The substitution hypothesis of agency conflicts: Evidence on Shariah compliant equities

Accepted Manuscript The substitution hypothesis of agency conflicts: Evidence on Shariah compliant equities

Wajahat Azmi, Zaheer Anwer, Shamsher Mohamad, Mohamed Eskandar Shah PII: DOI: Reference:

S1044-0283(18)30186-8 https://doi.org/10.1016/j.gfj.2019.02.004 GLOFIN 463

To appear in:

Global Finance Journal

Received date: Revised date: Accepted date:

27 April 2018 22 February 2019 25 February 2019

Please cite this article as: W. Azmi, Z. Anwer, S. Mohamad, et al., The substitution hypothesis of agency conflicts: Evidence on Shariah compliant equities, Global Finance Journal, https://doi.org/10.1016/j.gfj.2019.02.004

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ACCEPTED MANUSCRIPT The substitution hypothesis of agency conflicts: Evidence on Shariah compliant equities Wajahat Azmia, Zaheer Anwerb*, Shamsher Mohamadc, Mohamed Eskandar Shahd a

International Centre for Education in Islamic Finance, Lorong Universiti ‘A’, Kuala Lumpur, Malaysia b

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Lahore Centre for Excellence in Islamic Banking and Finance, University of Lahore, 1-KM Defense Road, Lahore, Pakistan c

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International Centre for Education in Islamic Finance, Lorong Universiti ‘A’, Kuala Lumpur, Malaysia d

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International Centre for Education in Islamic Finance, Lorong Universiti ‘A’, Kuala Lumpur, Malaysia

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Conflict of Interest: The authors declare that they have no conflict of interest.

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Corresponding author. +923214011252 E-mail addresses: [email protected] (W. Azmi), [email protected] (Z. Anwer), [email protected] (S. Mohamad), [email protected] (M. Shah) 1

ACCEPTED MANUSCRIPT ABSTRACT According to the substitution hypothesis and recent evidence, firms that are better governed carry less debt and experience fewer agency problems. This may also imply that firms with lower debt are better governed and experience lower agency costs. We test this hypothesis by comparing

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the agency costs of Shariah compliant (SC, and therefore low debt) and Shariah noncompliant

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(SNC) firms, using a proprietary dataset comprising constituents of the Dow Jones Islamic index

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for the period 2006–2015. The findings support the hypothesis but are contingent on the firm’s

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idiosyncratic risk; SC firms with low idiosyncratic risk have higher agency costs.

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JEL classification:

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G340

Agency costs

Capital structure

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Stock screening

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Corporate governance

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Shariah compliant equities

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Keywords:

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Introduction Agency theory, put forth in the seminal work of Jensen and Meckling (1976), has its

origin in the way a corporation works. The owners or the shareholders appoint managers to run the business, and this separation of ownership from control gives rise to agency conflicts. The managers, as agents of the shareholders, are supposed to carry out activities in the best interests 2

ACCEPTED MANUSCRIPT of shareholders. However, the managers may be motivated to work in their own self-interest and in the process may destroy firm value. One way to align the interests of shareholders and managers is to issue debt, as regular debt payment reduces the free cash flow available to managers, and increases external monitoring and takeover threats (Grossman & Hart, 1982;

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Jensen, 1986). Along similar lines, improving corporate governance ensures a balance between

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managers’ and shareholders’ interests (Arping & Sautner, 2010; Jiraporn, Kim, Kim, &

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Kitsabunnarat, 2012). Recent evidence indicates that better corporate governance can be effectively used as a substitute for debt in reducing agency conflicts. La Porta, Lopez-de-Silanes,

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Shleifer, and Vishny (2000), Hu and Kumar (2004), Hoberg and Prabhala (2009), and Michaely

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and Roberts (2012) argue that weakly governed firms must signal to the market that they are not expropriating wealth from shareholders, and that they can do this by carrying more debt, as the

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regular payments reduce free cash flow and hence the amount available to be expropriated. It

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follows that low-debt firms are presumed to be well governed and should have lower agency costs. Shariah compliant (SC) firms provide a natural experiment to test this claim, as they do

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not use debt beyond a certain threshold. Taking our cue from the substitution hypothesis and the

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empirical findings of Arping and Sautner (2010) and Jiraporn et al. (2012) that there is a negative association between governance and debt, we therefore hypothesize that Shariah compliant (SC)

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firms have lower agency problems than Shariah noncompliant (SNC) firms. Islamic Shariah screening follows two criteria for approving investments: “line-ofbusiness screens” and “financial ratio screens” (Ashraf & Khawaja, 2016). The first criterion excludes firms whose main business are impermissible involving interest (riba), pork, extreme risk taking (gharar), gambling (maysir), weapons and defense, pornography, etc. However, even after this screen, there will be firms that have revenues from impermissible businesses that

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ACCEPTED MANUSCRIPT cannot be directly avoided. The second criterion excludes companies having (1) total debt and/or monetary assets accounting for 33% or more of market capitalization, (2) accounts receivable accounting for more than 33% of total assets/market value of equity, (3) ratio of cash to market value of equity greater than 33%, and (4) more than 5% of revenues coming from impermissible

Table 1.

