positively to such optimal ownership-induced share purchases. Tong (2008) found evidence tosupport the argument of Core and Larcker (2002). He showed that both above-optimal and below-optimal deviations of CEOownership reduce firm value, but the difference in the negative effect on firm value is not significant between both deviations.When ownership deviations are above the optimal level, CEO share sales are associated with higher abnormal return and CEOshare purchases are associated with lower abnormal return. Helwege, Pirinsky, and Stulz (2007) and Fahlenbrach and Stulz(2009) investigated the determinants and effect of large changes in ownership. However, they did not emphasize the role of theoptimal level in ownership adjustments.

While previous studies have suggested that optimal level deviations lead to subsequent ownership adjustments, movementtoward the optimal level is not the only source of observed ownership adjustment. Changes in managerial ownership could belarger or smaller than changes required to achieve the optimal level, or even move in the opposite direction, because of managers'discretionary intention to manipulate ownership for their own benefit or to defend themselves against unfriendly businessevents. The observed changes in managerial ownership thus consist of adjustments arising from optimal level deviations anddiscretionary adjustments, which are not based on optimal ownership consideration and may interfere with expectedadjustments. This decomposition is not simply a theoretical statement. By assessing the market and business conditions of thefirm, investors of the firm are able to recognize the managers' motivation behind changes in ownership and distinguish requiredownership adjustments from discretionary ones. The resulting changes in firm value are composed of different market valuationson two sources of adjustments. We believe that disentangling the sources of adjustments in ownership and identifying theirdifferent effects on firm value facilitate a more thoughtful description about how changes in managerial ownership toward theoptimal level affect changes in firm value.

This paper addresses the relation between managerial ownership and firm value from two perspectives. First, we examinewhether moving toward the optimal level is a significant concern for managers when they adjust their ownership. Theoretically, ifmanagers stick to the optimal level in adjusting their ownership, those having above-optimal deviations will have downwardadjustments, whereas upward adjustments appear for below-optimal deviations. However, this makes an unrealistic assumptionthat ownership adjustments toward the optimal level from either side of that level are the same. It is very possible and morerealistic to expect a downward rigidity in ownership adjustments because managers may be concerned about losing theirownership stakes and attempt to maintain relative advantage in controlling positions. Managers desire to increase theirownership when there are below-optimal deviations, but are less willing to reduce their ownership for above-optimal deviations.This study tests the hypothesis of asymmetric adjustments in the sense that managers respond differently to deviations fromdifferent sides of optimal ownership.

Second, after examining the adjustment process, this work develops an empirical framework to decompose ownershipadjustments into two components, namely, adjustments caused by deviations from optimal ownership and discretionaryadjustments, and tests how the market reacts to two types of adjustments. The market is expected to react positively whenchanges in managerial ownership are intended to remove the deviations on either side of the optimal level. This apparently is ahypothesis consistent with the theory of Core and Larcker (2002). In this study, we further argue that the Core and Larcker (2002)view can be reinforced by hypothesizing that changes in managerial ownership because of managers' discretionary manipulation,either increasing or decreasing ownership, should lower firm value because these changes divert the expected adjustment pathtoward the optimal level.

Using panel data constructed from non-financial companies listed on the Taiwan Stock Exchange (TWSE) during 2000–2008,we find that moving toward the optimal level is an important factor to determine managerial ownership adjustment across years.Adjustment asymmetry exists between managers that have positive and negative ownership deviations. Managers who holdownership below the optimal level experience large subsequent increases in ownership, whereas the decreases in ownership formanagers having above-optimal deviations are not significant. The results are robust even though we normalize the deviations byfirm size or measure the changes in ownership as those caused by changes in the number of shares held by managers(Fahlenbrach & Stulz, 2009; Helwege et al., 2007). Empirical results also show that changes in ownership toward the optimal levelfrom either side of that level significantly raise firm value. Other discretionary increases or reductions in ownership aredetrimental to firm value. These findings still hold for a restricted sample of firms having large ownership variations over time.Accordingly, our empirical results support the interpretation of Core and Larcker (2002) in reconciling the competing viewsposited in the literature.

2 M.-Y. Chen / International Review of Economics and Finance 25 (2013) 1–12

In the remainder of the paper, Section 2 presents an empirical framework to model the relation between adjustments inmanagerial ownership and changes in firm value. Section 3 details variable measurement and data. Empirical results anddiscussions are presented in Section 4. Section 5 concludes the paper.

2. Empirical methodology

Himmelberg et al. (1999) suggested a benchmark specification that hypothesizes certain firm characteristics to determine afirm's optimal managerial ownership. We initially estimate a similar model with firm fixed effects and use the model to predictthe annual optimal level of managerial ownership for the firms in our sample. The model for estimating firm i's optimalownership at year t can be expressed as

Sit ¼ φi þ ηt þ γXit þ uit : ð1Þ

The dependent variable, Sit , is the logistic transformation of managerial ownership (MHit), calculated as the ratio of the number ofshares owned by managers to the number of the firm's total shares outstanding at the end of year t, or Sit=ln[MHit/(1−MHit)].FollowingHimmelberg et al. (1999),McConnell et al. (2008), and Fahlenbrach and Stulz (2009), we definemanagers as top officers andmembers of the board of directors. The logistic transformation ismade tomap a proportional dependent variable, which is bounded by0 and 1, to the unbounded real line for fitting a regression model. This is also a method adopted by Demsetz and Lehn (1985). φi is thefirm-specific term capturing unobserved firm characteristics and ηt is a set of year dummies to filter macro-economic shocks that arecommon across firms. Xit, discussed in the next section, represents observed firm characteristics hypothesized to affect managerialownership. The fitted value of Sit, denoted as Sit* , stands for firm i's predicted optimal level of managerial ownership at year t.

Whether this approach is appropriate to measure optimal ownership might be questionable because statistically it is only theexpected value of the dependent variable (Sit) for a given set of explanatory variables represented by sample firms. We recognizethis concern; however, this seems to be an empirical strategy widely accepted in the literature. Using the fitted value of thedependent variable as the proxy for its optimal, benchmark, or targeted value has been adopted in the research of corporatefinance and management, for example, studies on ownership structure (McConnell et al., 2008; Tong, 2008), executivecompensation (Core, Holthausen, & Larcker, 1999; Ezzamel & Watson, 1998), and corporate board structure (Cicero, Wintoki, &Yang, 2010). In a paper on the relation between CEO ownership and firm value, Tong (2008) validated this approach by arguingthat if this specification cannot provide a proper description of optimal ownership, the regression residuals, which representdeviations from the optimal level, will not have systematic and significant effect on firm value. Therefore, our findings onownership adjustment in response to previous deviations and the relation between firm value and ownership changes because ofthese deviations assess the appropriateness of this specification. Considering the expected (fitted) ownership level as an optimalone also yields a sensible interpretation. The sample of this study is the companies listed on the TWSE; therefore, the expectedlevel can be regarded as a market-wide level of managerial ownership given specific firm characteristics. This value may not be aperfect proxy for the optimal ownership level, but it is a level that managers of comparable firms in the market are expected tohold and an important benchmark when managers decide to change their ownership because market investors tend to evaluatemanager behavior by referring to similar firms in the market. This expected level will guide managers to adjust their ownership.

