Corporate Governance and Risk-Taking in Pension Plans: Evidence from Defined Benefit Asset Allocations
Hieu V. Phan and Shantaram P. Hegde*
∗
Phan,
[email protected], School of Business, University of Connecticut, 2100 Hillside Road, Storrs, CT
06269; Hegde,
[email protected], School of Business, University of Connecticut, 2100 Hillside Road, Storrs, CT 06269. We are especially grateful to an anonymous referee, whose comments on the paper substantially improved the exposition and analyses. We also thank Assaf Eisdorfer, Carmelo Giaccotto, Joseph Golec, John Harding, Robert Kieschnick, Jung-Min Kim, Choonsik Lee, Alfred Liu, Paul Malatesta (the editor), Ronald Masulis, and seminar and conference participants at the 2011 Financial Management Association International Annual Meetings and the Doctoral Student Consortium, India Finance Conference 2011, Pace University, Salisbury University, and University of the Pacific. All remaining errors are ours.
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Electronic copy available at: http://ssrn.com/abstract=2009943
Corporate Governance and Risk-Taking in Pension Plans: Evidence from Defined Benefit Asset Allocations
Abstract Based on theoretical advice and empirical evidence suggesting that risk-taking in asset allocation enhances pension returns, we evaluate empirically whether good corporate governance leads to a larger allocation of pension assets to risky securities as compared to safe investments. Our findings suggest that firms with good external and internal corporate governance take more risk by investing heavily in equities and allocating a smaller share of the plan assets to cash, government debt, and insurance company accounts. The main underlying mechanisms appear to be higher investment returns and better pension funding status associated with higher equity and lower safe asset allocations. I. Introduction Corporate governance plays an important role in corporate business operation and performance. Prior research documents that good corporate governance can reduce default risk by monitoring managerial performance, mitigating agency costs, and reducing information asymmetry between a firm and its lenders, resulting in lower cost of debt (Ashbaugh-Skaife, Collins, and LaFond (2006), Bhojraj and Sengupta (2003), Cremers, Nair, and Wei (2007), Klock, Mansi, and Maxwell (2005)). In addition, good corporate governance can mitigate the corporate overinvestment problem that triggers higher cost of equity (Albuquerque and Wang (2008), Chen, Chen, and Wei (2011)). The literature also documents evidence that good corporate governance is associated with better operating performance (Core, Guay, and Rusticus (2006)) and higher abnormal returns (Gompers, Ishii, and Metrick (2003), Masulis, Wang, and 3
Electronic copy available at: http://ssrn.com/abstract=2009943
Xie (2007)). Examining the link between corporate governance and asset values, Dittmar and Marht-Smith (2007) document that cash holdings of well-governed firms are valued higher than those of poorly-governed firms and they suggest that corporate governance impacts the operating and investing decisions more than the financing decision. While good corporate governance tends to hinder managerial discretion, it puts pressure on managers to take more risk in making business investment decisions (John, Litov, and Yeung (2008); Laeven and Levine (2008)). Defined benefit (DB) plan is one of the most important private retirement schemes in corporate America. A report by the Investment Company Institute (2010) reveals that the total assets held by private DB pension funds were valued at $2.1 trillion, accounting for 21 percent of employer-sponsored plan assets in 2009. Further, defined benefit pension plan assets account for a significant part of the book value of assets recorded on the balance sheet and of the market value of the sponsoring firm’s equity (Shivdasani and Stefanescu (2010)). Given their large values and their implications to shareholders’ wealth, pension assets are simply too big to be ignored by large shareholders of the firm or the market. Although pension regulations require firms to establish separate trusts to manage and invest DB pension plan assets, these pension plans are owned by the sponsoring corporations and the plan asset allocations are made under the influence of, if not the direction and control of, the plan sponsors (see Bergstresser, Desai, and Rauh (2006), Frank (2002), Rauh (2009), among others). Tower Watson Company reports that in the U.S. approximately 45% of DB plan assets of Fortune 1000 companies were invested in equities and about 40% were allocated to cash and debt the year end of 2009. Depending on the firm and plan characteristics as well as the market environment, firms may have different incentives in investing pension assets, namely, either risk-taking by allocating a larger share of plan assets to risky asset classes (e.g., equity) or risk management by investing heavily in safe 4
asset classes (e.g., cash, government debt, and guaranteed insurance contracts). Indeed, survey results reveal that boards of directors, trustees and senior pension executives look for long-term investment strategies to ensure full funding of corporate pension obligations, and that active equity investment (including some element of strategic market timing) is key to improving funding status of pension plans (Pyramis Global Advisors (2010)). Rauh (2009) finds evidence that firms with well-funded pension plans and strong credit ratings shift more pension assets to equity, whereas firms with underfunded pension plans and weak credit ratings allocate a greater share of pension assets to government debt and cash. Asset allocation of DB plans provides a unique setting to investigate the relation between corporate governance and risk-taking in pension plans. Standard models of consumption and portfolio choice for long-term investors advise that pension funds should behave more aggressively than a one-period investor and invest more in risky assets (see, for example, Campbell and Viceira (2002)). Widely accepted empirical evidence indicates that for long investment horizons excess returns as well as risk- or benchmark-adjusted returns on equities outperform those on corporate and government bonds on average (see Campbell, Chan, and Viceira (2003), and Dyck and Pomorski (2011)). Against this backdrop, in this paper we examine the impact on pension asset allocations of corporate governance mechanisms that measure investor protection by blockholder ownership or institutional ownership and antitakeover provisions. Given their large capital commitment, blockholders or institutional investors have an incentive to monitor and influence management’s actions (see Denis, Denis, and Sarin (1997), Gillian and Starks (2000), Gompers and Metrick (2001), among others). On the other hand, firms with low anti-takeover provisions subject the management to the scrutiny and discipline of the market for corporate control, thus enhancing the interests of investors (e.g.,
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Gompers, Ishii, and Metrick (2003), Bebchuk, Cohen, and Ferrell (2005), Cremers and Nair (2005)). Together, these measures of corporate governance, representing internal (blockholder ownership) and external (anti-takeover provisions) monitoring, can put pressure on sponsors and pension trustees to take prudential risks in investing pension assets to benefit the employees as well as shareholders. We analyze the asset allocation of 467 DB plans of 329 unique firms over the 1990-2006 period and find evidence that higher allocations of plan assets to equities and smaller shares to cash, government debt, and insurance company accounts are characterized by higher investment returns, lower pension contributions, and overall better pension funding. More importantly, firms with good external corporate governance, classified on the basis of a sample firm’s rank in the number of anti-takeover provisions in comparison with the sample median, take more risk by allocating about 9% more of firm-level pension assets to risky assets (i.e., equities) than those with poor external corporate governance. The finding of a positive relation between good external governance and risk-taking in pension asset allocation holds at both the plan and firm levels after controlling for several other factors that are documented in the literature to have power in explaining pension asset allocation. The main underlying mechanisms appear to be higher investment returns and better pension funding status associated with higher equity and lower safe asset allocations. In addition, we also find weak evidence that higher ownership concentration is associated with more risk-taking in pension asset allocation. The governanceasset allocation relation is robust to corrections for potential endogeneity bias induced by corporate governance and survives several other robustness checks. Our research makes several contributions to the literature. First, we provide a novel test of the relationship between corporate governance and corporate risk-taking in pension asset 6
allocation. Second, we show that through its impact on pension plan asset allocation good corporate governance influences firm behavior more broadly than previously thought. Third, pension contributions could drain the DB plan sponsors’ liquid resources that would otherwise be used to grow their businesses, especially for financially constrained firms. Complementary to the evidence of a positive relation between investor protection and risk taking in real investment documented by John, Litov, and Yeung (2008), our findings suggest an alternative channel through which better corporate governance may improve the investment policy on defined benefit pension plans: by altering the structure of pension assets allocations toward risky assets firms can earn higher returns on pension assets, improve the pension funding status, and lower pension contribution. The resulting savings can be invested in other corporate growth programs for the benefit of shareholders. Our research is close to that of Cocco and Volpin (2007) who examine the agency hypothesis that sponsoring companies with corporate (inside) directors serving as plan trustees will invest more of pension assets in equities and make lower pension contributions. They use the proportion of executive directors of the sponsoring company on the board of trustees of the pension plan as a measure of governance quality. Based on a sample of 90 firms with defined benefit plans in the United Kingdom over 2002-2003, they find support for the agency hypothesis and conclude that insider trustees act in the interests of shareholders of the sponsor, rather than those of pension beneficiaries. In contrast, our focus is on the mitigating effects of shareholder rights on curbing the excessive risk avoidance behavior of sponsoring firms in the U.S. The governance measures we rely on are not only different from the proportion of insider trustees used by Cocco and Volpin, but are also broader in scope as they encompass both internal governance proxied by blockholder ownership and external governance represented by the 7
number of anti-takeover provisions adopted by sponsoring firms. Our findings are different from those of Cocco and Volpin because our results show that not only shareholders of sponsoring firms but also pension plan beneficiaries gain when good internal and external governance structures lead to more (less) allocation to equity (safe assets). The employees win because of enhanced returns on pension assets and the improved funding status of the plan and the shareholders of the sponsoring firms gain through lower pension contributions and reduced risk of pension shortfalls. The rest of the paper proceeds as follows. Section II reviews the related literature and develops the testable hypothesis and Section III describes the data and descriptive statistics. Section IV discusses models, presents empirical results, and provides discussions. Section V concludes the paper. II. Related Literature and the Testable Hypotheses A growing body of literature has documented a close relationship between corporate governance and risk-taking in capital investment policy. Using volatility of the country-adjusted firm-level cash flows over assets as a proxy for the “riskiness” of corporate investment, John, Litov, and Yeung (2008) show that those firms that are subject to market scrutiny and discipline pursue a less conservative investment policy. However, they do not find evidence of a significant relation between risk-taking and high concentration of ownership. Alternatively, Laeven and Levine (2008) examine risk-taking by large banks in 48 countries and use the z-scores, which measure the distance from insolvency, volatility of asset returns, volatility of equity returns, volatility of earnings, and leverage as alternate proxies for risk-taking. They report that banks that have large owners with substantial cash flow rights take more risk, but the relationship
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between cash-flow rights and risk is weaker in economies with stronger shareholder protection laws.1 It is noteworthy that the main challenge to empirical research on the relation between corporate governance and risk-taking is to determine the precise risk level or risk choice embedded in real investment because this information is rarely available. Proxies for risk-taking, such as stock return volatility or cash flow volatility, could be noisy measures. For instance, return volatility could be driven by many factors beyond the control of the firm whereas cash flow volatility could be partially driven by cash flow seasonality or earnings smoothing. Hence executing the proxy approach without care could introduce noise into the estimation process and bias the parameter estimates. Cocco and Volpin (2007) argue that in the U.S. the pension trust is an asset of the corporation and the directors of the sponsoring company usually make decisions on how to invest the plan’s assets. Rauh (2009) observes that the firm’s board of directors and relevant committees are responsible for setting the pension fund investment policy and appointing or hiring investment managers to execute it. Bergstresser, Desai, and Rauh (2006) suggest even a more direct involvement of corporate managers in the pension asset allocation process. Specifically, they provide evidence that corporate managers manipulate earnings by using higher assumed rates of return on pension assets in anticipation of important corporate events, such as mergers and acquisitions, or for managerial benefits, such as stock options exercise. They note that managers justify the increase in assumed rates of return by allocating a larger share of DB plans to equity. In addition, Logue and Rader (1998) argue that investment managers of DB 1
For more discussion on the possible mitigating effects of internal and external corporate governance on agency
problems, refer to Amihud and Lev (1981), Bebchuk, Cohen, and Ferrell (2005), Cremers and Nair (2005), Denis, Denis, and Sarin (1997), Gompers, Ishii, and Metrick (2003), Hirshleifer and Thakor (1992), Jensen and Ruback (1983), Mørck, Wolfenzon, and Yeung (2005), and Stulz (2005), among others.