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[Table 1 around here]

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business activities. Details on the screening methods applied by different indexes are available in

If SC firms manifest lower agency costs, what drives this difference? As a plethora of

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corporate governance literature (Shleifer & Vishny, 1997) asserts that better governance

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translates into lower agency cost, our second testable hypothesis is that, if SC firms have lower agency cost, one of the drivers of that difference is good governance. As the substitution

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hypothesis suggests that debt and governance are alternatives in mitigating agency conflicts, our

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third hypothesis is that low debt in SC firms drives their lower agency costs. Additionally, stewardship theory (Singh and Davidson III (2003) argues that longer CEO tenure is associated

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with stability and better governance, so our fourth hypothesis states that lower agency cost in SC

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firms is driven by longer CEO tenure. Likewise, agency theory posits that if agency issues are severe, self-interested managers indulge in empire building and start suboptimal projects,

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whereas good governance encourages projects with positive net present value. Consequently, our fifth hypothesis is that higher asset growth drives lower agency cost in SC firms. Finally, many authors argue that good governance and effective legal protection of shareholders encourage dividend payout (La Porta et al., 2000; Hu & Kumar, 2004; Hoberg & Prabhala, 2009; Michaely & Roberts, 2012), minimizing free cash flows that otherwise could be exploited by managers for

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ACCEPTED MANUSCRIPT their own benefit. In line with this argument, our sixth hypothesis is that higher dividend payout drives lower agency cost in SC firms. To test these hypotheses, we use the constituents of the Dow Jones Islamic Market IndexUS (DJIM-US) and its parent index the Dow Jones US Index (DJUSI). We use three alternate

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proxies of agency cost: expense ratio, asset utilization ratio, and Q*Free Cash Flow. To test for

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the sensitivity of the results, we use an alternate proxy of governance, namely the ESG

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(environmental, social, and governance) Combined Score from Thomson Reuters Eikon, which takes into account news and information available in the public domain. As we use firm-level

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data, some of our variables—specifically, debt and corporate governance—may be endogenous,

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and the dependent variable (agency problems) may be affecting one of the independent variables (debt), so that the model may suffer from reverse causality. To address these possibilities, we

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estimate the model using lag terms of the independent variables. To add an additional layer of

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robustness, our analysis applies the two-step first differenced and system Generalized Method of Moments (GMM).

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This paper contributes to the literature in several ways. First, it adds to the substitution

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literature by shedding light on the substitutability of debt and governance in affecting agency costs. Specifically, this paper highlights the effectiveness of corporate governance mechanisms

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in reducing agency issues in SC equities. Moreover, this paper adds to the growing literature on agency costs by providing evidence on agency issues in SC firms, and on how the absence of sin stocks and presence of low-debt capital structure affect agency cost. Second, our estimations involve the U.S. market, whereas, with few exceptions, most of the evidence available so far on SC firms is based on Malaysia (Hooy & Ali, 2017), Saudi Arabia (Merdad, Kabir Hassan, & Hippler, 2015), or the GCC market (Al-Awadhi & Dempsey,

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ACCEPTED MANUSCRIPT 2017), because the data maintained by the index providers are proprietary and not publicly available. We use proprietary data from the Dow Jones Indices. Third, the lack of literature on this topic is unfortunate, to say the least, since Islamic finance as a system has been pitched as an alternative to a conventional system by some of its

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necessary to examine how Islamic financial transactions work.

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strong advocates (see Mirakhor (2010)). The increasing acceptance of Islamic finance makes it

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The rest of this paper is organized as follows: section 2 describes research methods, section 3 discusses results, and section 4 concludes the study. Research methods

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2.

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For our estimations, we have used the following general fixed effect model:

where y represents agency cost, i represents number of firms, t represents time periods, and u is

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the error term. SC is a dummy variable that takes the value of one for SC equities, and zero

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otherwise. In order to choose whether to employ a fixed effects or a random effects model, we used the Hausman specification test, as Wooldridge (2010) suggests. As the independent

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variables were correlated with the individual random effects, we used a fixed-effects model. In further estimations we incorporated interactions of the SC dummy with key control variables, namely a governance index, ratio of debt to assets, tenure, asset growth, and dividend payout, all of which influence agency costs and may distinguish SC firms from SNC firms. We used data on the constituents of the Dow Jones Islamic Market Index US (DJIM-US) and its conventional counterpart, the Dow Jones United States Index (DJUSI), purchased directly from S&P Dow Jones Indices. There are several reasons to choose DJIM-US over other service 6

ACCEPTED MANUSCRIPT providers. First, it provides longer data on SC firms than do MSCI Islamic, FTSE Islamic, etc. Second, its screening criteria are believed to be more balanced—neither too strict as compared to MSCI, nor too lenient as compared to the Bursa Malaysia Shariah Index. Third, it has the largest number of stocks. Fourth, it is the index most used in academic research. Why did we not use the

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screening criteria to select our sample stocks ourselves? First, it is very tedious to screen stocks

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quarterly, as a stock qualifying as SC in one quarter may become SNC in the next period.

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Second, doing so can lead to measurement errors. DJIM-US has a team dedicated to the screening, and its data should be relatively free from measurement errors. Third, using DJIM-US

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constituents also ensures, to a certain extent, that the data we use are followed by investors and

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other market players, as being on the index increases their visibility. This ensures that all the firms in the sample meet certain standards in terms of their performance, etc., and agency issues

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and corporate governance.