To measure to what extent managerial ownership adjustments arise from the movement toward the optimal level, weformulate the following regression model:

ΔSit ¼ φi þ ηt þ δ Si;t−1−S�i;t−1

� �þ εit ; ð2aÞ

ΔSit ¼ φi þ ηt þ δp Si;t−1−S�i;t−1

� �pos

þ δn Si;t−1−S�i;t−1

� �neg

þ εit ; ð2bÞ

where ΔSit=Sit−Si, t−1 are the changes of managerial ownership from year t–1 to year t, and Si, t−1−Si, t−1* are the ownershipdeviations from the predicted optimal level for firm i at year t–1. To consider adjustment asymmetry between managers whohave ownership above and below the optimal level, in Eq. (2b), Si, t−1−Si, t−1* are separated out for both types of managers: formanagers having above-optimal (positive) deviations, (Si, t−1−Si, t−1* )pos=Si, t−1−Si, t−1* and (Si, t−1−Si, t−1* )neg=0; and forthose having below-optimal (negative) deviations, (Si, t−1−Si, t−1* )neg=Si, t−1−Si, t−1* and (Si, t−1−Si, t−1* )pos=0. Coefficientsδp and δn are predicted to be negative if ownership is adjusted toward the optimal level. Negative deviations lead to increases inownership, and decreases in ownership are for positive deviations. Normally, there is a partial adjustment in a single period sothat δp and δn will be between 0 and −1. The earlier stated hypothesis of asymmetric adjustments predicts that δn has a largermagnitude and is more significant than δp.

Firm size may affect the deviationmagnitude from optimal ownership (Tong, 2008). Larger firms generally have greater capitalresources, and hence have larger market value. Because of the higher price for a given fraction of ownership, individual managerstypically cannot purchase sufficient shares to reach optimal ownership in a fixed period when below-optimal deviations exist.Similarly, it is also more difficult for managers to sell shares rapidly in the market at a higher price to remove above-optimaldeviations. Therefore, large firmsmay havemore deviations from optimal ownership than small firms do. For robustness check, weconsider the effect of size-adjusted deviations where (Si, t−1−Si, t−1* ),, (Si, t−1−Si, t−1* )pos, and (Si, t−1−Si, t−1* )neg are normalizedby firm size, that is, divided by firm asset.

3M.-Y. Chen / International Review of Economics and Finance 25 (2013) 1–12

In estimating Eqs. (2a) and (2b), the error term, εit, which is the part of the dependent variable ΔSit (i.e., Sit−Si, t−1) thatcannot be explained by the explanatory variables, is correlated with the explanatory variable Si, t−1−Si, t−1* . This endogeneityproblem causes OLS estimation to be inconsistent. Instrumental-variables estimation can be used to solve such problems. We usethe lag variable, Si, t−2−Si, t−2* , as the instrument for Si, t−1−Si, t−1* , and (Si, t−2−Si, t−2* )pos and (Si, t−2−Si, t−2* )neg as theinstruments for (Si, t−1−Si, t−1* )pos and (Si, t−1−Si, t−1* )neg. Statistical tests for the instruments are applied. For the test ofendogeneity, the statistic is the difference of two Sargan–Hansen statistics: one for the equation where Si, t−1−Si, t−1* is treatedas endogenous, and one for the equation where it is treated as exogenous. Under the null hypothesis that Si, t−1−Si, t−1* can betreated as exogenous, the statistic is distributed as chi-squared. The test of under-identification, where the null hypothesis is thatSi, t−2−Si, t−2* is not correlated with Si, t−1−Si, t−1* , is performed by the Kleibergen and Paap (2006) LM test statistic, whichis also distributed as chi-squared. Because we have a just-identified case, the test of over-identifying restrictions, such asHansen's J test, is not applied.

Resulting estimated coefficients of Eq. (2b) are used to calculate the following components of ownership adjustments:

ΔSitð Þopt�neg ¼ δp Si;t−1−S�i;t−1

� �pos

; ð3Þ

ΔSitð Þopt�pos ¼ δn Si;t−1−S�i;t−1

� �neg

; ð4Þ

ΔSitð Þdisc ¼ ΔSit−δp Si;t−1−S�i;t−1

� �pos

−δn Si;t−1−S�i;t−1

� �neg

: ð5Þ

The first component, (ΔSit)opt-neg, is the downward adjustment (decrease) in managerial ownership at year t due to above-optimal deviations at year t–1. The second component, (ΔSit)opt-pos, is the upward adjustment (increase) in managerialownership at year t due to below-optimal deviations at year t–1. The third component, (ΔSit)disc, which is the part of ΔSit thatcannot be explained by the movement toward the optimal level, represents the discretionary ownership adjustments at year t.

The main regressions of examining how changes in managerial ownership affect the subsequent changes in Tobin's q, which isthe proxy for firm value, are shown as

Δqi;tþ1 ¼ φþ ηt þ β1 ΔSitð Þpos þ β2 ΔSitð Þneg þ γΔXit þ εi;tþ1; ð6aÞ

Δqi;tþ1 ¼ φþ ηt þ θ1 ΔSitð Þopt�neg þ θ2 ΔSitð Þopt�pos þ θ3 ΔSitð Þdisc�neg þ θ4 ΔSitð Þdisc�posþγΔXit þ εi;tþ1: ð6bÞ

Tobin's q is measured as the sum of the market value of common equity and the book value of total debt divided by the bookvalue of total assets. To capture the pure effect of adjustments in managerial ownership, changes in firm characteristics (ΔXit) areincluded as the control variables. Eq. (6a) relates subsequent changes in q to changes in managerial ownership. The effects ofpositive and negative changes in ownership are separately estimated so that ΔSit is specified in two variables: (ΔSit)pos=Sit whenΔSit>0 and zero otherwise; (ΔSit)neg=ΔSit when ΔSitb0 and zero otherwise. Eq. (6b) relates subsequent changes in q to variouscomponents of changes in managerial ownership obtained from Eqs. (3), (4), and (5). Similar to ΔSit, (ΔSit)disc is also separatelyspecified as two variables, (ΔSit)disc-neg and (ΔSit)disc-pos. Both equations are estimated by cross-sectional OLS because alldependent and independent variables are first-differenced. The time-invariant firm heterogeneity, which might affect firm value,is cancelled out.

Because (ΔSit)opt-neg has negative value and (ΔSit)opt-pos has positive value, the hypothesis that the market reacts positively toownership adjustments for attaining the optimal level implies that the coefficient θ1 will be negative and θ2 positive. For (ΔSit)disc-negand (ΔSit)disc-pos, the hypothesis that discretionary changes in ownership lead to reduced firm value suggests a positive θ3 and anegative θ4.