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plans may find that meeting the requests of the corporate sponsor is more personally rewarding. Ultimately, it is the DB plan sponsor that is responsible for the plan asset allocation decision (Frank (2002)) as well as making up any pension deficit. We exploit the pension asset allocation of DB plans to investigate the relation between corporate governance and risk-taking. The liabilities of a DB plan are fixed obligations which resemble regular corporate debt in that the limited liability provision protects shareholders from having to transfer non-corporate assets to compensate plan beneficiaries in case of bankruptcy (Rauh (2006)). Given the Pension Benefits Guaranty Corporation (PBGC)’s insurance, the sponsor of a DB plan holds a put option on pension assets with a strike price equal to the pension obligation (Sharpe (1976), Treynor (1977)). The value of the put option increases in the volatility of the underlying (pension plan) asset, which implies moral hazard incentives for the firm to underfund pension plans and invest the plan assets in risky securities, such as equities. Consistent with this risk-taking argument, Cocco and Volpin (2007) report evidence that UK pension plans of more leveraged firms with a higher proportion of insider-trustees invest a larger proportion of the pension plan assets in riskier securities, i.e. equities, and the presence of insider-trustees allows firms to make lower contributions to the DB plans. Since the DB plan sponsors are willing to make riskier investment, they expect to earn higher returns which in turn help lower future pension contributions. Theoretically, under certain conditions, firms can maximize shareholder value if they allocate all the DB plan assets to bonds with duration equal to the term of pension liabilities. DB plan sponsors can earn tax arbitrage profit if they issue bonds and use the proceeds to make contributions to DB pension plans, whose assets are invested in bonds (see Black (1980), Tepper (1981), Bodie et al. (1987), Frank (2002), Cocco and Volpin (2007)). On the other hand, the 10
moral hazard mentioned above to underfund pensions could be mitigated since the Employee Income Security Act (ERISA) of 1974 and its later versions stipulate a mandatory pension contribution regime designed to ensure full funding of DB pension plans. Moreover, even if firms could avoid bankruptcy and end up with poor pension investment performance, they still need to fund the pension plan with liquid resources which depress non-pension corporate investment (Rauh (2006)). These arguments suggest that risk management in pension plan asset allocation serves the interests of the DB plan sponsors, particularly those experiencing financial constraints or financial distress. Indeed, Rauh (2009) finds evidence that U.S. firms with underfunded DB plans and weak credit ratings allocate a larger share of pension assets to government debt and cash. In summary, the arguments outlined above identify incentives of the sponsors for risktaking in increasing allocation to risky securities (such as the PBGC put option, earnings manipulation, among others) as well as for risk management (investing in safer asset classes) such as avoiding costly financial distress. However, they are less directly related to corporate governance. Against this backdrop, we focus on the effects of anti-takeover provisions and blockholder ownership of equity on pension asset allocation. The key advice on strategic asset allocation provided by standard models of consumption and portfolio choice for long-term investors, such as pension funds, emphasizes that they should behave more aggressively than a myopic (one-period) investor and tilt their portfolios to risky assets. Moreover, the optimal investment strategy for long-term horizons involves strategic asset allocation including an element of market-timing, not the passive buy-and-hold strategy (see, for example, Campbell and Viceira (2002)).
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Widely accepted empirical evidence indicates that for long investment horizons returns on equities outperform those on corporate and government bonds on average.2 Although equities are roughly three times more volatile than bonds, the Sharpe ratio is almost three and a half times as high for stocks as for bonds. In addition, survey results reveal that boards of directors, trustees and senior pension executives look for long-term investment strategies to ensure full funding of corporate pension obligations, emphasizing that active equity investment (including some element of strategic market timing) is key to improving funding status of pension plans. To illustrate, the vast majority of institutional investors believe that actively managed equity strategies compared to passive management is key to securing improved funding status of pension plans, according to a post-crisis survey conducted by Pyramis Global Advisors (2010), a unit of Fidelity Investments, in 2009 of a representative sample of chief investment officers, treasurers, and executive directors at 427 corporate and public pension plans in 12 countries (including 142 corporate and 75 public U.S. pension plans) who cumulatively manage in excess of $1 trillion in assets. Shivdasani and Stefanescu (2010) estimate that, on average, defined benefits pension plan assets are 16.4% of the book value of assets recorded on the balance sheet and represent 62% of the market value of the sponsoring firm’s equity over the 1991-2003 period. Given their large values and their implications to shareholder wealth, pension assets are simply too big to be ignored by large shareholders of the firm or the market.3 The forgoing review of theoretical optimal investment advice, empirical evidence on average stock, bond and pension fund returns, and pension industry survey results suggest that investors are aware that a prudential risk-taking asset allocation strategy has the power to 2
For example, Campbell, Chan, and Viceira (2003) report that over 1952-1999 U.S. stocks earned an excess return
(over 90-day T-bills) of 7.72% per year compared to 1.08% for corporate bonds with five-years to maturity. 3
We thank an anonymous referee for suggestions to strengthen our arguments for hypotheses development.