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There are also several reasons for choosing the United States for this research. To begin with, the United States is a developed country with a sophisticated market, and the chances of

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friction are lower, as La Porta et al. (2000) rate it as having high shareholder protection.

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Furthermore, the United States is among the most innovative countries of the world and possesses substantial geographic variation in religious composition and innovative activities

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(Adhikari & Agrawal, 2016). Data availability is a prime reason; Dow Jones has been screening U.S. stocks for Shariah compliance for a considerable period of time, and ESG data for U.S. firms are easily available from more than one provider, allowing us to check the robustness of our results by using different ESG measures. Our analysis could be made more comprehensive by adding other countries to the sample, but data on SC firms are not publicly available except for Malaysia, and reliable governance indicators are available only for the U.S. market.

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ACCEPTED MANUSCRIPT We use data for 2006–2015 and consider our sample adequate to conduct the required estimations and draw inferences. The DJIM-US is rebalanced quarterly, and the DJUSI is rebalanced once a year. The historical information on the firms indexed, especially SC stocks, is important, as stocks in the current list may not have been SC in previous lists or may become

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SNC in the next screening. Following is a year-by-year summary of the numbers of stocks for

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[Table 2 around here]

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which we received data from Dow Jones, on the DJUS and the DJIM-US.

In line with agency literature, we exclude utilities (SIC Codes 4900–4949) and financial

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firms (6000–6999), as they are subject to distinct regulatory structures. The final sample

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comprises all those stocks within the constituent lists for which financial and governance-related information was available; it includes 9,058 firm-year observations, out of which 4,405 pertain to

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SC firms. Table 3 reports statistics related to the capital structure of SC and SNC firms. It can be

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observed that, on average, only 12% of the assets of SC firms are financed by debt, whereas for SNC firms the average debt component is 27%. For the full sample as well as for SNC firms, the

[Table 3 around here]

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maximum leverage reaches as high as 90%, but for SC firms the maximum debt ratio is 32%.

To measure agency cost, we have used three different ratios—the expense ratio, the asset

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utilization ratio, and Q*Free Cash Flow (Q*FCF)—in line with existing studies by Doukas, Kim, and Pantzalis (2000), McKnight and Weir (2009), Henry (2010), and Rashid (2016). The independent variables include a governance index, asset growth, firm size, debt/assets, idiosyncratic risk, and the KZ index of Kaplan and Zingales (1997). Table 5 provides detailed descriptions of the variables. [Table 5 around here]

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ACCEPTED MANUSCRIPT In order to estimate risk variables, we retrieved the daily values for holding period returns from the Centre for Research in Security Prices (CRSP) database. The factor loadings (daily frequency) on market risk, small-minus-big, high-minus-low, and momentum are from Wharton Research Data Services (WRDS). The financial information, including figures from financial

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statements, is obtained from COMPUSTAT-Capital IQ. The governance indicators are collected

3.1

Results and discussion

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3.

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from the MSCI GMI Ratings available on WRDS.

Descriptive statistics

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[Table 6 around here]

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[Table 7 around here]

Tables 6 and 7 provide mean comparison tests and a correlation analysis for our variables. The

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descriptive statistics show that SC stocks differ significantly from SNC stocks in all the variables

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except systematic risk, confirming our intuition that SC firms differ from SNC ones because of the screens they pass through and their different capital structures. Importantly, SC firms have

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higher governance scores. This finding is inconsistent with that of Hayat and Hassan (2017), who

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found no difference in governance. However, this result should be read with caution, as it is only a mean analysis and the results may change if we control for other factors. In a univariate setting,

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the agency cost variables show slightly higher values for SC firms, as does the asset utilization ratio. Idiosyncratic (firm-specific) risk is significantly lower for SC firms, whereas systematic risk is the same. Not surprisingly, leverage (ratio of debt to total assets) is lower in SC firms. The significantly lower KZ index suggests that the SC firms are less constrained. Interestingly, SC firms have lower assets, higher market-to-book ratio, higher asset growth, and higher R&D-tosales ratio, implying that these firms have higher growth potential than SNC firms. Importantly,

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ACCEPTED MANUSCRIPT the two groups have almost the same age and size, so their dissimilarities cannot be attributed to differences in those factors. The correlation analysis reveals important patterns. Neither governance nor leverage correlates with agency costs and the correlation between asset utilization and agency costs is

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negative and significant. The association between agency conflicts and financial constraints is

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inconclusive, as the correlation coefficient is negative in one case and positive in another.

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Surprisingly, firms with higher idiosyncratic and systematic risk are associated with lower agency costs. Firm age and asset growth seem to be associated with lower agency cost, whereas

Agency costs and corporate governance

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3.2

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total assets increase with an increase in agency costs.

[Table 8 around here]

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Table 8 reports the results of estimations using a fixed effect model in which the

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dependent variable is expense ratio. To begin with, the SC dummy is negative and significant, implying that SC firms exhibit lower agency expense ratios. Additionally, the results for

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interaction dummies reported in columns 3 and 6 highlight that high debt increases agency costs

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more for SC firms than for SNC firms, whereas dividend payout reduces agency costs more for SC firms than for SNC firms. That is, low debt and higher dividends are drivers of the lower

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expense ratio for SC firms.