Helwege et al. (2007) indicated that ΔSit might provide an incomplete measurement of manager incentives to change theirownership. Recall that ΔSit is computed as the change in the ratio of the number of shares held by managers to the total number ofshares outstanding (in the logistic form). The ratio could fall even if managers increase share purchases, providing there is a largerincrease in the number of shares outstanding. An increase in ΔSit resulting from manager shares purchase reflects managerialincentives differently from an increase in ΔSit caused by a decrease in the number of shares outstanding (Fahlenbrach & Stulz,2009; Lambert, Larcker, & Verrecchia, 1991). Therefore, by referring to the decomposition used by Helwege et al. (2007), weconsider an alternative measure to focus on the changes of managerial ownership caused by changes in the number of shares heldby managers. This measure, denoted as ΔSMit, is calculated as the logistically transformed ratio of the number of shares held bymanagers at year t to the total number of shares outstanding at year t–1 minus the logistically transformed ratio of the number ofshares held by managers at year t–1 to the total number of shares outstanding at year t–1. Eqs. (2a) and (2b) are re-estimatedusing ΔSMit as the dependent variable to understand how managers change their own shareholding when ownership deviationsfrom the optimal level exist. The components, (ΔSMit)opt-neg, (ΔSMit)opt-pos, and (ΔSMit)disc are calculated following the formulasof Eqs. (3)–(5) and their effects on changes in firm value are examined by Eqs. (6a) and (6b).


3. Variable measurement and data

3.1. Measurement of firm characteristics

Firm characteristics considered in this study to determine the optimal level of managerial ownership include firm size, firmage, fixed capital investments, R&D spending, capital expenditures, free cash flow, leverage, and firm's idiosyncratic risk. Thesevariables, mostly suggested by Himmelberg et al. (1999), have been used by numerous related studies.

Demsetz and Lehn (1985) indicated that greater market value and higher price of a given fraction of ownership in large firmsprevents managers from owning a high percentage of equity because of the constrained wealth of individual managers. Besides, agiven degree of control generally requires a smaller share of the firm as firm size increases. Both effects imply that managerialownership decreases with firm size. Demsetz and Lehn further argued that risk aversion might reinforce this negative size effecton ownership. Because preserving concentrated ownership in a larger firm necessitates committing more wealth to a single firm,risk-averse managers purchase additional shares only at lower and risk-compensating prices. This increased cost of capitaldiscourages large firms to maintain an ownership structure having a high percentage of managerial ownership. We use thelogarithm of the firm's total assets (lnASSET) to measure firm size.

From the perspective of life cycle of the firm, firm age is an important factor related to firm ownership structure.Entrepreneurs with concentrated managerial ownership are typically the original owners of a firm. However, the founders' heirsmay not have the desire or ability to manage the firm. A diversified portfolio would be more attractive than ownership of the firm.If the firm cannot borrow on acceptable terms, it needs to issue public equity to finance growth. The firm's ownership tends to bewidely held as it grows. Therefore, there is more time for older and larger firms to disperse their ownership. Managerialownership concentration is expected to be negatively related to firm age and firm size. Firm age (FAGE) is measured as thenumber of years since the firm's inception. The life cycle theory makes the same prediction about firm size effect as the Demsetzand Lehn (1985) argument.

Within the agency theory perspective, because fixed capital investments are observable andmore easily monitored, firms witha lower concentration of fixed capital in their inputs have a higher potential for managerial expropriation. Managerialexpropriation implies large private benefits accruing to managers, not only pecuniary, but also non-pecuniary benefits, such asengaging in self-dealing transactions. Because high managerial ownership typically plays a governance mechanism in the agencytheory (Park, Selvili, & Song, 2008), firms having lower degrees of fixed capital call for higher levels of managerial ownership toreduce managerial incentives of resource expropriation. We use the ratio of property, plant, and equipment to total assets (PPEA)as the measure of the relative importance of fixed capital in firms' technology.

In addition to fixed capital, three variables, R&D spending, capital expenditures, and free cash flow, are also the proxy forexpropriation opportunities of the managers. Greater R&D spending and capital expenditures mean more informationasymmetries and managerial discretion. More ownership will thus be required to ensure that this discretion is used to benefitshareholders. According to Jensen (1986), agency costs are higher for firms with more free cash flow so that higher levels ofownership are desired to better align with shareholder interests. R&D spending is measured as the ratio of research anddevelopment expenditures to total assets (RDA). A dummy variable, which is equal to one if data on R&D spending are missing, isincluded. When this dummy is one, the value of RDA is set to zero. We measure a firm's capital expenditures by the ratio of capitalexpenditures to total assets (CAPEXA), and free cash flow by the ratio of earnings before interest, taxes, depreciation, andamortization to total sales (FCF). A dummy assigned value of one is also for missing data of capital expenditures. The value ofCAPEXA is set to zero if this dummy is one.

The debt issue can reduce free cash flow available for managers by bonding their promise to make the interest and principalpayments (Garvey, 1992; Jensen, 1986). More debt is associated with lower managerial ownership because it reduces theimportance of managerial ownership being a convergence-of-interest mechanism. However, Stulz (1988) indicated that ifmanagers are concerned about controlling power, they may use more debt so that they can afford a large proportional stake in thefirm's cash flow. This implies a positive correlation between debt use and managerial ownership. Debt value is measured as totaldebt divided by total assets (DEBTA).

Demsetz and Lehn (1985) argued that greater payoff potential in maintaining tighter control in noisier environments calls forgreater ownership concentration. Managerial behavior is more difficult to monitor and more crucial for profitability in a lesspredictable firm environment. Therefore, higher firm risk increases the value of incentive contracts with large ownership.However, the cost of higher levels of managerial ownership because of less portfolio diversification rises as risk increases. Thebenefits and costs of managerial ownership may increase simultaneously with a higher firm idiosyncratic risk. Thus, the effect ofrisk on managerial ownership is not conclusive. Firm risk is measured as the standard deviation of idiosyncratic stock price risk(SIGMA), calculated as the standard error of residuals obtained from the market model in which the firm's daily returns areregressed on the daily returns of the value-weighted market portfolio (daily returns of the Taiwan Stock Exchange Index). Thesquare of SIGMA is also included to capture the potential nonlinear effect of firm risk. Analogous to the treatment of missingvalues of RDA and CAPEXA, a dummy variable is assigned if data used to estimate the residual standard error are missing.1 Thevalue of SIGMA is assumed zero when the dummy is one.

1 Several firms in our sample have zero-volume trading days in the daily data, or have days for which daily returns are not available. Therefore, we compute afirm's SIGMA based on at least 200 daily returns per year. For those firms that do not have sufficient daily return data, the dummy variable is set to one.


These variables are all proxies for Xit in Eq. (1) to determine optimal managerial ownership. For Eqs. (6a) and (6b), thechanges in firm characteristics, ΔXit are computed as the changed values of Xit across years. The change of firm age (FAGE) is notincluded because it is equal to one for all firm-year observations. While dummy variables are specified to consider missing valuesof RDA, CAPEXA, and SIGMA in Eq. (1), for the changed values of these variables, a dummy is assigned to one for each variable ifthe current year or previous year value is missing. The changed values are then set to zero if the dummy is one.