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enhance the financial strength of a plan (i.e., better pension funding status) by generating higher average returns on pension investments, which results in lower average pension contributions. Therefore, investors facing fewer restrictions on their monitoring power exert pressure on managers to increase pension allocations to risky assets, without exposing firms to costly financial distress. By promoting judicious risk-taking, good governance results in higher average returns on investments, which lower pension contributions required to fund a given pension liability and improve the pension funding status. Positive pension funding status is analogous to an equity cushion held by the fund beneficiaries against adverse shocks to pension assets. These benefits decrease the likelihood that a firm would be forced to give up profitable capital investment (Rauh (2006)). Furthermore, by lowering the cash drains required to ensure adequate funding of pension plans they decrease the probability of default on a firm’s regular nonpension debt and of incurring costs of financial distress. These arguments lead us to hypothesize that, all else equal, DB plan sponsors with good external corporate governance would invest heavily in risky securities such as equities due to strong investor monitoring, whereas those with poor external governance allocate a greater share of pension assets to safer asset classes such as government debt, cash, and insurance accounts. However, the effect of internal corporate governance, represented by either blockholder or institutional ownership, on pension asset allocation is ambiguous ex ante because private benefits of control and lack of diversification of dominant owners might motivate them to favor a conservative pension investment policy. III. Data Description Our source of data about DB pension plans is Schedule B (DB pension plan) and Schedule H (plan asset allocation) of Form 5500 that firms file with the Internal Revenue Service (IRS) annually. Form 5500 reports on individual plans by the plan sponsor’s CUSIP number
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prior to 1998, but reports by Employer Identification Number (EIN) for later years, therefore we aggregate plan-level data to firm-level using CUSIP numbers for the 1990-1997 period and EIN for the later years. Information in Schedule H provides a breakdown of asset allocations into standardized categories, however the plan sponsors may classify assets as belonging to opaque categories whose risks are ambiguous. For example, while plan sponsors can classify assets to stocks or government bonds, they can also assign those assets to common or collective trusts, pooled separate accounts, master trusts, 103-112 investment entities, and registered investment companies. It is infeasible to manually check for the detailed asset classification of these opaque categories of individual plan sponsors given the large sample size. Therefore, we follow Rauh (2009) in restricting our main analysis to plans for which the value of the opaque asset classes is less than 5% of the total pension plan asset value (but we relax this restriction in our robustness tests). We investigate the relation between corporate governance and pension asset allocation at both the plan- and firm-levels, hence we match the plan- and firm-level pension data with Compustat accounting data based on the CUSIP number or EIN as appropriate. For those plans and firms that cannot be matched with Compustat data based on EIN, we manually match by their names, using the pension plan sponsor’s name in Form 5500 and the company name in Compustat. Since matching pension plan data with Compustat accounting data is a challenging process, we acknowledge that our matching process is not perfect for the 1998-2006 subperiod because a firm’s subsidiary may have its own EIN number and report its pension plans on a separate Form 5500. If a subsidiary’s name (i.e., sponsor’s name) is not identical to its parent’s name, it is possible that the subsidiary’s pension data is not aggregated to its parent firm’s data,
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resulting in an underestimation of pension assets, liabilities, and other relevant data for some firms in our sample. Anti-takeover provisions (ATPs) are an important measure of investor protection since the market for corporate control is viewed as a strong external force to scrutinize and discipline management. More (less) ATPs mean poorer (better) corporate governance. Gompers, Ishii, and Metrick (2003) construct a corporate governance index, named G-index, based on a total of 24 ATPs adopted by firms for a sample of about 1500 publicly listed large firms over the 1990-2006 period (the G-index is available at Andrew Metrick’s website). G-index has been used widely in financial economics and corporate governance literature so we use this index as the primary proxy for external corporate governance in our research. The G-index is assembled and reported about every two years during the 1990-2006 period, so in a year during our research period when the G-index is not available we assume that the index value is unchanged from the previous year. Bebchuk, Cohen, and Ferrell (2009) report that among the anti-takeover provisions that are used to construct the G-index, six provisions that include staggered boards, limits to shareholder bylaw amendments, supermajority requirements for mergers, supermajority requirements for charter amendments, poison pills, and golden parachutes have more explanatory power about managerial entrenchment than the remaining provisions so they propose the entrenchment index (E-index) based on these six provisions. We use the E-index as an alternate proxy for external corporate governance in our study. The Eindex is available for the period from 1990-2008 at Lucian Bebchuk’s website. Large shareholders have incentives to monitor management and take steps to protect their own investments in the face of potential managerial agency conflicts, therefore we follow
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Dittmar and Mahrt-Smith (2006) in using either a firm’s aggregated block ownership or its aggregated institutional ownership as a proxy for internal corporate governance. Blockholder and institutional ownership are aggregated for each firm in a given year from the Thomson ONE Banker database. We start with the total sample of 257,868 plan-year observations of 35,120 individual DB plans belonging to 24,010 unique firms reported in Form 5500 over the 1990-2006 period. By restricting DB plans to those that have investment in opaque assets less than 5% of the total plan assets, the sample size is reduced to 88,854 plan-year observations of 22,563 unique plans belonging to 17,730 unique firms. We label this sample as all-DB plans sample. After matching the all-DB plans sample with accounting data in Compustat, G-index, E-index, and blockholder ownership, our final sample has 1,588 plan-year observations of 467 independent plans which belong to 329 unique firms and distribute almost evenly over the sample period (therefore our sample is an unbalanced panel). More than half of these firms are concentrated in manufacturing industries and most of the remaining firms come from mining, transportation and communications, and finance and insurance industries. We use the final sample in our analysis and label this sample as the analysis sample. We present summary statistics of the all-DB plans sample and our analysis DB plan sample in Panels A and B, and firm-level data which is aggregated from the analysis DB plan sample in Panel C of Table 1, respectively. Table 1 shows that, at the plan level, the pension assets and current pension liabilities of our analysis sample (reported in Panel B) are about four times of those of the all-DB sample (reported in Pane A) on average, which is appropriate since the restricted samples, by construction, include Compustat firms which are usually larger than those not included in Compustat. In addition, the average DB plan in the analysis sample has 16
higher funding status than that of the all-DB plan sample. With respect to pension asset allocation, the analysis sample has higher average equity ratio in relation to the all-DB plan sample (0.326 vs. 0.29), significantly lower cash and government debt ratio (0.077 vs. 0.27), lower insurance company accounts ratio (0.153 vs. 0.18), and significantly higher other investment ratio (0.443 vs. 0.27). It is noteworthy that in insurance company account arrangements, the insurance company provides an annuity that pays the pension benefits and keeps plan assets in the general pool of funds. Rauh (2009) suggests that this arrangement is very safe for the plan sponsor since the risks are shifted to the insurance company, which invests only in high-grade securities. For this reason, we group cash, government bond, and insurance accounts together into a safe asset class in our later analysis and label it as cash-debt-insurance, but our findings still hold if we exclude insurance accounts from the safe asset class. Other investments may include corporate debts, real estate investment, investment in mutual funds, and investment in opaque assets, etc. that have not been accounted for in equity, cash, government debt, and insurance company accounts calculation. ___________________________ Insert table 1 about here ____________________________ A comparison of asset allocation between the two plan-level samples suggests that plan sponsors in our analysis sample tend to take more risk by allocating a larger share of the pension assets to equity while investing less in safe asset classes than their counterparts in the all-DB sample. The aggressive pension investment policy of the analysis sample is associated with significantly higher median surplus funding (funding status of 0.22 vs. 0.15). The median pension investment returns (defined as investment income divided by beginning-of-year pension assets) are equal at 8% for both samples, whereas the median contribution ratio is 2% of 17
beginning-of-year assets for the analysis sample as compared with 4% for the all-DB sample. The firm-level summary statistics (based on the analysis sample) presented in Panel C of Table 1 show that the median equity ratio is even higher than that at the plan-level. Further, the median contribution ratio is lower (1.3% vs. 2%) and the median pension investment returns are slightly higher (8.3% vs. 8%) at the firm-level. For those firms with credit ratings, the average credit rating is 8.07, which is equivalent to BBB+. These firms have large size (the average operating asset value is 8 billion dollars). IV. Empirical Results In this section, we discuss empirical models that examine the effects of corporate governance on pension asset allocation and provide and discuss the estimation results. A. Univariate Analysis We start our analyses with univariate tests to assess the aggregate (base level) effects of external and internal corporate governance on pension asset allocation at the plan and firm levels and the implication of the effects on pension investment returns, contributions, and pension funding status. We conduct t-tests (Wilcoxon rank sum tests) to test the null hypothesis that the mean (median) effects on the above three measures of fund performance are not different between two subgroups that differ in external (internal) corporate governance ranking and asset allocation strategies. Table 2 reports the univariate analyses of the relation between asset allocation and fund performance. Low equity subsample includes those firm-year observations that have the ratio of assets allocated to equity less than the respective contemporaneous sample median. The remaining firm-year observations are classified as high equity. In Panel A, of the total of 1,114 18
firm-year observations, 551 data points belong to the conservative asset allocation policy (i.e., low equity asset allocation - Low EAA), while the remaining 563 observations fall under the aggressive allocation strategy (High EAA). The aggressive (risk-taking) allocation yields an average return on pension assets of 10.77% per annum as compared with a mean of 7.41% on the conservative policy. Moreover, higher investment returns generated by the High EAA result in a mean pension contribution ratio of 4.18% in relation to 6.81% of the Low EAA policy. Furthermore, aggressive equity allocation produces an average funding surplus of 34.51% of current pension liabilities as against 17.65% associate with the conservative equity investments. ___________________________ Insert table 2 about here ____________________________ We repeat the above analyses by further (independently) sorting the sample into two asset allocation groups based on safe assets: low safe assets (Low SAA, which includes those firmyear observations that have the ratio of assets allocated to cash-debt-insurance contracts less than the respective contemporaneous sample median) and high safe investments (High SAA, which covers the remaining firm-year data points). Low SAA subsample has 549 observations, which appears to overlap the High EAA group with 563 observations. Similarly, the High SAA subsample with 565 observations seems to be highly correlated with the Low EAA group. The aggressive asset allocation represented by the Low SAA subsample has average investment returns, contribution ratio and pension funding ratio of 11.23%, 4.33% and 37.22%, respectively. In sharp contrast, the conservative investment policy underlying the High SAA group has average investment returns, contribution ratio, and pension funding ratio of 6.99%, 6.39%, and 16.22%, respectively. The t-tests as well as the Wilcoxon rank sum tests indicate that the mean and median differences in the three measures of fund performance between the aggressive and 19
conservative investment allocation strategies are highly significant. Thus, the aggregate results demonstrate that aggressive portfolio allocations have delivered substantially better average funding of defined benefit pension plans through higher average investment returns and lower average pension contributions as compared to conservative asset allocation over our sample period 1990-2006. We assume that the empirical relation between pension asset allocation and fund performance is a long-term trend that predates our sample period. Our basic argument is that investors are aware of this evidence on the benefits of aggressive pension fund investment policy in terms of higher average pension investment returns and lower average pension contributions resulting in better average funding of defined benefit pension plans and exert pressure on managers through governance mechanisms to choose judicious risk-taking in asset allocations. To explore this argument at the aggregate level, we sort the sample into two corporate governance groups: good governance (GOV) and poor GOV. The good GOV subsample consists of firm-year observations that have G-index or E-index less than or equal to the respective contemporaneous sample median (for external corporate governance), or blockholder ownership equal to or greater than the respective contemporaneous sample median (for internal corporate governance).4 The remaining firm-year observations are included in the poor governance group. In Panel C, average equity allocation between the good and poor governance groups varies between 38% and 43% across the three measures of governance and the difference in EAA is insignificant in two out of three tests. The exception is the case of the E-index where the difference in mean equity ratio is about 4.5% and statistically significant. Similarly, the
4
We use 5% as the floor limit of block ownership because this percentage allows a blockholder to appoint
director(s) to the board of directors.