The results in Table 9, related to our second agency cost proxy, the asset utilization ratio, show that the SC dummy is positive and significant, implying that managers of SC firms use assets better than those of SNC firms. The results of interaction terms reveal that good governance improves asset utilization much more for SC firms than for SNC firms, as does leverage. This finding is in line with the debt monitoring hypothesis. Moreover, higher CEO

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ACCEPTED MANUSCRIPT tenure, asset growth, and dividend payment improve asset utilization more for SC firms than for SNC firms. [Table 9 around here] The results for our third agency proxy, Q*Free Cash Flow, are equally interesting, as

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Table 10 shows. The SC dummy is negative and significant, implying that SC firms have lower

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agency costs are long CEO tenure and higher dividend payments.

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agency cost and invest excess free cash flow in better projects. The reasons behind these lower

[Table 10 around here]

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In sum, these results suggest that SC firms exhibit lower agency cost. The major drivers

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of their lower expense ratio are low debt and high dividends; the major drivers of their higher asset utilization are good governance, high debt, long CEO tenure, high asset growth, and high

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dividends; and the major drivers of their lower Q*Free Cash Flow are long CEO tenure and high

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dividends.

The results related to control variables are equally interesting. First, although good

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governance does not affect the expense ratio, it increases the asset utilization ratio and decreases

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the Q*FCF measure. Moreover, debt reduces the expense ratio and Q*FCF, in line with agency theory, which highlights the disciplining role of debt (Grossman & Hart, 1982; Jensen, 1986).

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These results support the evidence provided by Dey (2008) but contrast with the recent findings of McKnight and Weir (2009) and Rashid (2016), who show that governance (proxied in terms of institutional ownership, nomination committee, etc.) is associated with higher agency costs. Their findings are more in line with stewardship theory, which argues that a higher proportion of managerial ownership is more beneficial for the firm, as managers know exactly what works

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ACCEPTED MANUSCRIPT better for the firm. Our findings are also in contrast with Singh and Davidson III (2003) finding that large inside ownership is associated with lower agency costs in U.S. firms. The impact of CEO duality in two out of three specifications indicates that it increases agency costs, in line with traditional agency theory. However, the results also suggest that firms

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whose CEO doubles as board chair can better use their assets to generate revenues. CEO tenure

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seems to increase agency costs, albeit only when they are proxied by the asset utilization ratio.

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This finding is also in line with agency theory, as longer tenure may make the CEO more powerful and allow both the CEO and other managers to indulge in activities that may benefit

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themselves but are detrimental to the interest of shareholders. The coefficient for asset growth

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suggests that higher asset growth is associated with higher agency costs, in line with the work of Rashid (2013, 2016). As Demsetz and Lehn (1985) argue, larger firms, because of their larger

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scale of operations, provide wrong incentives and opportunity for managers to shirk. However,

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these results are inconsistent with Doukas et al. (2000) argument that agency conflicts are independent of firm size. Firm age has no association with agency conflicts.

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The results related to dividend payout are mixed. We find that higher dividend payout

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increases the expense ratio and reduces the asset utilization ratio. Nevertheless, higher dividends increase the firm’s ability to invest in high-growth projects. This finding contradicts claims that

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payout policies can mitigate agency costs (Hoberg & Prabhala, 2009; Hu & Kumar, 2004; La Porta et al. (2000); Michaely and Roberts (2012) and findings that better governed firms pay lower dividends and use the retained earnings to adopt better investment policies (John and Knyazeva (2006); John, Knyazeva, & Knyazeva, 2015; Officer (2011).

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Robustness checks

3.3.1 Agency costs and negative earnings To rule out the possibility that the results are distorted by firms with negative earnings and financial distress, we include in the estimation a dummy variable that takes the value of one

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for a firm reporting earnings and zero otherwise, and also include the KZ index. Results are

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reported in Table 11. Our motivation stems from DeAngelo, DeAngelo, and Skinner (1992) and

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Bhattacharya, Li, and Rhee (2016), who posit that negative earnings and financial constraints are a major reason for cuts in dividends, thereby affecting agency cost for the firm. The results

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confirm our main results suggesting that SC firms have lower agency costs.

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[Table 11 around here] 3.3.2 Agency costs and the KZ index

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As we note above, financial constraints can lead to dividend cuts and hence may increase

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agency costs. However, if firms facing constraints are likely to underinvest (Guariglia & Yang, 2016), they may not face the typical overinvestment issue of investing below the cost of capital

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or wasting funds on organizational inefficiencies (Jensen, 1986). In either case, our results may

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be driven by financing constraints faced by firms. Therefore, as an additional robustness check, we further split the sample according to financial constraints. To measure constraints, we employ

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the KZ index proposed by Kaplan and Zingales (1997). Results are reported in Table 12. Our findings reveal that SC firms exhibit lower agency costs, as reflected by their expense ratios and Q*Free Cash Flow, whether they face constraints or not. Governance remains an effective channel for reducing agency costs only when financial constraints are low. However, debt remains an effective channel at either level of financial constraint. [Table 12 around here]

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ACCEPTED MANUSCRIPT 3.3.3 Agency costs and idiosyncratic risk There is empirical evidence that idiosyncratic risk affects payout behavior, and hence agency conflicts, by increasing cash flow risk (Pástor & Pietro, 2003), carrying implications about future growth (Xu & Malkiel, 2003), and increasing firm-specific price discovery (Durnev,

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Morck, Yeung, & Zarowin, 2003). To test the possibility that firm-specific risk may drive the

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difference in agency conflicts across SC and SNC firms, we divide the sample according to firm-

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specific risk, measured using the Carhart four-factor model (Table 13). The results indicate that SC firms with low idiosyncratic risk face higher agency costs than SNC firms with low

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idiosyncratic risk.