3.2. Data and summary statistics

The sample of this study includes 477 non-financial firms listed on the TWSE and reported complete ownership data over theperiod 2000–2008. For Eq. (1) of the determinants of optimal managerial ownership, 477 firms with nine observations eachconstitute a balanced panel data set. The total observations are 4293. For Eqs. (2a) and (2b), because data for year t–1 are used todefine optimal ownership deviations and data for year t–2 are reserved as instrumental variables in model estimation, the totalobservations are 477 firms with seven observations each (2002–2008), for a total 3339. The components of annual ownershipadjustments during 2002–2008 are computed according to Eqs. (3), (4), and (5). Following Eqs. (6a) and (6b), we examine howchanges in Tobin's q in subsequent years, that is, 2003–2009, are affected by changes in managerial ownership and their

Table 1Summary statistics.

A. Descriptive statistics (number of observations=4293)

Mean Std. dev. Min Max

MH 0.242 0.138 0.024 0.971S −1.285 0.789 −3.705 3.525lnASSET 15.763 1.241 12.656 20.290FAGE 28.811 11.584 3.000 63.000PPEA 0.265 0.185 0.000 0.923RDA 0.013 0.022 0.000 0.301CAPEXA 0.029 0.043 0.000 0.679FCF 0.074 0.093 −0.818 0.458DEBTA 0.401 0.169 0.015 0.986SIGMA 0.023 0.010 0.000 0.302Dummy for RDA 0.367 0.482 0.000 1.000Dummy for CAPEXA 0.017 0.130 0.000 1.000Dummy for SIGMA 0.051 0.221 0.000 1.000

B. Means of changes in managerial ownership and changes in Tobin's q

Year (t) Changes in ownership Positive changes in ownership Negative changes in ownership Changes in Tobin's q (qt+1−qt)

MHt−MHt−1

2001 −0.010 (477) 0.029 (143) −0.030 (302) −0.139 (477)2002 −0.010 (477) 0.026 (129) −0.026 (313) 0.115 (477)2003 −0.006 (477) 0.023 (226) −0.033 (237) −0.071 (477)2004 −0.009 (477) 0.026 (141) −0.027 (301) −0.016 (477)2005 −0.006 (477) 0.024 (160) −0.024 (283) 0.192 (477)2006 0.004 (477) 0.034 (198) −0.021 (244) −0.030 (477)2007 −0.003 (477) 0.029 (174) −0.024 (272) −0.389 (477)2008 0.002 (477) 0.021 (222) −0.019 (214) 0.479 (467)Overall −0.005 (3816) 0.026 (1393) −0.026 (2166) 0.016 (3806)

MHt−MHt−1 (caused by changes in the number of shares held by managers)2001 0.022 (477) 0.053 (293) −0.033 (155)2002 0.014 (477) 0.052 (238) −0.026 (216)2003 0.007 (477) 0.031 (303) −0.037 (171)2004 0.004 (477) 0.030 (246) −0.027 (212)2005 0.005 (477) 0.028 (271) −0.026 (191)2006 0.012 (477) 0.038 (271) −0.025 (185)2007 0.011 (477) 0.043 (260) −0.029 (200)2008 0.006 (477) 0.026 (295) −0.032 (155)Overall 0.010 (3816) 0.037 (2177) −0.029 (1485)

Notes: Panel A reports descriptive statistics for the variables used in this study. The number of observations is 4293, including 477 firms with 9 observations each(2000–2008). MH is the ratio of the number of shares owned by managers (top officers and members of the board of directors) to the number of the firm's totalshares outstanding. S is the logistic transformation of MH. lnASSET is the logarithm of the firm's total assets. FAGE is the firm's age. PPEA is the ratio of property,plant and equipment to total assets. RDA is the ratio of research and development expenditures to total assets. CAPEXA is the ratio of capital expenditures to totalassets. FCF is the earnings before interest, taxes, depreciation and amortization divided by total sales. DEBTA is total debt divided by total assets. SIGMA is thestandard error of the residuals obtained from the market model in which the firm's daily returns are regressed on the daily returns of Taiwan Stock ExchangeIndex. Dummy for RDA is equal to one if data on R&D spending are missing. Dummy for CAPEXA is equal to one if data on capital expenditures are missing.Dummy for SIGMA is equal to one if data are missing for estimating the residual standard errors. Panel B reports the mean values of ownership adjustments overthe period 2001–2008 and mean values of changes in Tobin's q in subsequent years, 2002–2009. The numbers in parentheses are the number of observations. Tenfirms have incomplete data for calculating 2009's Tobin's q so that 467 observations are shown in the table.


components. Ten firms have incomplete data for the 2009 Tobin's q; therefore, 477 firms with 3329 observations are used toestimate Eqs. (6a) and (6b). Managerial ownership data (ownership of top officers and members of the board of directors) areavailable from the company profile database maintained by the Taiwan Economic Journal Data Banks, the most reliable datasource for Taiwanese listed companies. Data for all proxy variables for firm characteristics and for Tobin's q are available from thecompany finance and equity databases in the Taiwan Economic Journal Data Banks.

Table 1 shows the summary statistics of the sample. Panel A contains the descriptive statistics for the variables used in themodel. For 477 firms over the period of 2000–2008, managers held, on average, 24.2% of the firm's shares outstanding. There wasa wide range of managerial ownership, with a maximum of 97.1% and a minimum of 2.4%. The results shown in the first part ofpanel B indicate that the means of changes in managerial ownership during 2001–2008, except for 2006 and 2008, were negative.When changes in managerial ownership are considered separately as positive and negative changes, the differences between themeans of positive changes and of negative changes (in absolute value) are not significant. For most years, the differences are lessthan 1%. There is a trend that managerial ownership is downward adjusted during this period, because the number of firmsexperiencing negative changes is greater than that having positive changes. The second part of panel B shows that for all years,ownership changes caused by changes in the number of shares held by managers have a positive mean, and there is a greaternumber of firms with managers increasing their shareholding. The different patterns of results between the two parts of panel Bmay explain why Helwege et al. (2007) and Fahlenbrach and Stulz (2009) expressed concern about the measurement of changesin managerial ownership. Finally, there is no apparent trend for the means of annual change in Tobin's q during 2002–2009.Overall, average annual change in q for all firm-year observations increased by 0.016.

4. Empirical results

Table 2 presents the regression results of Eq. (1), the determination of managerial ownership. For comparison, the equation isestimated by the fixed effects and random effects models. To deal with heteroskedasticity in the panel data set, we report therobust standard errors of the coefficient estimates clustered at the firm level. The year dummies and three dummies assigned formissing values of RDA, CAPEXA, and SIGMA are included but not reported. The large Hausman statistic value (179.57) favors thefixed effects model over the random effects model. In the following analyses of ownership adjustments, the fixed effectsestimation is used to obtain the predicted optimal level of managerial ownership.

Most of the results shown in Table 2 are in line with the theoretical predictions. Larger and older firms (higher values oflnASSET and FAGE) are associated with lower levels of managerial ownership. Increases in fixed capital intensity (PPEA) lead to adecline of managerial ownership. Capital expenditures (CAPEXA) and free cash flow (FCF) have significantly positive coefficients,consistent with the argument that greater opportunities for managerial expropriation call for larger ownership to ensureshareholder benefit. R&D intensity (RDA) does not have a significant effect on managerial ownership. Although the agency costs

Table 2The determination of managerial ownership.