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difference in allocations to safe assets between the good and poor governance subsamples is typically insignificant, again with one exception - firms with larger blockholder ownership tend to allocate a larger average share of pension assets to cash-debt-insurance contracts (17.56%) as compared with 13.6% for the poor governance group. In summary, the univariate evidence on the effects of governance on pension asset allocations seems weak. Central to our argument is the idea that firms with good governance invest heavily in risky assets over safe assets to exploit the higher average investment returns and lower average pension contributions required to assure adequate funding of pension obligations. This argument underscores that pension investment returns and pension contributions are two mechanisms underlying the governance-pension asset allocation relation. We test this hypothesis by further sorting EAA into High and Low EAA, and SAA into High and Low SAA (independent double sorts) following the partitioning procedures employed in Panels A and B. In other words, we double-sort governance and asset allocations and examine the effects of good governance-high EAA vs. poor governance-low EAA (good governance-low SAA vs. poor governance-high SAA) on the three measures of fund performance and report the results in Panels D (Panel E). The sample size drops roughly by half to about 500 to 600 observations. Consistent with our conjecture, the results in Panel D show that firms with good governance and high equity allocation earn significantly higher investment returns (from 2.7% to 3.7%), and make lower pension contributions (0.67% and 2.05%) than firms with poor governance and low equity allocation. The combination of good governance and high EAA is associated with significantly higher pension funding status varying from 7.47% to 17.27% of pension obligations. The results in Panel E show a similar pattern with respect to the joint effects of good governance and low allocation to safe assets. We expect firms with good governance to allocate
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a smaller share of pension assets to less risky securities, and we find that the intersection of Good Governance-Low SAA earns significantly higher average investment returns and pension funding ratios than the combination of Poor Governance-High SAA. The corresponding results with respect to pension contributions follow the same trend but are statistically weaker. Taken together, the univariate analyses indicate that risk-taking in pension asset allocations as measured by higher equity and lower cash-debt-insurance account investments is rewarded by significantly higher average investment returns, lower average pension contributions, and better average pension funding status. More importantly, the emerging big picture suggests that good governance enhances the benefits of risk-taking in terms of fund performance, whereas poor governance coupled with conservative investment policy is correlated with diminished benefits. B. Multivariate Analysis The above univariate results provide a general indication that good external corporate governance is associated with more risk taking but there are several other factors that can also explain risk- taking in pension asset allocation. We examine the relation between firm-level asset allocation and corporate governance while controlling for several other factors in a multivariate setting. 1. Empirical Specifications and Estimation Methods Our asset allocation baseline regression has the following form: (1)
Asset_class_ratioi,t = α + αt + β1EGOVi,t-1 + β2EGOVi,t-1*Funding_statusi,t-1 + β3IGOVi,t-1 + β4IGOVi,t-1*Funding_statusi,t-1 + β5Funding_statusi,t-1 + γXi,t-1+ εi,t
22
We aggregate plan-level data to the firm-level and run the regression in equation (1). The dependent variable, asset class ratio, is either equity ratio, measured as the proportion of pension assets allocated to equity securities, or cash-debt-insurance ratio which is the proportion of the sum of cash, government debt, and insurance company account arrangements out of the total pension plan assets. X is a vector of other control variables. We are interested in the impact of corporate governance on pension plan asset allocation hence our test variables include external governance (EGOV) and internal governance (IGOV). We use the G-index (E-index) as a proxy for EGOV and the aggregated ownership of blockholders who hold at least 5% of the firm’s common shares as the proxy for IGOV. Since G-index (E-index) represents the number of antitakeover provisions adopted by a firm, it is not immediately clear how many provisions would represent the cutoff point between good and poor external governance. In line with the literature, we construct an external governance dummy variable (ED) that takes a value of one (i.e., good external governance) for those firm-year observations that have a G-index (E-index) value less than or equal to the respective contemporaneous sample median value, and zero otherwise (i.e., poor external governance). We construct an internal governance dummy variable (ID) that takes a value of one for those firm-year observations that have the aggregated block ownership equal to or greater than the respective contemporaneous sample median value, and zero otherwise. If good external governance and good internal corporate governance (i.e. high concentration of ownership) have positive impact on risk taking, we expect the coefficients on ED and ID to be positive (negative) and significant in equity ratio (cash-debt-insurance ratio) regressions. Following Rauh (2009) we control for funding status, the natural logarithm of pension assets, pension investment returns, firm’s credit ratings, Altman’s Z-score, the natural logarithm of corporate operating assets, non-pension cash flow ratio (NPC), NPC volatility, and pension 23
obligations, but additionally include pension contributions as control variables. All variables, except pension asset returns and pension contributions, are measured at the beginning of the pension plan year. Funding status is measured as the difference between pension plan assets and current liabilities divided by current liabilities. Following Rauh (2009) we further include interaction terms between ED and funding status and between ID and funding status as well. To better gauge the unconditional effect of the interacted variables, we demean the interacted variables that are non-indicators. The effects captured by the dummy variables represent the average effect on asset allocations (i.e., shift in the intercept) whereas the effects captured by the interaction terms show the marginal change in risk-taking as the funding status improves (i.e., change in the slope of the regression). Pension asset returns are measured as the total pension income from the main 5500 Form or Schedule H net of contributions and other noninvestment income divided by pension assets at the beginning of the year. Analogously, annual total pension contributions are scaled by beginning-of-year pension assets. As discussed earlier, fund managers have incentives to allocate a greater (lower) share of pension assets to risky securities (safe assets) to capture higher average investment returns, lower pension contributions and better funding status. Therefore, we expect equity (safe assets) allocations to be positively (negatively) correlated with pension investment returns and funding status but negatively (positively) correlated with pension contributions. Nonpension cash flow is defined as the sum of net income, depreciation and amortization, and pension expense.5 Credit ratings indicate the financial strength as well as the debt default 5
Pension expense is an accounting expense that is weakly related to cash demand whereas pension contribution
actually drains cash. Therefore we add pension expense back to cash flow to arrive at non-pension cash flow but include pension contributions as a separate control variable in the pension asset regressions. See Bergstresser, Desai, and Rauh (2006) and Rauh (2006) for further discussion.
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probability of a firm hence a firm with good credit ratings is in a better position to fulfill its pension obligations. Empirically, Rauh finds that firms with good credit ratings allocate more (less) pension assets to equity (cash-debt-insurance), which is consistent with the risk management perspective. We use the S&P long-term debt ratings as a proxy for the firm’s credit ratings, but convert them to scores (with lower scores indicating better credit ratings and vice versa) for statistical analysis, and expect the coefficient on credit ratings to be negative (positive) in equity (cash-debt-insurance) regressions.6 To account for the fact that many firms in Compustat database do not have credit ratings, we construct a dummy variable that takes a value of one for those firm-year observations that do not have credit ratings and zero otherwise. Finally, we include year dummies to control for time fixed effects. We employ panel random effects (RE) and pooled regressions to estimate equations (1), and use heteroskedascity-robust firm-clustered standard errors for statistical inference. Indeed, the Hausman tests (reported with the estimation results in the later part) support the consistency of our RE estimates.7 2. Multivariate Analysis Results and Discussions
6
We convert the entire S&P credit ratings into scores as follows: AAA=1, AA+ =2, AA=3, AA− =4, A+ =5, A=6,
A− =7, BBB+ =8, BBB=9, BBB− =10, BB+ =11, BB=12, BB− =13, B+ =14, B=15, B− =16, CCC+=17, CCC=18, CCC− =19, CC=20, C=21, and D=22. By construction lower score means better credit ratings. 7
To account for possible unobserved firm fixed effects, the panel fixed-effect (FE) estimation is the appropriate
method. However, when the variables on the right-hand side have little variation over time, like the G-index or Eindex in this paper, the FE estimates would be imprecise (Wooldridge (2002), p. 286). Nonetheless, we do try the fixed effect model and find the results consistent with our findings only when continuous variables of G-index and block ownership are used.
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Focusing on the impact of corporate governance on firm-level pension asset allocation, we report the regression results in Panels A and B of Table 3 (using either G-index or E-index as a proxy for external corporate governance, respectively). In both panels, columns (1)-(3) present equity regressions and columns (4)-(6) report cash-debt-insurance regression results. As all other regressors are calculated at the beginning of the plan year, Panels A and B use lagged values of pension returns, pension contributions, and funding status. Also, using the lagged pension contributions serves to mitigate concerns about a potentially endogenous regressor.8 We report only the RE model results in order to save space. All columns include ED and ID dummy variables, columns (2) and (5) include lagged pension contributions as a control variable, and columns (3) and (6) include interactions between governance dummy variables and funding status. The results in Panel A show that, in equity regression, the coefficients on ED are all positive (0.089-0.094) and significant at 5% level, suggesting that firms with good external corporate governance allocate a larger share of pension assets to equity. The coefficients on ID are also positive but insignificant. Further, none of the coefficients on the interaction terms are significant. On the other hand, the signs and significance of most of other control variables are consistent with those reported in the literature. The negative sign of the coefficients on credit ratings (ranging from -0.006 to -0.004) is expected, however the estimates are insignificant. In
8
Pension contributions comprise mandatory contributions imposed by pension laws and voluntary contributions
made by sponsors. When pension plans are underfunded, firms tend to make the minimum contributions required under pension regulations due to financial constraints faced by the sponsors. On the other hand, voluntary contributions are typically made when firms are in good financial condition. Rauh (2006) finds that mandatory contributions appear to be exogenous and pose little endogeneity concerns. When we replace total pension contributions with the mandatory component, our results remain qualitatively unchanged.
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addition, those firms that do not have credit ratings (as measured by Credit ratings dummy) tend to allocate a smaller share (about 13%) of pension assets to equity. ___________________________ Insert table 3 about here ____________________________ The results of the cash-debt-insurance regressions show that firms with good external corporate governance allocate a smaller share of their pension assets to safe classes since the coefficients on ED are all negative, range from -0.076 to -0.067, and highly significant. However, the coefficients on ID are not significant in any specification, implying no relation between internal governance and safe asset investment. The coefficients on credit ratings are positive as expected but again insignificant. Funding status enters the regression with negative sign as expected but it is only marginally significant in one out of three specifications. Moreover, it is noteworthy that the coefficients on lagged pension contributions are positive and highly significant. It indicates that firms that made 1% more pension contributions in the prior year tend to allocate about 0.27% more pension assets to safe securities. This result appears to reflect that less risk-taking is correlated with more pension contributions. Finally, the Hausman test does not reject the null hypothesis that the random effects (RE) model estimates are consistent (all the pvalues of the chi-squares statistics are above 10%), validating our use of RE models for regression estimation. In Panel B of Table 3 (using E-index in place of G-index as a proxy for external governance), the estimates of control variables have the signs, magnitudes, and significance qualitatively similar to those in Panel A and the tests statistics also validate the models used, so we suppress the estimates of control variables and model validity test statistics for brevity.