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[Table 13 around here]

3.3.4 Estimations using lagged terms, industry fixed effects, an alternative governance proxy,

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and a GMM approach

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As we are using firm-level data, there may be endogeneity and reverse causality issues (see, e.g., Rashid, 2016). To address this issue, we reestimated all three models measuring

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independent variables at year t-1, and the results (Table 14, columns 1–3) remained similar to the

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main findings. We then reestimated all the models using industry fixed effects, in line with Rashid (2016), and again the results (reported in columns 4–6) remained robust. We also

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experimented with the alternate governance proxy provided by Thomson Reuters, referred to as the ESG Combined Score. This score is based on governance practices revealed in the news and public-domain information. The results (in the last three columns of Table 14) remained robust to this alternative specification as well. Finally, to provide an additional layer of robustness and tackle the endogeneity and reverse causality issue more efficiently, we also employed dynamic

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ACCEPTED MANUSCRIPT GMM. The results, reported in Table 15, remained robust and insensitive to the method employed. [Table 14 around here] [Table 15 around here] Conclusion

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4.

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Our findings show that agency costs are lower for SC equities, and that the drivers of this

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difference include good governance, higher dividends, longer CEO tenure, higher asset growth, and low debt. These results are robust even after we discount for idiosyncratic risk and use

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alternate proxies of agency costs, different measures of governance, lagged terms, industry and

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year fixed effects, and a GMM approach. When idiosyncratic risk is low, SC firms exhibit higher agency costs than corresponding SNC firms; but when idiosyncratic risk is high, the SC firms

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again exhibit lower agency costs than SNC firms.

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In order to extend our research, scholars could examine the agency costs–debt relationship in SC firms under different institutional and infrastructural settings and in other

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countries such as Malaysia, Saudi Arabia, or the UAE (the leading countries for Islamic

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finance)—if data were to become available on SC firms and corporate governance measures. The SC firms in such institutional environments may respond differently from those we examined in

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the U.S. market.

Acknowledgement The authors are grateful to BNP Paribas-INCEIF Centre for Islamic Asset and Wealth Management, for the research grant for the purchase of data.

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215.

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La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. W. (2000). Agency Problems and Dividend Policies around the World. The Journal of Finance, 55(1), 1-33.

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McKnight, P. J., & Weir, C. (2009). Agency Costs, Corporate Governance Mechanisms and Ownership Structure in Large Uk Publicly Quoted Companies: A Panel Data Analysis. The Quarterly Review of Economics and Finance, 49(2), 139-158. Merdad, H. J., Kabir Hassan, M., & Hippler, W. J. (2015). The Islamic Risk Factor in Expected Stock Returns: An Empirical Study in Saudi Arabia. Pacific-Basin Finance Journal, 34, 293-314. doi:10.1016/j.pacfin.2015.04.001

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ACCEPTED MANUSCRIPT Michaely, R., & Roberts, M. R. (2012). Corporate Dividend Policies: Lessons from Private Firms. Review of Financial Studies, 25(3), 711-746. doi:10.1093/rfs/hhr108 Mirakhor, A. (2010). Whither Islamic Finance? Risk Sharing in an Age of Crises. Paper presented at the Inaugural Securities Commission Malaysia (SC) –Oxford Centre for

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Islamic Studies (OCIS) Roundtable “Developing a Scientific Methodology on Shariah

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Governance for Positioning Islamic Finance Globally”, Kuala Lumpur, Malaysia.

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https://mpra.ub.uni-muenchen.de/56341/1/MPRA_paper_56341.pdf

of Corporate Finance, 17(3), 710-724.

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Officer, M. S. (2011). Overinvestment, Corporate Governance, and Dividend Initiations. Journal

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Pástor, Ľ., & Pietro, V. (2003). Stock Valuation and Learning About Profitability. The Journal of Finance, 58(5), 1749-1789.

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Rashid, A. (2013). Ceo Duality and Agency Cost: Evidence from Bangladesh. Journal of

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Management and Governance, 17(4), 989-1008. doi:https://doi.org/10.1007/s10997-0129213-x

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Rashid, A. (2016). Managerial Ownership and Agency Cost: Evidence from Bangladesh. Journal

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of Business Ethics, 137(3), 609-621. doi:https://doi.org/10.1007/s10551-015-2570-z Shleifer, A., & Vishny, R. W. (1997). A Survey of Corporate Governance. The Journal of

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Finance, 52(2), 737-783. Singh, M., & Davidson III, W. N. (2003). Agency Costs, Ownership Structure and Corporate Governance Mechanisms. Journal of Banking & Finance, 27(5), 793-816. Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). Cambridge MA: MIT press.

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ACCEPTED MANUSCRIPT Xu, Y., & Malkiel, B. G. (2003). Investigating the Behavior of Idiosyncratic Volatility. Journal of Business, 76(4), 613-644. Table 1 Screening criteria of index providers.