Fixed effects Random effects

Coef. Robust Coef. Robust

std. err. std. err.

lnASSET −0.341 (0.050) ⁎⁎⁎ −0.244 (0.035) ⁎⁎⁎

FAGE −0.017 (0.005) ⁎⁎⁎ −0.003 (0.003)PPEA −0.313 (0.161) ⁎ −0.081 (0.144)RDA −1.425 (1.237) −1.523 (1.174)CAPEXA 0.488 (0.265) ⁎ 0.485 (0.269) ⁎

FCF 0.509 (0.137) ⁎⁎⁎ 0.548 (0.134) ⁎⁎⁎

DEBTA 0.376 (0.147) ⁎⁎ 0.258 (0.132) ⁎

SIGMA −4.161 (1.981) ⁎⁎ −5.669 (1.964) ⁎⁎⁎

(SIGMA)2 11.086 (6.039) ⁎ 15.417 (5.968) ⁎⁎

Firm-specific intercepts yesYear dummies yes yesR2 (within) 0.13 0.12Statistic for the model F(19, 476)=7.99 ⁎⁎⁎ χ2(20)=180.28 ⁎⁎⁎

Hausman statistic 179.57 ⁎⁎⁎

Number of observations 4293 4293Number of firms 477 477

Notes: This table reports the results of fixed and random effects estimation of Eq. (1). The dependent variable is Sit, the logistic transformation of the ratio of thenumber of shares owned by managers (top officers and members of the board of directors) to the number of the firm's total shares outstanding. For theexplanatory variables, lnASSET is the logarithm of the firm's total assets, FAGE the firm's age, PPEA the ratio of property, plant and equipment to total assets, RDAthe ratio of research and development expenditures to total assets, CAPEXA the ratio of capital expenditures to total assets, FCF the earnings before interest, taxes,depreciation and amortization divided by total sales, DEBTA total debt divided by total assets, and SIGMA the standard error of the residuals obtained from themarket model in which the firm's daily returns are regressed on the daily returns of Taiwan Stock Exchange Index. All regressions include eight year-dummies(ηt), representing 2001–2008 with omitted year being 2000, to filter the macro-economic shocks and three dummies to capture the effect of missing values inRDA, CAPEXA and SIGMA. Numbers in parentheses are robust standard errors clustered at the firm level. ⁎⁎⁎, ⁎⁎, and ⁎ indicate statistical significance at the 1%, 5%,and 10% levels respectively.


of higher R&D expenditures raise the desired level of managerial ownership, the characteristic uncertainty in R&D investmentsimposes great costs on manager capital commitment and results in a negative relation to managerial ownership. Both effectsoffset each other to have an insignificant coefficient. The value of debt (DEBTA) has a positive effect on ownership levels. Thissuggests that managers in Taiwanese companies are more concerned about control and use more debt so that they can afford alarge stake of the firm (Stulz, 1988). Finally, differing from the result of Demsetz and Lehn (1985), but echoing the findings ofcertain previous studies, such as Bathala, Moon, and Rao (1994) and Himmelberg et al. (1999), firm idiosyncratic risk (SIGMA)carries a significantly negative coefficient with a positive coefficient on its squared term. Managers are reluctant to hold largeownership because the costs associated with reduced portfolio diversification increase with firm risk. The decrease in managerialownership associated with a given increase in risk diminishes at higher levels of risk.

Using fitted values calculated from the fixed effects estimation of Table 2 as the predicted optimal managerial ownership,Table 3 shows the regression results of instrumental-variables estimation of Eqs. (2a) and (2b), which relate changes inownership (ΔSit) and changes in ownership caused by changes in the number of shares held by managers (ΔSMit) to optimallevel deviations. Panel A is for original deviations and panel B is for size-adjusted deviations. Again, the robust standard errorsclustered at the firm level are reported. In both panels, high values of the difference-in-Sargan–Hansen statistic for theendogeneity test, except for the weaker significance level (one-tailed 10% level) in column (3) of panel B, reject the exogeneityof the regressors, Si, t−1−Si, t− 1* , (Si, t− 1−Si, t−1* )pos, and (Si, t−1−Si, t− 1* )neg. Significantly high values of the Kleibergen–PaapLM statistic for the test of under-identification in all regressions suggest that the instruments are correlated with endogenousregressors.

The results in panel A are consistent between ΔSit and ΔSMit although in Table 1 they show different trends of the means ofchanges in ownership across years. The problem of measuring changes in managerial ownership indicated by Helwege et al. (2007)does not cause a problem in our analysis of ownership adjustments. The negative coefficient on Si, t−1−Si, t−1* in columns (1) and (3)suggests that managerial ownership is adjusted toward the optimal level. In columns (2) and (4), (Si, t−1−Si, t−1* )neg has asignificantly negative coefficient between 0 and −1, whereas the negative coefficient on (Si, t−1−Si, t−1* )pos is not significant.Supporting our hypothesis of asymmetric adjustments, those managers who have below-optimal deviations have their ownershipincreased in the following year, but manager willingness to reduce ownership when there are above-optimal deviations is notsignificant.

Table 3Adjustments in managerial ownership for the deviations from optimal ownership.

Dependent variable is ΔSit Dependent variable is ΔSMit

(1) (2) (3) (4)

Coef. Robust Coef. Robust Coef. Robust Coef. Robust

std. err. std. err. std. err. std. err.

A. Ownership deviationsSi, t−1−Si, t−1* −0.538 (0.042)⁎⁎⁎ −0.509 (0.052)⁎⁎⁎

(Si, t−1−Si, t−1* )pos −0.152 (0.218) −0.228 (0.211)(Si, t−1−Si, t−1* )neg −0.906 (0.208)⁎⁎⁎ −0.783 (0.191)⁎⁎⁎

Firm-specific intercepts and year dummies yes yes yes yesEndogeneity test:Difference-in-Sargan–Hansen statistic~χ2 (p-value) 6.419⁎⁎ 8.157⁎⁎ 2.914⁎ 5.162⁎

(0.011) (0.017) (0.088) (0.076)Under-identification test:Kleibergen–Paap LM statistic~χ2 (p-value) 78.967⁎⁎⁎ 23.439⁎⁎⁎ 76.640⁎⁎⁎ 24.453⁎⁎⁎

(0.000) (0.000) (0.000) (0.000)

B. Size-adjusted ownership deviationsSi, t−1−Si, t−1* −1.064 (0.209)⁎⁎⁎ −1.078 (0.264)⁎⁎⁎

(Si, t−1−Si, t−1* )pos −0.100 (0.313) −0.203 (0.356)(Si, t−1−Si, t−1* )neg −2.142 (0.589)⁎⁎⁎ −2.593 (0.674)⁎⁎⁎

Firm-specific intercepts and year dummies yes yes yes yesEndogeneity test:Difference-in-Sargan–Hansen statistic~χ2 (p-value) 4.807⁎⁎ 5.573⁎ 2.109 8.998⁎⁎