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Consistent with the earlier evidence, the coefficients on ED are positive, range from 0.091 to 0.097, and significant at 1% level in equity regression. The coefficients on ID are positive but insignificant. Further, governance variables are not significant in cash-debt-insurance regressions. In summary, the findings from the firm-level asset allocation regressions show that risktaking in pension asset allocations is positively correlated with pension investment returns and funding status, whereas allocations to safe assets are associated with increased pension contributions. More importantly, external governance has a significant impact on risk-taking of the DB pension plan sponsors, and firms with good external governance take more risk in their pension investment activities as evidenced by larger (smaller) share of pension assets allocated to equity (cash-debt-insurance) investment. C. Endogeneity Correction Firms may consider asset allocation and anti-takeover provision adoptions jointly or, alternatively, blockholders may consider pension asset allocation when they decide to hold a block of shares of the firm. If corporate governance and asset allocation were jointly determined, it would raise endogeneity concerns and regressions that did not explicitly correct for endogeneity would produce biased estimates. To address such potential endogeneity concerns, we use instrumental variable (IV) regressions through two-stage least squares (2SLS) to reestimate the asset allocation regressions. Specifically, we use for each firm the initial year Gindex (E-index) value in our sample period from 1990 to 2006 as a proxy for external governance and construct the Initial ED dummy variable accordingly. The initial G-index value is used because it changes slowly over time and the initial value is likely to be exogenous to
28
future pension asset allocations. This technique and reasoning have been used in Bebchuk, Cohen, and Ferrell (2005), Dittmar and Mahrt-Smith (2007), Masulis, Wang, and Xie (2007), and John, Litov, and Yeung (2008). With respect to internal governance, we follow John, Litov, and Yeung and use the 2-digit SIC industry’s contemporaneous average of block holdings and individual firm age as instruments for a firm’s block ownership. In the first stage of the 2SLS, we regress a firm’s aggregated block ownership on the selected instruments and other exogenous variables in the main equation to get the fitted values of aggregated block ownership. In the second stage, we replace the aggregated block ownership with its fitted values and run an OLS regression of the main equation. In addition, we run a battery of tests to examine the validity of endogeneity concerns and of the instruments. The IV regression results of the main equation that uses either the initial G-index or the initial E-index as a proxy for external corporate governance are reported in Panels A and B, respectively, of Table 4. In equity regressions (columns (1) and (2)) in Panel A, the Hausman endogeneity test rejects the null hypothesis that the 2SLS and OLS coefficient estimates are statistically the same, indicating that the OLS estimates could be biased. It validates the use of IV regression to correct for the potential endogeneity bias. The over-identification test does not reject the null hypothesis that the instruments are uncorrelated with the error term of the main equation and therefore substantiates their exclusion from the main equation. The partial Rsquared of the first-stage regression indicates that the selected instruments can explain 3% of the variation in aggregated block ownership, net of any effect they may have through the other explanatory variables. The F-test rejects the null hypothesis that the coefficients on both instruments are jointly zero.
29
As expected, both the Initial ED and Instrumented IGOV variables are positive and significant in the equity regressions. The estimates on initial ED suggest that firms with good external corporate governance take more investment risk by allocating 16% to 20% more of their pension assets to equities on average. In the same vein, a one percent increase in the blockholder ownership (represented by instrumented IGOV, a continuous variable) is associated with 0.29% to 0.32% increase in equity investment. Moreover, funding status and lagged returns on pension assets enter the regressions with positive signs and highly significant, confirming the previous round of results that risk-taking in asset allocations is positively correlated with better funding of pension plans, higher average (prior) returns on assets, and better financial condition of the sponsoring firms. With respect to other control variables, the coefficients on credit ratings are negative and highly significant, indicating that firms with poor credit ratings (i.e., with higher credit ratings values) allocate less pension asset to equities. Also, in line with the earlier finding, firms without credit ratings allocate a smaller share of pension asset to equities. ___________________________ Insert table 4 about here ____________________________ In the cash-debt-insurance regressions in Panel A, the coefficients on Initial ED and Instrumented IGOV have the expected signs but are not significant. Lagged pension returns are negatively correlated with cash-debt-insurance investment allocations, further suggesting that firms dynamically decrease safe asset allocations based on higher investment returns. It is worth highlighting that this key explanatory variable has the expected signs and significance even after controlling for several firm characteristics. Most of the remaining control variables have the expected signs but are not significant. Although the over-identification test and the test of instrument strength at the bottom of columns (3) and (4) suggest that the selected instruments are 30
valid, the Hausman endogeneity tests do not reject the null hypothesis that the IV and OLS coefficient estimates are statistically identical, which indicates that the OLS estimates (of the cash-debt-insurance regressions) are consistent and therefore more efficient than IV estimates. Panel B of Table 4 reports the IV regression results of pension asset allocation using the initial E-index as a proxy for external corporate governance. The estimates of control variables and related IV model validity test statistics are essentially similar to those reported in Panel A but are suppressed for brevity. It is noteworthy that the coefficient estimates of the internal and external corporate governance are all positive and statistically significant in equity allocation regressions but they are negative and insignificant in safe asset allocation regressions. These results are consistent with those reported in Panel A. To ensure that our IV regression results are robust and not sensitive to the choice of the proxy for external corporate governance, we replace the initial values of ED with the two-digit SIC industry peers’ contemporaneous average of the G-index or the E-index (as continuous measures and labeled as EGOV). In the following part, we discuss the estimation results but do not report them to save space (however the results are available upon request). Our results hold when we use the 2-digit SIC industry’s contemporaneous average E-index as evidenced by the negative sign and significance of the variable EGOV in equity regressions (note that by construction a higher value of E-index means higher entrenchment/poorer external governance). However, the coefficient on EGOV using the 2-digit SIC industry peers average G-index is not significant. The difference in the G- and E-index-based estimates could be due to the following reasons: a) the 2-digit SIC industry’s contemporaneous G-index is a poor proxy for a firm’s Gindex (indeed the correlation coefficient between the firm-level current G-index values and the 31
2-digit SIC industry contemporaneous average G-index is roughly 0.30 but the correlation between firm-specific initial G-index and current G-index values is about 0.90 in our sample; high correlation is perhaps one important reason why the initial year G-index is more often used as proxy for a firm’s G-index in the literature (for example, Bebchuk, Cohen, and Ferrell (2005), Dittmar and Mahrt-Smith (2007), Masulis, Wang, and Xie (2007), and John, Litov, and Yeung (2008)); and b) even if the values of the industry surrogate G-index and firm-level G-index are close, their importance in a firm’s anti-takeover defenses could be different since some provisions of the G-index are more efficient in discouraging takeovers than others (hence we find our results with 2-digit industry’s average E-index essentially unchanged since E-index builds on the most important ATPs). To evaluate the potential concern that the 2-digit SIC industry peers contemporaneous G-index is a poor proxy, we replace the initial G-index with the respective 3digit SIC industry surrogate and find that its coefficient is negative and significant as expected. In all cases, the coefficients on the instrumented IGOV are still positive and significant. Collectively, these results indicate that our findings are robust to using the industry peers’ contemporaneous average external governance as a proxy for the firm-level external governance. In summary, the IV regression estimates which correct for potential endogeneity bias induced by the choice of corporate governance mechanisms demonstrate that (a) risk-taking in pension asset allocations is positively correlated with higher investment returns and better funding of pension plans, and (b) firms with good external and/or internal corporate governance take more risk in pension asset allocations by investing more in equities. D. Robustness Tests We conduct several additional tests to make sure our results are robust (to save space we do not report these results but they are available upon request). First, we replace the governance 32
dummy variables with their respective continuous measures and rerun the analyses, but the results are essentially similar. Second, we replace the aggregated block ownership with aggregated institutional ownership as a proxy for internal corporate governance, without imposing the floor limit of 5% ownership. We also construct an internal governance dummy variable by comparing a firm’s institutional ownership with the sample’s annual respective median value. Our findings are qualitatively unchanged using either continuous institutional ownership or its dummy version. Third, we recalculate the safe asset ratios by including only cash and government debt while excluding insurance assets from the safe assets class and redo the estimation, but the conclusion about the effect of corporate governance on cash-debt allocation and the impact of cash-debt ratio on total pension asset returns are virtually the same. Fourth, as the dependent variables are ratios which are bounded between zero and one, we use the Tobit models to re-estimate asset allocations, but the reported findings persist. Fifth, firms can exploit arbitrage profits if they borrow to fund pension obligations and invest pension assets in debts since interest on the firm’s issued debts is tax deductible but income from investment of pension assets is tax free (Black (1980), Tepper (1981); Frank (2002)). Thus, the cash-debt-insurance allocations are expected to be positively correlated with the corporate marginal tax rate. We use John Graham’s simulated tax rates as the proxy for corporate marginal tax rate and augment firm-level pension asset allocation with this variable.9 The coefficients on marginal tax rates are negative and highly significant in equity regressions indicating that firms with high marginal tax rate allocate less pension assets to equity investment, but they are not significant in cash-debt-insurance regressions. More importantly, our findings about the effects of corporate governance on pension asset allocations are qualitatively unchanged when marginal
9
We thank John Graham for sharing the simulated tax rates.