T

IP

Accounts Receivable + Cash/Total Assets < 70% Revenue from Prohibited Items + Total Interest/ Total Assets < 5% Cash + Interest Bearing Instruments/ Total Assets < 33.33%

AN

US

Accounts Receivable + Cash/Total Assets < 50% Revenue from Prohibited Items + Total Interest/ Total Assets < 5% Cash + Interest Bearing Instruments/ Total Assets < 33%

MSCI Islamic Index Debt/Total Assets < 33.33%

CR

FTSE Islamic Index Debt/Total Assets < 33%

M

Dow Jones Islamic Index Debt/2 Year Average Market Cap < 33% Liquidity Accounts (Accounts Receivable + Cash Receivable + /2 year Average Cash) Market Cap < 33% Impermissible Revenue from Income Prohibited Items + Total Interest/2 Year Average Market Cap < 5% Cash & Interest- Cash + Interest Bearing Bearing Instruments Instruments/2 Year Average Market Cap < 33%

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Financial Screen Leverage (Debt/Equity)

Bursa Malaysia Shariah Index Debt/Total Assets ≤ 33% Cash/Total Assets ≤ 33%

Revenue from Prohibited Items + Total Interest/ Total Assets < 5% N/A

AC

CE

PT

Notes: This table reports the details of the screening criteria of four different indexes, available on the providers’ websites and extracted from Ashraf and Khawaja (2016). The list of prohibited items includes alcohol; tobacco; pork related items; conventional banking and insurance (except for Islamic banks and Takaful companies); weapons and defense; and entertainment, including hotels, casinos/gambling, cinema, pornography, music, etc. MSCI criteria consider revenue from hotel business operating in Saudi Arabia permissible. Slight differences exist in the categorization of prohibited items between Bursa Malaysia and the other indices. Bursa Malaysia also considers the image or public perception of the company, its importance to the community, and its social responsibility.

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ACCEPTED MANUSCRIPT 22 Table 2 Numbers of constituent stocks in the sample portfolios, by year.

IP

T

SC 597 592 551 554 558 543 522 411 467 473

CR

US 1,632 1,530 1,482 1,378 1,371 1,343 1,275 1,259 1,263 1,273

US

Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

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CE

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ED

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Note: This table summarizes the numbers of stocks that were included in the Dow Jones US Index (DJUS) and Dow Jones Islamic Market Index (DJIMUS) for the period 2006–2015.

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ACCEPTED MANUSCRIPT 23 Table 3 Debt/assets ratio statistics for sample portfolios.

Mean 0.12 0.27 0.22

S.D. 0.14 0.20 0.19

Median 0.12 0.25 0.19

0.75 0.21 0.41 0.34

Max 0.32 0.90 0.90

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SC SNC US

Observations 4,553 7,237 11,790

Quantiles Min 0.25 0.00 0.01 0.00 0.08 0.00 0.05

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CE

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ED

M

AN

US

CR

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Notes: The portfolios for SC firms, SNC firms, and the U.S. market as a whole are constructed by using the constituent stocks of the Dow Jones US Index (DJUS) and Dow Jones Islamic Market Index-US (DJIMUS) for the period 2006–2015.

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Table 4 Governance index. Data Source

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M

AN

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MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI

IP

CR

S. Variable Ownership Related Variables 1 No Insider Control 2 Ownership Diversity 3 Outsider Majority 4 Outsider Majority Strict 5 Directors Active CEOs 6 Presence of Women Directors Internal Governance Mechanisms 7 Business Ethics Code Available 8 Board Meetings Frequency 9 Outsiders Board Members Meetings Frequency 10 Audit Committee—Independent 11 Audit Committee—Fully Independent 12 Compensation Committee—Independent 13 Compensation Committee—Fully Independent 14 Nomination & Governance Committee—Independent 15 Nomination & Governance Committee—Fully Independent 16 Company Compensation Plan Approved 17 Formal Governance Policy Approved Audit Quality 18 Auditor Independence 19 Big4Auditors 20 Auditor Opinion 21 Auditor Opinion—Internal Control

MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI MSCI GMI Compustat Compustat

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Notes: This table reports the constituents of the independent variable corporate governance index. It is developed in line with John, Knyazeva, and Knyazeva (2015). The variables in general take the value 1 if yes and 0 otherwise. Owner Diversity takes the value 1 if ownership category is either “Institutions Dominant” or “Widely Held” or “Indexed Stock” or “Mixed Ownership.” If Board Meetings Frequency is 4 or above, the value assigned is equal to 1 and otherwise 0. Big4Auditors takes the value of 1 if the external auditor is among the top four audit firms (or their subsidiaries), namely, Deloitte & Touche LLP, Ernst & Young LLP, KPMG LLP, and PricewaterhouseCoopers LLP. Auditor Opinion (Compustat item No. 20) is assigned the value 1 if it is “unqualified (1)” or “unqualified with additional language (4)” and 0 otherwise. Auditor Opinion-Internal Control— (Compustat item No. 21) is 1 if opinion is “Effective (1)”

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and 0 otherwise. The governance score is converted into percentiles following Gompers, Ishii, and Metrick (2003).

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ACCEPTED MANUSCRIPT 26 Table 5 Description of variables.