(0.028) (0.062) (0.146) (0.011)Under-identification test:Kleibergen–Paap LM statistic~χ2 (p-value) 20.712⁎⁎⁎ 19.275⁎⁎⁎ 19.855⁎⁎⁎ 18.941⁎⁎⁎

(0.000) (0.000) (0.000) (0.000)Number of observations 3339 3339 3339 3339Number of firms 477 477 477 477

Notes: This table reports the estimates of Eqs. (2a) and (2b). The dependent variable is ΔSit, the changes in the logistic transformation of the ratio of the number ofshares owned by managers to the number of the firm's shares outstanding from year t–1 to year t. Si, t−1* is the fitted value of Si, t−1, estimated from Eq. (1), tostand for firm i's predicted optimal managerial ownership at year t–1. Si, t−1−Si, t−1* is the deviations of managerial ownership from the predicted optimal levelfor firm i at year t–1. (Si, t−1−Si, t−1* )pos represents above-optimal deviations and (Si, t−1−Si, t−1* )neg represents below-optimal deviations. All regressionsinclude six year-dummies, representing 2003–2008 with omitted year being 2002, to filter the macro-economic shocks. Numbers in parentheses are robuststandard errors clustered at the firm level. ⁎⁎⁎, ⁎⁎, and ⁎ indicate statistical significance at the 1%, 5%, and 10% levels respectively.


Quantitatively, suppose that managers currently hold 9% of shares outstanding and optimal ownership is 10%, thus 1% below theoptimal level. The coefficient on (Si, t−1−Si, t−1* )neg in Eq. (2) is −0.906, which means that managerial ownership in the followingyear will be 9.90%.2 The ownership increases by 0.90%. Using the same calculation method, the coefficient on (Si, t−1−Si, t−1* )neg inEq. (4), –0.783, implies that the increase in ownership caused by changes in the number of shares held by managers is 0.77%. Ourfindings suggest thatwhen there are below-optimal deviations, the increase in ownershipmight be caused by reducing the number ofshares outstanding, but themajor part of the ownership increase is because of the increase in the number of shares held bymanagers.

The results shown in panel B, where ownership deviations are normalized by firm assets, have the same implications as panelA. The comparison on the coefficient of (Si, t−1−Si, t−1* )neg in both panels indicates that the increase in ownership (ΔSit) and theincrease in ownership because of manager share purchases (ΔSMit) when there are below-optimal deviations are both greater forsize-adjusted deviations than for original deviations. The findings about the relation between ownership deviations andsubsequent adjustments are robust to firm size.

Using Eqs. (3) and (4) with the coefficients reported in column (2) of panel A, we extract the portions of ΔSit arising from thedeviations on either side of the optimal level. The increase in ownership from below-optimal deviations for firm i, (ΔSit)opt - pos, iscalculated as−0.906×(Si, t−1−Si, t−1* )neg. Although the coefficient on (Si, t−1−Si, t−1* )pos is not significant, we also calculate thesmall ownership decrease because of above-optimal deviations as (ΔSit)opt - neg=−0.152×(Si, t−1−Si, t−1* )pos for comparing theeffect on changes in firm value in the following analysis. Discretionary changes in managerial ownership, (ΔSit)disc, are resultedaccording to Eq. (5). The same calculation procedures are applied to the coefficients reported in column (4) for ΔSMit.

Table 4 reports the descriptive statistics of the components of managerial ownership adjustments. Similar to the results inTable 1, the average change in ownership (ΔSit) during the sample period is negative, whereas the average change in ownershipcaused by the changes in the number of shares held by managers (ΔSMit) is positive. The declines in ownership may primarilyarise from the increases in the number of shares outstanding. For ownership adjustments toward the optimal level, the amount ofincreases in ownership for below-optimal deviations, (ΔSit)opt-pos and (ΔSMit)opt-pos, is on average larger than the amount ofdecreases in ownership, (ΔSit)opt-neg and (ΔSMit)opt-neg, but has larger variations across firms. For discretionary ownershipadjustments, the average amount of reductions, (ΔSit)disc-neg and (ΔSMit)disc-neg, is larger than the average amount of increases,(ΔSit)disc-pos and (ΔSMit)disc-pos.

Table 5 shows the regression results examining the effect of managerial ownership adjustments on subsequent changes inTobin's q. The results in columns (1) and (2) show that either decreases or increases of changes in ownership do not havesignificant effect on changes in Tobin's q. Changes in ownership are seemingly irrelevant to changes in firm value. Althoughstudies following the Demsetz (1983) view that ownership is endogenously determined endorse this result, the relation betweenownership and firm value is not straightforward. As shown in column (3), when ownership adjustments are decomposed intoadjustments toward the optimal level and discretionary adjustments, significant findings appear.

In column (3), the coefficient on (ΔSit)opt-neg, a variable with negative value, is negative (−0.465) and the coefficient on(ΔSit)opt-pos, a variable with positive value, is positive (0.168). Both are significant. Thus, a larger magnitude of ownershipadjustments toward the optimal level, either upward or downward, is able to produce greater increases in Tobin's q. The marketreacts positively to changes in managerial ownership that are based on reaching the optimal level, and this positive reaction isindependent of the direction of changes in ownership. This finding supports the notion of Core and Larcker (2002). In contrast tothe Demsetz (1983) assumption, there are non-negligible adjustment costs that prevent a firm from continuously maintaining its

2 In this case, (Si, t− 1−Si, t− 1* )neg=ln[0.09/(1−0.09)]− ln[0.1/(1−0.1)]=−0.116. Therefore, ΔSit=ln[MHit/(1−MHit)]− ln[0.09/(1−0.09)]=−0.906×(Si, t− 1−Si, t−1* )neg=(−0.906)×(−0.116)=0.105. MHit is thus equal to 0.0990, or 9.90%.

Table 4Descriptive statistics for the components of adjustments in managerial ownership.

Mean Std. dev. Min Max

A. Changes in ownershipΔSit −0.025 0.295 −2.064 3.720(ΔSit)opt-neg −0.016 0.027 −0.328 0.000(ΔSit)opt-pos 0.096 0.172 0.000 1.628(ΔSit)disc-neg −0.144 0.218 −1.946 0.000(ΔSit)disc-pos 0.039 0.126 0.000 2.111

B. Changes in ownership caused by changes in the number of shares held by managersΔSMit 0.024 0.355 −2.670 3.769(ΔSMit)opt-neg −0.024 0.041 −0.491 0.000(ΔSMit)opt-pos 0.083 0.149 0.000 1.408(ΔSMit)disc-neg −0.116 0.238 −2.559 0.000(ΔSMit)disc-pos 0.082 0.198 0.000 3.587ΔSit−ΔSMit −0.051 0.230 −2.871 2.714Number of observations 3339

Note: This table reports the descriptive statistics for the components of managerial ownership adjustments according to Eqs. (3), (4), and (5). ΔSit is the changesin the logistic transformation of the managerial ownership. ΔSMit is the portion of ΔSit caused by changes in the number of shares held by managers. For thesubscripts of the variables, opt represents the adjustments toward the optimal level, disc represents the discretionary adjustments that are not based on optimallevel consideration, -neg is for reductions in ownership, and -pos is for increases in ownership.


ownership at the optimal level. While the deviations of ownership from the optimal level reduce firm value, the adjustmentstoward optimal ownership enhance firm value.