33
tax rates are included in the regressions. Sixth, we relax the limit of opaque investment ratio (originally set at 5%) in increasing steps of 5% until it reaches 30% and notice that our conclusion are largely insensitive to these relaxations. Seventh, as firms could make pension asset allocation at the plan level, we follow Rauh (2009) and re-estimate the baseline regression as specified in equation (1) using the plan-level data. Our plan-level findings are consistent with those of the firm-level analyses. As firms self-select to offer or not to offer DB plans to their employees, our sample is non-random which raises potential self-selection bias concerns. We follow the Heckman (1979) two-step procedure to address these concerns. Specifically, in the first step we run a firm-level probit model similar to that of Shivdasani and Stefanescu (2010) with the dependent variable being a dummy variable, D, that takes a value of one if a firm sponsors a DB plan in a given year, and zero otherwise. Our sample comes from the intersection of Compustat, CRSP, G-index and E-index datasets, Thomson One Banker (for institutional ownership data), and industry unionization data (Hirsch and MacPherson (2003)) over the period from 1990-2006. The resulting consistent estimates of the probit model are then used to estimate the inverse Mill’s ratio, which is essentially the ratio of the probability density function and the cumulative density function. In the second step, we estimate asset allocation, i.e., equity or safe asset allocation, augmented with the inverse Mill’s ratio. It is noteworthy that all of our previous findings are robust to the correction for potential self-selection bias. Further, the coefficients on the inverse Mill’s ratio are negative and statistically significant in equity allocation regressions, validating correction for self-selection bias. It is plausible that sponsors with better governance invest more of their pension assets in their own equity with higher expected returns in order to raise pension returns and lower funding 34
requirements. We note that pension regulations cap the holdings of pension fund assets in sponsor’s own-stock at 10% of pension assets, but in our sample the sponsor’s own-equity accounts for a tiny portion of the total defined benefit pension plan assets (0.45%) and total equity investment (2.54%) on average. We perform multivariate analyses similar to those of equity regressions in Table 3, except that the dependent variable is the ratio of sponsor’s ownequity value divided by the total pension asset value. As before, we use three approaches to estimate the model: a) random effects model without correcting for potential self-selection bias; b) two-step Heckman model to correct for potential self-selection bias; and c) instrumental variable (IV) regression. Our estimation results do not show evidence of a significant effect of external corporate governance on own-equity allocation. However, the coefficients on internal corporate governance are all negative and marginally significant in some specifications. This evidence suggests that firms with higher blockholder ownership tend to allocate a smaller share of their pension assets to their own equity. If anything, this result implies the blockholders’ preference for diversifying investment. Further, the relation between prior year returns on pension assets and the own-equity asset allocation is insignificant. Finally, sponsors with higher lagged pension contributions tend to invest less in own-equity. Overall, the allocation to ownequity appears to play a minor role in pension risk-taking. If a firm becomes insolvent and its pension assets are insufficient to meet pension liabilities, its pension funds will be taken over by the Pension Benefit Guaranty Corporation (PBGC). Alternatively, a pension fund could be acquired along with its sponsor by another firm and the acquirer assumes full responsibility for the pension fund of the target following the merger. Such events raise concerns about potential survival bias in our sample. To address the first concern about PBGC takeover, we check Form IRS 5500 for each firm year and flag 35
individual firms that have at least one DB plan taken over by the PBGC in any given year during our sample period. In the next step, we match these firms with our sample firms and are able to identify 11 unique firms (associated with a total of 33 firm-year observations) that have at least one DB plan taken over by the PBGC. It is noteworthy that both the number of unique firms and the number of firm-year observations are very small in comparison to our total sample (329 unique firms and 1,114 firm-year observations), so we do not expect our results to change in a significant way even when we control for the PBGC takeovers. Next, we create a dummy variable that takes a value of one for those 11 identified firms (i.e., 33 observations take a value of one) and zero otherwise, and rerun our regressions. The coefficients on the newly created dummy variable are not significant in any specification and, more importantly, all our findings are essentially unchanged. Alternatively, we exclude these 33 firm-year observations of the 11 firms from our sample and rerun the regressions. Our results are qualitatively the same. To address the second source of potential survival bias when pension funds are taken over in a merger and acquisition (M&A), we identify those firms in our sample that were targets during the sample period. Then we exclude from our sample those cases in which the acquirer holds less than 50 percent of the target’s equity before the M&A deal and 100 percent of the target’s equity following the merger and the deal is reported as complete. This filter is fairly standard in the M&A literature and represents a major change in the target firm’s ownership and corporate governance. We are able to identify and exclude 64 unique target firms with 219 firmyear observations that meet our exclusion condition. Then we re-estimate our asset allocation equations using random effects model, self-selection model, and IV regressions. Although the sample gets smaller, our estimated results indicate that our findings persist.
36
Our evidence thus far indicates that plan sponsors with good corporate governance (either external or internal governance or both) take more risk in pension asset allocation by allocating a larger share of pension assets to equity. To go one step further, we ask whether the positive relation between good governance and risk taking is restricted to pension asset allocation only or whether it is a firm-wide behavior. Prior studies (see Rauh (2009), for example) suggest that the pension policy and its execution are not made in a vacuum with respect to the overall corporate objectives. Therefore, it is likely that the risk-taking behavior of the board of directors and its representatives serving as pension trustees carries over to the operating and capital investment policies of the entire firm. We adopt the framework in John, Litov, and Yeung (2008) but modify it to examine the likelihood of integration of risk-taking in corporate pension policy with real corporate decisions in our sample. Specifically, we construct three different measures of risktaking: volatility of industry-adjusted cash flow ratio (RISK1), volatility of industry-adjusted non-pension cash flow ratio (RISK2), and volatility of industry-adjusted return on equity (RISK3). RISK3 is meant to capture risk-taking incentives in capital structure choices in addition to real investment policy. Then we model firm-level risk-taking as a function of external and internal corporate governance while controlling for earnings smoothing, initial firm size, initial corporate earnings, initial sales growth, and initial leverage (the last control variable is used in RISK1 and RISK2 regressions). The estimated results suggest that the positive relation between good governance, particularly good external corporate governance, and risk-taking is a firm-wide behavior rather than limited to the pension investment policy. V. Conclusion Extending the line of research on investor protection and corporate risk-taking in capital investment decisions, we use private defined benefit pension plan asset allocations as a vehicle to 37
examine the impact of external and internal corporate governance on risk-taking. Our work is motivated by theoretical investment advice and empirical evidence suggesting that risk-taking in asset allocation enhances pension funding through higher investment returns and lower pension contributions. Our main findings are that firms that invest heavily in equities are positively correlated with higher average pension investment returns and better funded pension plans as well as somewhat lower pension contributions, as compared with their counterparts who allocate a larger percentage of pension assets to cash, debt, and insurance accounts. More importantly, we find evidence that plan sponsors with good corporate governance take more risks by allocating a larger share of their pension plan assets to equities. The evidence holds generally at both the plan and firm levels, even after we control for other factors that have been documented in the literature to have potential power in explaining pension asset allocation. Our findings are robust to corrections for potential endogeneity of corporate governance and survive several other robustness checks. Our results suggest that public policy should consider strengthening external and internal governance mechanisms to improve the financial health of private defined benefit plans.
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Logue, D., and J. Rader. “Managing Pension Plans.” Boston, MA: Harvard Business School Press (1998). Masulis, R. D.; C. Wang; and F. Xie. “Corporate Governance and Acquirer Returns.” Journal of Finance, 62 (2007), 1851-1889. Mørck, R. K.; D. Wolfenzon; and B. Yeung. “Corporate Governance, Economic Entrenchment, and Growth.” Journal of Economic Literature, 43 (2005), 657-722. Pyramis Global Advisors. “Pyramis Global Pension “Pulse” Poll: Leading Global Pension Plans Believe Future Growth to Come from Active Equity Management.” Toronto, © 2010 FMR LLC. Retrieved on November 11, 2011 from www.fidelity.ca/cs/Satellite/doc/pyramis_pulse_poll.pdf. Rauh, J. D. “Investment and Financing Constraints: Evidence from the Funding of Corporate Pension Plans.” Journal of Finance, 61 (2006), 33-71. Rauh, J. D. “Risk Shifting versus Risk Management: Investment Policy in Corporate Pension Plans.” Review of Financial Studies, 20 (2009), 2687-2773. Sharpe, W. F. “Corporate Pension Funding Policy.” Journal of Financial Economics, 3 (1976), 183-193. Shivdasani, A., and I. Stefanescu. “How Do Pension Affect Capital Structure Decisions?” Review of Financial Studies 23 (2010), 1287-1323. Stulz, R. “The Limits of Financial Globalization.” Journal of Finance, 60 (2005), 1595-1638. Sundaresan, S., and F. Zapatero. “Valuation, Optimal Asset Allocation and Retirement Incentives of Pension Plans.” Review of Financial Studies 10 (1997), 631-660. Tepper, I. “Taxation and Corporate Pension Policy.” Journal of Finance, 36 (1981), 1-13.
42
Treynor, J. “The Principles of Corporate Pension Finance.” Journal of Finance, 32 (1977), 627638. Wooldridge, J. M. “Econometric Analysis of Cross Section and Panel Data.” MIT Press, Cambridge, Massachusetts, London, (2002).
43
Table 1: Descriptive Statistics The table reports summary statistics for the all Defined Benefit (DB) plan sample (Panel A) and the analysis DB plan sample (Panel B), with more than 100 employees, and have opaque asset value less than 5% of the total pension plan assets value in the 1990-2006 period. Observations are at the beginning of plan years. Plan data come from Form 5500 that firms file annually with the IRS. Pension assets come from the main 5500 form (1998 and earlier) or Schedule H (in the post-1998 period). Plan liabilities are based on OBRA87 for plan years ending 1990-1994 and on the RPA94 for plan-year observations ending 1995-2006. Pension investment income is measured as the total income from the main form or Schedule H minus contributions minus other noninvestment income. Pension investment returns are calculated as investment income divided by beginning-of-year assets. Pension contributions come from Schedule B. Panel B reports summary statistics of DB plan that can be matched with firm characteristics and Compustat accounting data based on CUSIP for 1990-1997 and Employer Identification Number (EIN) for 1998-2006. Funding status is measured as the difference between plan assets and current pension liabilities all scaled by current pension liabilities. Panel C provides summary statistics for firm-level data. Credit rating is S&P credit rating and credit rating dummy is a dummy variable that takes a value of one if a firm has no credit rating in a given year and zero otherwise. We convert the S&P credit rating into scores as follows: AAA=1, AA+=2, …, C=21, and D=22.a A firm with lower (higher) score has better (worse) credit rating. Operating assets is the firm’s book value of assets. Altman’s Z score, a measure of financial bankruptcy probability, is calculated as (3.3*EBIT/Operating Assets) + (Sales/Operating Assets) + 1.4*(Retained Earnings/Operating Assets) + 1.2*(Net Working Capital/Operating Assets). Non-pension cash flow ratio (NPC) is measured as the sum of (Net Income + Depreciation and Amortization + Accounting Pension Expense) divided by total assets. NPC volatility is the 5-year standard deviation of the NPC. Pension obligation is the ratio of pension liabilities 44
to operating assets. G-index is the Gompers-Ishii-Metrick index that represents the number of anti-takeover provisions adopted by a firm. Eindex covers up to six anti-takeover provisions with more explanatory power about managerial entrenchment. Block ownership is the plan sponsor’s sum of holdings of blockholders that hold at least 5% of the firm’s common shares. Ratio variables are winsorized at the 1% and 99% levels to avoid outliers.