Idiosyncratic Risk (IR) Systematic Risk Asset Growth Firm Age Firm Size

CR

IP

T

Source Rashid (2016) McKnight and Weir (2009) Doukas et al. (2000)

John et al. (2015)

Hayat and Hassan (2017)

Hu and Kumar (2004)

Hoberg and Prabhala (2009)

(McKnight & Weir, 2009)

Debt in Current Liabilities (34)+ Total Long-Term Debt (9)/Total Assets (6)

CE

Debt/Assets

US

CEO Duality

AN

CEO Tenure

M

ESG Combined Score

Interaction of free cash flow and a dummy variable “low growth opportunities” that takes the value 1 if the firm is making a positive total payout (dividends plus repurchases) in year t and 0 otherwise. Governance ranking based on 21 governance-related variables (details available in Table 4). The data are obtained from MSCI GMI Ratings (Companies). Governance ranking based on 178 firm-level ESG measures that take into account materiality, data availability, and industry relevance. The data are obtained from Thomson Reuters EIKON. Number of years CEO has served in the firm. The data come from Execucomp (Compustat). Dummy that takes the value 1 if CEO is chair of the board of directors and 0 otherwise. The data are obtained from MSCI GMI Ratings (Companies). The standard deviation of residuals from a regression of firm-specific daily excess stock returns on Carhart’s four factors. The standard deviation of the predicted value from the above-mentioned regression defining IR. ∆Total Assets/Total Assets at year t-1 Log(1+Listing Age of Firm) Log (Total Assets)

ED

Governance Index

Definition Operating Expenses (189)/Total Sales (12) Total Sales (12)/Total Assets (6)

PT

Variable Expense Ratio Asset Utilization Ratio Q*Free Cash Flow

Notes: The numbers in parentheses are Compustat item numbers.

where

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KZ Index = −1.002(CF/K) − 39.368 (DIV/K) − 1.315 (CA/K) + 3.139LEV + 0.283Q

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ACCEPTED MANUSCRIPT 27

where

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??, i.e., Market-to-book ratio of assets, can be calculated as

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CE

PT

ED

M

AN

US

CR

IP

where

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ACCEPTED MANUSCRIPT 28 Table 6 Mean comparison tests.

M

IP

T

Difference 0.0321*** 0.0891*** 0.0564*** 0.2083*** -0.0009*** -0.001*** -0.0009*** 0.000 0.000 0.000 0.6660*** -0.1454*** 0.0709 -0.7463*** 0.0347*** 0.2267*** -11.7474*** 0.0403***

US

CR

SNC 0.1179 0.9072 0.0565 16.8145 0.0180 0.0187 0.0182 0.0143 0.0134 0.0141 1.638 0.3123 3.2110 8.8662 0.0652 0.4098 54.7845 0.0290 4,653

AN

SC 0.1500 0.9963 0.1129 17.0228 0.0171 0.0177 0.0173 0.0143 0.0134 0.0141 2.3041 0.1669 3.2819 8.1199 0.0999 0.6365 43.0371 0.0693 4,405

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Expense Ratio Asset Utilization Ratio Q*FCF Governance Index Idiosyncratic Risk (Carhart) Idiosyncratic Risk (CAPM) Idiosyncratic Risk (Fama French) Systematic Risk (Carhart) Systematic Risk (CAPM) Systematic Risk (Fama French) Market/Book Assets Ratio Debt/Assets Firm Age Book Value of Assets Asset Growth Retained Earnings/Total Equity KZ Index R&D/Sales N

Notes: This table shows the means for U.S. market proxy, SC firms, and SNC firms. The “difference of

AC

CE

PT

means” tests are performed using a parametric t-test for unequal variance. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

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ACCEPTED MANUSCRIPT 29 Table 7 Correlation matrix: market portfolio. Exp. Ratio Expense Ratio

1

AUR

0.013 (0.269) 0.0069 (0.554) -0.0279 (0.017) -0.0103 (0.380) -0.0231 (0.048) 0.0148 (0.209) 0.0379 (0.001) 0.0141 (0.230) 0.0141 (0.228)

Gov. Index Idio. Risk Systematic Risk KZ Index Firm Age Total Assets Asset Growth Debt/Assets

AUR

Gov. Index

Idio. Risk

Sys. Risk

KZ Ind.

Total Assets

Age

Asset Growth

Debt/Assets

T P

I R

1 0.0142 (0.225) 0.0864 (<0.001) -0.0366 (0.001) -0.0283 (0.015) 0.0379 (0.001) -0.2773 (<0.001) -0.0449 (<0.001) -0.0386 (<0.001)

-0.0268 (0.021) 0.1077 (<0.001) -0.0391 (<0.001) 0.344 (<0.001) 0.204 (<0.001) -0.0552 (<0.001) -0.0573 (<0.001)

1 0.7383 (<0.001) 0.1185 (<0.001) -0.1252 (<0.001) -0.2358 (<0.001) -0.0024 (0.837) 0.0638 (<0.001)

D E

T P

E C

C A

C S

1

1

M

A

U N

0.034 (0.003) -0.009 (0.441) -0.0448 (<0.001) -0.0412 (<0.001) -0.0025 (0.829)

1 -0.0875 (<0.001) -0.0661 (<0.001) -0.0516 (<0.001) 0.3925 (<0.001)

1 0.1891 (<0.001) -0.0782 (<0.001) -0.096 (<0.001)

1 -0.006 (0.607) -0.0574 (<0.001)

1 -0.0233 (0.046)

1

Notes: The table shows pairwise correlations between our variables of interest using Pearson correlation coefficients for the market portfolio. The p-values are reported in parentheses below each variable. The variable definitions are available in the methods section.