The coefficient on (ΔSit)opt-neg has a magnitude considerably larger than the coefficient on (ΔSit)opt-pos. For adjustmentstoward optimal ownership, a given amount of decreases in ownership produces greater improvement in firm value than the sameamount of increases in ownership. This implies that increases in ownership from the below-optimal side deliver less favorableinformation to the market, even though the adjustments from either side are both toward optimal ownership. We can explain thisasymmetric value effect. Several corporate scandals involving manager manipulation of their controlling ownership radicallydistorted the firm's operation and led to delinquencies over the past two decades in Taiwan. Higher managerial ownership islikely perceived by the market as manager intentions to entrench themselves. Market investors recognize that the increases inmanagerial ownership are toward the optimal level, but are not willing to ignore potential managerial expropriation associatedwith higher ownership. This results in smaller increases in firm value, compared to value increases caused by ownershipreductions. This explanation is particular to the Taiwanese business environment and capital markets, but it explores knowledgeabout the different value effects of changes in managerial ownership toward the optimal level when the deviations are derivedfrom different sides of that level.

Column (3) shows a positive coefficient (0.080) on (ΔSit)disc-neg, which is a negative variable, and a negative coefficient(−0.122) on (ΔSit)disc-pos, which is a positive variable. Hence, after partialling out the effect of ownership changes caused byoptimal level deviations, both increases and decreases in ownership give rise to significant declines in firm value. A generalrecognition in the market is that discretionary changes in ownership, which have nothing to do with reaching the optimal level,may come from managers' own beneficial share manipulation and are typically harmful to firm value.

Column (4) reports the results of examining the relation between changes in firm value and changes in ownership broughtabout by changes in the number of shares held by mangers. The difference between ΔSit and ΔSMit is added to the regression as acontrol variable. For ΔSMit, the pattern of the effect of its various components on firm value is the same as that of ΔSit shown incolumn (3), with only the significance level of (ΔSMit)disc-pos reduced. Evidence suggests that after ruling out the effect caused by

Table 5The effect of changes in managerial ownership on changes in firm value.

(1) (2) (3) (4)



ΔSit 0.025 (0.021)(ΔSit)neg 0.027 (0.041)(ΔSit)pos 0.024 (0.032)(ΔSit)opt-neg −0.465 (0.249)⁎

(ΔSit)opt-pos 0.168 (0.058)⁎⁎⁎

(ΔSit)disc-neg 0.080 (0.033)⁎⁎

(ΔSit)disc-pos −0.122 (0.060)⁎⁎

(ΔSMit)opt-neg −0.268 (0.162)⁎

(ΔSMit)opt-pos 0.161 (0.064)⁎⁎

(ΔSMit)disc-neg 0.062 (0.030)⁎⁎

(ΔSMit)disc-pos −0.024 (0.041)ΔSit – ΔSMit 0.032 (0.053)ΔlnASSET −0.170 (0.046)⁎⁎⁎ −0.170 (0.046)⁎⁎⁎ −0.170 (0.047)⁎⁎⁎ −0.178 (0.057)⁎⁎⁎

ΔPPEA 0.188 (0.247) 0.188 (0.250) 0.170 (0.242) 0.188 (0.242)ΔRDA 1.087 (1.668) 1.087 (1.669) 1.164 (1.663) 1.120 (1.666)ΔCAPEXA 0.584 (0.796) 0.584 (0.791) 0.597 (0.782) 0.583 (0.783)ΔFCF 0.157 (0.159) 0.157 (0.161) 0.161 (0.153) 0.204 (0.167)ΔDEBTA 0.137 (0.120) 0.137 (0.121) 0.131 (0.120) 0.123 (0.135)ΔSIGMA −2.188 (1.232)⁎ −2.188 (1.232)⁎ −2.223 (1.221)⁎ −2.308 (1.258)⁎

Constant and year dummies yes yes yes yesAdjusted R2 0.320 0.320 0.323 0.322F-statistic for the model 62.99⁎⁎⁎ 58.79⁎⁎⁎ 52.62⁎⁎⁎ 49.50⁎⁎⁎

Number of observations 3329 3329 3329 3329Number of firms 477 477 477 477

Notes: This table reports the estimates of Eqs. (6a) and (6b). The dependent variable is the changes in Tobin's q from year t to year t+1. Tobin's q is measured bythe sum of the market value of common equity and the book value of total debt divided by the book value of total assets. ΔSit is the changes in the logisticallytransformed managerial ownership. ΔSMit is the portion of ΔSit caused by changes in the shares held by managers. The components of ownership adjustments areobtained according to Eqs. (3), (4), and (5). The subscript opt represents the adjustments toward the optimal level, disc represents the discretionary adjustments,-neg is for reductions in ownership, and -pos is for increases in ownership. For other explanatory (control) variables, Δ denotes the changes from year t–1 toyear t. lnASSET is the logarithm of the firm's total assets, PPEA the ratio of property, plant and equipment to total assets, RDA the ratio of research anddevelopment expenditures to total assets, CAPEXA the ratio of capital expenditures to total assets, FCF the earnings before interest, taxes, depreciation andamortization divided by total sales, DEBTA total debt divided by total assets, and SIGMA the standard error of the residuals obtained from the market model inwhich the firm's daily returns are regressed on the daily returns of Taiwan Stock Exchange Index. The change of firm age (FAGE) is not included because it is equalto one for all firm-year observations. All regressions include six year-dummies, representing 2003–2008 with omitted year being 2002, to filter the macro-economic shocks and three dummies to capture the effect of missing values in ΔRDA, ΔCAPEXA and ΔSIGMA. There are ten firms having incomplete data forcalculating 2009's Tobin's q so that the sample is 477 firms with 3329 observations. Numbers in parentheses are robust standard errors clustered at the firm level.⁎⁎⁎, ⁎⁎, and ⁎ indicate statistical significance at the 1%, 5%, and 10% levels respectively.


changes in shares outstanding and considering the individual incentive of managers to change their stake in the firm, managershare sales or purchases aimed at moving ownership toward the optimal level increase firm value and the discretionary changesof their own shares are detrimental to firm value. Our results are robust to different measures of ownership changes.

Previous studies, such as Zhou (2001) and Coles, Lemmon, and Meschke (2006), have criticized that because most changes inmanagerial ownership are small and lack time variations, caution should be exercised in the limited power of using the fixedeffects panel data model. Thus, Fahlenbrach and Stulz (2009) examined the relation between managerial ownership and firmvalue by focusing on changes of ownership larger than 2.5% in absolute value. To consider the relative stability of ownership overtime and check the robustness of the results shown in Table 5, this work examines the subsamples of firms that have largervariations in ownership over nine years of the sample period. The results reported in Table 6 are for firms with the coefficient ofvariation of ownership greater than 0.15 (291 firms) and 0.3 (113 firms). Using another coefficient of variation (0.1 or 0.2) as thethreshold produces similar results. For either case, the relations between changes in firm value and the components of ΔSit andΔSMit summarized in Table 5 are preserved. The positive effect of ownership adjustments toward the optimal level from eitherside of optimal ownership on changes in firm value still significantly appear. Despite somewhat different significance levels in thetwo subsamples, the negative effect of discretionary ownership adjustments on changes in firm value also shows up. The findingsin this study on the ownership-firm value relationship hold, irrespective of variations in managerial ownership.