Panel A: All-DB Plan Sample Variable
Mean
1st Percentile
Median
99th Percentile
Std Dev
Pension assets
34. 835
0.00
4.902
626.150
133.422
Pension current liabilities Pension investment income
36.751 3.123
0.018 -4.821
5.519 0.299
638.781 63.824
137.375 13.639
1.279
0.00
0.160
22.814
4.659
0.170
-1.000
0.150
2.310
0.590
Pension investment return
0.080
-0.120
0.080
0.300
0.080
Contributions/Pension assets Active participant ratio
0.080 0.620
0.000 0.000
0.040 0.650
0.850 0.980
0.130 0.240
Corporate equity Cash and government debt
0.290 0.270
0.000 0.000
0.290 0.210
0.790 1.000
0.270 0.270
Insurance company accounts
0.180
0.000
0.000
1.000
0.360
Other investment
0.270
0.000
0.180
1.000
0.260
Levels (in millions)
Pension contributions Ratios Funding status
Asset allocation
Plan year observations : 88,854 Number of unique plans: 22,563 Number of unique firms: 17,730
45
Panel B: Analysis DB Plan Sample Variable
Mean
1st Percentile
Median
99th Percentile
Std Dev
Pension assets
147.902
0.044
26.634
1,745.845
339.559
Pension current liabilities Pension investment income
122.645 11.827
0.024 -11.892
21.256 1.069
1,655.901 172.575
305.056 32.641
3.384
0.000
0.147
54.024
9.468
Levels (in millions)
Pension contributions Ratios Funding status
0.330
-0.920
0.220
2.430
0.560
Pension investment return
0.090
-0.130
0.080
0.310
0.090
Pension contributions/Pension assets Active participant ratio
0.080 0.590
0.000 0.000
0.020 0.640
0.850 0.960
0.140 0.250
Corporate equity Government debt and cash
0.326 0.077
0.000 0.000
0.378 0.000
0.987 0.990
0.296 0.186
Insurance company accounts
0.153
0.000
0.000
1.000
0.340
Other investment
0.443
0.000
0.387
1.000
0.343
Mean
1st Percentile
Median
99th Percentile
Std Dev
8.070
1.000
8.000
17.000
3.449
Asset allocation
Plan-year observations
: 1,588
Number of unique plans :
467
Number of unique firms :
329
Panel C: Firm-level Statistics Firm characteristics S&P credit rating (1-22) No S&P credit rating Operating assets ($ millions) Altman Z-score NPC
0.449
0.000
0.000
1.000
0.498
7,982.29 3.251
93.38 1.115
1,688.80 2.711
65,284.50 6.754
15,271.61 1.818
0.086
-0.096
0.081
0.340
0.090
46
Standard deviation of NPC
0.031
0.001
0.019
0.166
0.049
Pension investment income (in $ million)
47.40
-46.80
3.101
857.00
371.00
Pension investment return Pension contribution (in $ million)
0.091 10.09
-0.119 0.000
0.083 0.30
0.301 19.78
0.094 54.79
Pension contribution ratio
0.055
0.000
0.013
0.408
0.096
G-index E-index
9.433 2.546
4.000 0.000
9.000 3.000
15.000 5.000
2.767 1.439
Block ownership
0.127
0.000
0.078
0.884
0.157
150.86
45.76
50.79
696.14
214.29
Funding status
0.263
-0.833
0.168
2.090
0.485
Asset allocation Corporate equity
Pension characteristics Pension assets ($ millions)
0.411
0.000
0.483
0.987
0.272
Government debt and cash
0.095
0.000
0.000
0.990
0.195
Insurance company accounts Other investment
0.061 0.433
0.000 0.000
0.000 0.389
1.000 1.000
0.212 0.298
Firm-year observations: 1,114 Number of unique firms: 329 a The entire S&P credit ratings are converted into scores as follows: AAA=1, AA+=2, AA=3, AA−=4, A+=5, A=6, A−=7, BBB+=8, BBB=9, BBB−=10, BB+=11, BB=12, BB−=13, B+=14, B=15, B−=16, CCC+=17, CCC=18, CCC−=19, CC=20, C=21, and D=22.
47
Table 2: Corporate Governance, Pension Asset Allocation, and Fund Performance – Univariate Analyses This table reports univariate analyses of the relation between firm-level equity asset allocation (EAA), safe asset allocation (SAA) and fund performance - pension investment returns, pension contributions, and pension funding status (Panels A and B); and the relation between the combinations of corporate governance-asset allocation and fund performance (Panels C, D, and E). The analysis is restricted to firm-year asset observations that have less than 5% of assets allocated to opaque investment vehicles. The sample consists of 1,114 firm-year observations (of 467 unique plans belonging to 329 unique firms) drawn from the 1990-2006 period. Poor governance consists of those firm-year observations that have G-index (E-index) less than the respective contemporaneous sample median, or blockholder ownership greater than the respective contemporaneous sample median. The remaining firm-year observations denote good governance for each respective governance measure. Low EAA (SAA) represents those firm-year observations that have the ratio of assets allocated to equity (cash-debt-insurance contract) less than the respective contemporaneous sample median, and high equity (safe assets) otherwise. Pension investment return is the return on pension assets measured as pension fund investment appreciation (or depreciation) in dollars during the fiscal year divided by the beginning-ofyear pension assets. Pension contributions are divided by beginning-of-year assets. Funding status is measured as the difference between plan assets and current pension liabilities all scaled by current pension liabilities. Panel A: Equity Asset Allocation (EAA) and Pension Fund Performance N
Pension Returns
Pension Contributions
Funding Status
Low EAA
551
0.0741
0.0681
0.1765
High EAA Difference
563
0.1077 -0.0336
0.0418 0.0263
0.3451 -0.1686
6.03
4.37
-5.49
t-value
48
Prob>|t| Wilcoxon rank sum Z-stat Prob>|z|
0.00
0.00
0.00
-6.43 0.00
3.98 0.00
-4.66 0.00
Panel B: Safe Asset Allocation (SAA) and Pension Fund Performance N
Pension Returns
Pension Contributions
Funding Status
Low SAA
549
0.1123
0.0433
0.3722
High SAA
565
0.0699
0.0639
0.1622
0.0424 7.55
-0.0206 -4.01
0.2100 6.89
Prob>|t|
0.00
0.00
0.00
Wilcoxon rank sum Z-stat
6.73
-3.45
8.36
Prob>|z|
0.00
0.00
0.00
Difference t-value
Panel C: Corporate Governance and Pension Asset Allocation G-index
E-index
Blockholder Ownership
N
EAA
SAA
N
EAA
SAA
N
EAA
SAA
425 689
0.4131 0.4106
0.1425 0.1643
497 617
0.3837 0.4337
0.1602 0.1512
555 559
0.4241 0.3996
0.1360 0.1759
0.0025
-0.0218
-0.0450
0.0108
0.0246
-0.0399
T-stat Prob>|t|
0.14 0.89
-1.43 0.15
-2.79 0.00
1.27 0.21
1.47 0.14
-2.60 0.00
Wilcoxon rank sum Z-stat Prob>|Z|
0.45 0.65
-0.07 0.95
-2.48 0.01
1.10 0.27
0.71 0.48
-3.64 0.00
Poor governance Good governance Difference in mean
49
Panel D: Governance (GOV), EAA and Pension Fund Performance G-index N
Pension Returns
E-index
Pension Contributions
Funding Status
Blockholder Ownership
N
Pension Returns
Pension Contributions
Funding Status
N
Pension Returns
Pension Contributions
Funding Status
Poor GOV-Low EAA
197
0.0746
0.0542
0.1707
198
0.0747
0.0615
0.1929
254
0.0797
0.0649
0.2150
Good GOV-High EAA Difference
335
0.1116 -0.0371
0.0474 0.0067
0.3434 -0.1727
327
0.1109 -0.0362
0.0459 0.0155
0.3348 -0.1419
277
0.1066 -0.0270
0.0443 0.0205
0.2897 -0.0747
-4.31
0.81
-3.78
-4.16
1.89
-3.14
-3.42
2.62
-1.80
0.00
0.42
0.00
0.00
0.06
0.00
0.00
0.00
0.07
-4.73
-0.66
-2.72
-4.68
1.71
-2.28
-3.97
2.39
-0.44
0.00
0.51
0.01
0.00
0.09
0.02
0.00
0.02
0.66
Funding Status
N
Pension Returns
Pension Contributions
Funding Status
N
Pension Returns
Pension Contributions
Funding Status
T-stat Prob>|t| Wilcoxon rank sum Z-stat Prob>|z|
Panel E: Governance (GOV), SAA and Pension Fund Performance G-index
E-index
N Poor GOV-High SAA
236
0.0654
0.5051
0.2487
321
0.0654
0.0594
0.1997
277
0.0710
0.0657
0.1953
Good GOV-Low SAA
360
0.112
0.0468
0.4278
314
0.1138
0.0456
0.4022
250
0.1099
0.0453
0.3228
-0.0466 -5.66
0.0037 0.44
-0.1791 -3.53
-0.0484 -5.66
0.0138 1.48
-0.2025 -4.17
-0.0389 -4.62
0.0204 2.43
-0.1275 -2.94
0.00
0.66
0.00
0.00
0.14
0.00
0.00
0.02
0.00
-5.30
-1.54
-4.52
-5.21
1.37
-5.15
-4.21
2.19
-3.23
0.00
0.12
0.00
0.00
0.17
0.00
0.00
0.03
0.00
Difference t-value Prob>|t| Wilcoxon rank sum Z-stat Prob>|z|
Pension Contributions
Blockholder Ownership
Pension Returns
50
Table 3: Corporate Governance and Pension Asset Allocation at the Firm-level: G-index The sample consists of 1,114 firm-year observations (of 329 unique firms) aggregated from DB plans that have less than 5% of assets allocated to opaque investment vehicles, and other firm-level data. ED is a dummy that takes a value of one if the plan sponsor’s G-index (E-index) is below or equal to the contemporaneous sample median (i.e. less managerial entrenchment, which implies good external corporate governance), and a value of zero (i.e. more managerial entrenchment, indicating poor corporate governance) otherwise. ID is a dummy variable that takes a value of one if the plan sponsor’s sum of holdings of block investors that hold at least 5% of the firm’s common shares is equal to or above the contemporaneous sample median, and a value of zero otherwise. Other variables are constructed similarly to those in Table 1 but at the firm-level. NPC represents non-pension cash flow ratio, and NPC volatility is the standard deviation of NPC ratio. Nonindicator variables in the interactions are demeaned. The Hausman test tests the null hypothesis of no difference between fixed effects and random effects against the alternative hypothesis that the fixed effects model is appropriate. Heteroskedasticity-robust standard errors clustered by firm are in parentheses. The estimates of most of the control variables and model validity test statistics are suppressed in Panel B for brevity. ***, **, * indicates statistical significance at 1%, 5%, and 10%, respectively.