5. Conclusion

This paper examines how managers adjust their ownership in response to the deviations from optimal ownership, andanalyzes the effect of adjustments in managerial ownership on changes in firm value. We focus on different value effects from twoownership adjustment components, namely, adjustments to remove deviations from optimal ownership and discretionaryadjustments. Although the answers to these questions are helpful to reconcile debates about the effect of managerial ownershipon firm value, previous studies provide little evidence. This study develops an integrated empirical model to incorporate these

Table 6The effect of changes in managerial ownership on changes in firm value for subsamples with large variations of ownership.

Coefficient of variation of ownership>0.15 Coefficient of variation of ownership>0.3



(ΔSit)opt-neg −0.289 (0.148)⁎⁎ −0.360 (0.208)⁎

(ΔSit)opt-pos 0.205 (0.074)⁎⁎⁎ 0.110 (0.060)⁎

(ΔSit)disc-neg 0.071 (0.038)⁎ 0.036 (0.055)(ΔSit)disc-pos −0.094 (0.060) −0.118 (0.066)⁎

(ΔSMit)opt-neg −0.177 (0.095)⁎ −0.217 (0.122)⁎

(ΔSMit)opt-pos 0.245 (0.089)⁎⁎⁎ 0.141 (0.075)⁎

(ΔSMit)disc-neg 0.072 (0.036)⁎⁎ 0.057 (0.060)(ΔSMit)disc-pos −0.030 (0.041) −0.121 (0.060)⁎⁎

ΔSit−ΔSMit −0.030 (0.059) −0.055 (0.056)ΔlnASSET −0.166 (0.063)⁎⁎⁎ −0.213 (0.072)⁎⁎⁎ −0.034 (0.068) −0.070 (0.081)ΔPPEA 0.304 (0.345) 0.328 (0.337) 0.313 (0.327) 0.333 (0.316)ΔRDA −0.234 (1.691) −0.202 (1.683) 1.947 (3.165) 2.140 (3.201)ΔCAPEXA 0.776 (1.146) 0.759 (1.138) 3.487 (1.934)⁎ 3.450 (1.922)⁎

ΔFCF 0.205 (0.192) 0.325 (0.212) −0.001 (0.005) 0.001 (0.005)ΔDEBTA 0.220 (0.145) 0.266 (0.160)⁎ 0.154 (0.174) 0.145 (0.160)ΔSIGMA −3.754 (1.575)⁎⁎ −3.869 (1.578)⁎⁎ 0.975 (3.184) −0.637 (2.648)Constant and year dummies yes yes yes yesAdjusted R2 0.321 0.321 0.350 0.348F-statistic for the model 34.97 ⁎⁎⁎ 32.78 ⁎⁎⁎ 12.71 ⁎⁎⁎ 12.67 ⁎⁎⁎

Number of observations 2034 2034 790 790Number of firms 291 291 113 113

Notes: This table reports the estimates of Eqs. (6a) and (6b) for the sample of firms having a large variation of ownership during the sample period. Thedependent variable is the changes in Tobin's q from year t to year t+1. Tobin's q is measured by the sum of the market value of common equity and the bookvalue of total debt divided by the book value of total assets. ΔSit is the changes in the logistically transformed managerial ownership. ΔSMit is the portion of ΔSitcaused by changes in the number of shares held by managers. The components of ownership adjustments are obtained according to Eqs. (3), (4), and (5). Thesubscript opt represents the adjustments toward the optimal level, disc represents the discretionary adjustments, -neg is for reductions in ownership, and -pos isfor increases in ownership. For other explanatory (control) variables, Δ denotes the changes from year t–1 to year t. lnASSET is the logarithm of the firm's totalassets, PPEA the ratio of property, plant and equipment to total assets, RDA the ratio of research and development expenditures to total assets, CAPEXA the ratio ofcapital expenditures to total assets, FCF the earnings before interest, taxes, depreciation and amortization divided by total sales, DEBTA total debt divided by totalassets, and SIGMA the standard error of the residuals obtained from the market model in which the firm's daily returns are regressed on the daily returns ofTaiwan Stock Exchange Index. The change of firm age (FAGE) is not included because it is equal to one for all firm-year observations. All regressions include sixyear-dummies, representing 2003–2008 with omitted year being 2002, to filter the macro-economic shocks and three dummies to capture the effect of missingvalues in ΔRDA, ΔCAPEXA and ΔSIGMA. There are 5 firms and 1 firm having incomplete data for calculating 2009's Tobin's q in two groups of firms respectively sothat the sample is 291 firms with 2034 observations and 113 firms with 790 observations. Numbers in parentheses are robust standard errors clustered at the firmlevel. ⁎⁎⁎, ⁎⁎, and ⁎ indicate statistical significance at the 1%, 5%, and 10% levels respectively.


issues, and constructs a panel data set from Taiwanese non-financial listed companies during 2000–2008 to test relatedhypotheses.

By employing the instrumental-variables estimation for the panel data model to examine ownership adjustments and performcertain related statistical tests, the empirical results show significant increases in managerial ownership when it is below theoptimal level, but decreases in ownership for above-optimal deviations are not significant. This asymmetric adjustment patternstill significantly appears when ownership deviations are normalized by firm size. The evidence supports our hypothesis thatmanagers attempt to maintain their relative controlling advantage in the process of ownership adjustments subsequent to thedeviations from optimal ownership.

The most important finding is that ownership adjustments caused by deviations from the optimal level, either increasing forbelow-optimal deviations or decreasing for above-optimal deviations, significantly raise Tobin's q of the firm. Irrespective of thedirections of changes in ownership, the market reacts positively to changes in managerial ownership toward the optimal level. Incontrast to the adjustments based on ownership deviations, both increases and decreases in discretionary ownership changes arefound to significantly lower firm value. These results are robust to a different measurement of changes in ownership suggested byHelwege et al. (2007), who emphasized ownership changes caused by changes in the number of shares held by managers. Finally,although the lack of time variations in ownership level can be an impediment to the fixed-effect approach, our findings on theeffect of changes in managerial ownership on changes in firm value are robust to subsamples of firms with larger variations ofownership over time. In sum, this study presents an empirical framework for better analyzing the relations among adjustments inmanagerial ownership, optimal ownership, and changes in firm value and provides strong evidence to reconcile different viewsproposed by previous studies.

Acknowledgements

This study is financially supported by the Taiwan National Science Council (NSC-99-2410-H-008-071-MY2). I would like tothank anonymous referees and the editor for valuable comments and suggestions on the early manuscript.

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adjustments in managerial ownership and changes in firm value

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