Panel A: G-index Equity Ratio
Cash-debt-insurance Ratio
1
2
3
4
5
6
ED
0.089**
0.093**
0.094**
-0.067**
-0.076**
-0.076**
ID
(0.035) 0.016
(0.038) 0.01
(0.038) 0.009
(0.031) 0.004
(0.032) 0.004
(0.032) 0.003
(0.015)
(0.016)
(0.016)
(0.015)
(0.013)
(0.014)
ED*FS
0.004 (0.053)
-0.002 (0.041)
ID*FS
-0.064
-0.01
51
(0.051) FS
0.04 (0.031)
-0.018 (0.021)
-0.012 (0.033)
-0.04
0.270***
0.270***
-0.004
(0.135) -0.006
(0.134) -0.005
0.003
(0.094) 0.004
(0.094) 0.004
(0.005)
(0.005)
(0.005)
(0.005)
(0.006)
(0.006)
-0.116** (0.053)
-0.135** (0.054)
-0.128** (0.053)
0.056 (0.045)
0.062 (0.046)
0.064 (0.046)
-0.025*
-0.027*
-0.026
-0.01
-0.004
-0.003
(0.015) 0.069***
(0.016) 0.074***
(0.016) 0.073***
(0.017) -0.043**
(0.018) -0.049***
(0.018) -0.050***
(0.012)
(0.012)
(0.012)
(0.018)
(0.019)
(0.019)
-0.004 (0.007)
-0.001 (0.007)
0.001 (0.007)
0.009 (0.007)
0.008 (0.007)
0.008 (0.007)
0.026
-0.046
-0.052
-0.352
-0.239
-0.241
(0.321) -0.129
(0.338) -0.131
(0.337) -0.135
(0.262) 0.044
(0.267) 0.077
(0.265) 0.076
(0.098)
(0.099)
(0.101)
(0.074)
(0.075)
(0.074)
0.106 (0.114)
0.06 (0.121)
0.053 (0.123)
-0.096 (0.101)
-0.022 (0.100)
-0.023 (0.101)
0.127
0.134
0.126
0.012
-0.006
-0.008
(0.081) -0.215
(0.087) -0.25
(0.087) -0.364
(0.080) 1.309***
(0.082) 1.268***
(0.082) 1.009***
(0.362)
(0.378)
(0.348)
(0.358)
(0.392)
(0.357)
117.98 0.00
118.61 0.00
127.79 0.00
384.52 0.00
429.19 0.00
462.04 0.00
Year fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
R-squared
0.19
0.19
0.19
0.32
0.35
0.35
15.5 0.22
12.39 0.50
33.47 0.26
3.52 0.99
3.2 0.99
7.14 0.99
No
No
No
No
No
No
Lagged contributions Credit ratings Credit ratings dummy (Y/N) Ln(Operating assets) Ln(Pension assets) Z score NPC volatility Pension obligations NPC Lagged pension returns Intercept 2
χ Prob> χ2
0.035 (0.032)
0.067* (0.040)
-0.049
(0.044) -0.044* (0.024)
Hausman test FE vs. RE χ2 Prob> χ2 Reject consistency of RE? Panel B: E-index Equity Ratio
Cash-debt-insurance Ratio
1
2
3
4
5
6
ED
0.091*** (0.031)
0.098*** (0.032)
0.097*** (0.032)
-0.02 (0.034)
-0.019 (0.035)
-0.018 (0.035)
ID
0.020
0.015
0.014
0.002
0.002
0.002
(0.015)
(0.016)
(0.016) -0.021
(0.015)
(0.014)
(0.014) 0.022
ED*FS ID*FS
(0.052)
(0.041)
-0.059
-0.015
52
(0.052) FS Lagged contributions
0.036 (0.031)
0.033 (0.032)
0.073* (0.040)
-0.004 (0.133)
(0.044) -0.045* (0.025)
-0.021 (0.021)
-0.023 (0.034)
-0.001
0.242**
0.248***
(0.132)
(0.094)
(0.093)
53
Table 4: Instrumental Variable (IV) Regressions of Corporate Governance and Pension Asset Allocation at the Firm-level The sample consists of 1,114 firm-year observations (of 329 unique firms) aggregated from DB plans that have less than 5% of pension assets allocated to opaque investment vehicles, and other firm-level data. All models are estimated by IV regressions through two-stage least squares (2SLS). The G-index (E-index) of the first year that a firm appears in the sample is used as an instrument for external governance. Initial ED is a dummy variable that takes a value of one if a firm’s G-index (E-index) in the initial year is below or equal to the sample median and zero otherwise. 2-digit SIC industry average block ownership ratio and firm age are used as instruments for a firm’s block ownership (i.e. IGOV). Test of over-identifying restriction tests the null hypothesis that the instruments do not belong to the main equation. Hausman test examines the endogeneity validity of the test variable (i.e. block ownership in this table). The test of instrument strength examines whether the selected instruments are valid. Heteroskedasticityrobust standard errors clustered by firm are in parentheses. ***, **, * indicates statistical significance at 1%, 5%, and 10%, respectively. Panel A: G-index Equity Ratio Instrumented IGOV Initial ED
1
2
3.175**
2.867**
-0.629
-0.657
(1.366)
(1.347)
(1.231)
(1.209)
0.203** (0.092)
0.158* (0.090)
-0.071 (0.091)
-0.061 (0.086)
Lagged contributions Credit ratings Credit ratings dummy (Y/N) Ln(Operating assets) Ln(Pension assets) Z score
Cash-debt-insurance Ratio 3
4
-0.046
0.173
-0.033**
(0.389) -0.038***
0.018
(0.253) 0.021
(0.015)
(0.014)
(0.013)
(0.014)
-0.469*** (0.159)
-0.510*** (0.148)
0.229 (0.147)
0.238 (0.152)
-0.033
-0.038
0.05
0.047
(0.035) 0.115***
(0.035) 0.115***
(0.035) -0.087**
(0.037) -0.084**
(0.037)
(0.035)
(0.036)
(0.035)
0.028
0.028
0.028
0.029
54
(0.022)
(0.021)
(0.023)
(0.023)
-0.265 (0.791)
-0.429 (0.745)
0.131 (0.678)
0.032 (0.601)
0.150**
0.159**
0.016
0.020
(0.070) -0.173
(0.070) -0.163
(0.050) 0.099
(0.058) 0.107
(0.203)
(0.194)
(0.146)
(0.153)
0.729 (0.464)
0.803* (0.471)
-0.518 (0.351)
-0.582 (0.411)
0.819**
0.651*
-0.456***
-0.397**
(0.358) -1.36
(0.381) -1.109
(0.155) 0.444
(0.176) 0.415
(1.199)
(1.180)
(1.241)
(1.250)
Yes 54.86
Yes 66.82
Yes 294.91
Yes 307.19
0.00
0.00
0.00
0.00
14.87
11.83
1.84
2.41
0.00
0.00
0.18
0.12
0.23
0.15
2.56
2.41
0.63
0.70
0.11
0.12
F-stat
3.77
3.16
3.77
3.16
Prob>F Partial R2
0.03 0.03
0.06 0.03
0.02 0.03
0.04 0.03
NPC volatility FS Pension obligations NPC Lagged pension returns Intercept Year fixed effects χ2 Prob> χ2 Hausman endogenous test χ2 2
Prob> χ Overidentification test χ2 2
Prob> χ Test of instrument strength
Panel B: E-index Equity Ratio Instrumented IGOV Initial ED
1
2
3.544**
3.078**
-1.045
-0.89
(1.650)
(1.515)
(1.500)
(1.352)
0.087* (0.053)
0.078* (0.047)
-0.03 (0.084)
-0.024 (0.079)
Lagged contributions FS
Cash-debt-insurance Ratio 3
0.138
4
0.095
0.123*
(0.397) 0.147**
0.022
(0.280) 0.022
(0.073)
(0.071)
(0.051)
(0.057)
55