29

ACCEPTED MANUSCRIPT 30 Table 8 Agency conflicts, debt levels, and corporate governance—what drives the lower expense ratio of SC firms? Expense Ratio Governance Index Debt/Assets CEO Duality CEO Tenure Firm Age Sales Asset Growth Dividend Payout SC Dummy

(1) -0.000121 (0.164) -0.273*** (0.000) 0.0187*** (0.005) -0.000508 (0.346) -0.00715 (0.115) 0.133*** (0.000) 0.0775*** (0.000) 0.000182 (0.693) -0.0241*** (0.000)

SC*Tenure SC*Asset Growth

(3) 0.0000207 (0.813) -0.395*** (0.000) 0.0111* (0.096) 0.000000336 (1.000) 0.00121 (0.792) 0.0878*** (0.000) 0.230*** (0.000) 0.0395*** (0.001) -0.000701 (0.944)

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C A

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(4) 0.0000249 (0.777) -0.335*** (0.000) 0.0116* (0.082) -0.000527 (0.437) 0.00118 (0.796) 0.0874*** (0.000) 0.233*** (0.000) 0.0410*** (0.000) -0.0191** (0.014)

(5) 0.0000217 (0.804) -0.335*** (0.000) 0.0117* (0.080) -0.0000186 (0.973) 0.00118 (0.797) 0.0873*** (0.000) 0.243*** (0.000) 0.0403*** (0.001) -0.0271*** (0.000)

T P

I R

C S

U N

A

D E

E C

SC*Governance Index SC*Debt/Assets

(2) 0.0000238 (0.835) -0.336*** (0.000) 0.0117* (0.081) -0.0000136 (0.980) 0.00115 (0.801) 0.0873*** (0.000) 0.233*** (0.000) 0.0407*** (0.000) -0.0252*** (0.006) -0.00000398 (0.979)

0.891***

(7) 0.000000291 (0.997) -0.336*** (0.000) 0.0114* (0.089) 0.0000100 (0.985) 0.00113 (0.806) 0.0893*** (0.000) 0.234*** (0.000) 0.0420*** (0.000) -0.00885 (0.390)

-0.0547*** (0.005) -0.564***

-0.578***

0.116*** (0.001) 0.000966 (0.201) -0.0209 (0.426)

SC*Dividend Payout Constant

(6) 0.0000177 (0.840) -0.331*** (0.000) 0.0117* (0.081) -0.0000145 (0.979) 0.000716 (0.876) 0.0870*** (0.000) 0.230*** (0.000) 0.0621*** (0.000) -0.0349*** (0.000)

-0.564***

-0.549***

-0.562***

-0.565***

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Observations R2

(0.000) 9,058 0.092

(0.000) 9,058 0.073

(0.000) 9,058 0.075

(0.000) 9,058 0.073

(0.000) 9,058 0.073

(0.000) 9,058 0.074

(0.000) 9,058 0.074

Notes: This table reports a panel regression with fixed effects for a portfolio of U.S. firms. P-values are reported in parentheses below each coefficient. The dependent variable is Expense Ratio. Detailed descriptions of variables are available in the methods section. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

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ACCEPTED MANUSCRIPT 32 Table 9 Agency conflicts, debt levels, and corporate governance—what drives the higher asset utilization ratio for SC firms? Asset Utilization Ratio Governance Index Debt/Assets CEO Duality CEO Tenure Firm Age Sales Asset Growth Dividend Payout SC Dummy

(1) 0.000181* (0.063) -0.230*** (0.000) 0.0318*** (0.000) -0.00540*** (0.000) -0.00529 (0.300) 0.0820*** (0.000) -0.104*** (0.000) -0.000506 (0.330) 0.0287*** (0.000)

SC*Debt/Assets SC*Tenure SC*Asset Growth

(3) 0.000155 (0.104) -0.580*** (0.000) 0.0274*** (0.000) -0.00491*** (0.000) -0.00486 (0.331) 0.0892*** (0.000) -0.270*** (0.000) -0.103*** (0.000) -0.0103 (0.348)

M

(4) 0.000161* (0.092) -0.504*** (0.000) 0.0280*** (0.000) -0.00567*** (0.000) -0.00489 (0.329) 0.0887*** (0.000) -0.266*** (0.000) -0.101*** (0.000) 0.0137 (0.106)

(5) 0.000158* (0.099) -0.506*** (0.000) 0.0280*** (0.000) -0.00491*** (0.000) -0.00501 (0.317) 0.0886*** (0.000) -0.298*** (0.000) -0.0997*** (0.000) 0.0158** (0.031)

T P

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C S

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A

D E

T P

E C

SC*Governance Index

(2) -0.0000453 (0.716) -0.503*** (0.000) 0.0285*** (0.000) -0.00493*** (0.000) -0.00495 (0.323) 0.0885*** (0.000) -0.266*** (0.000) -0.0999*** (0.000) 0.00390 (0.694) 0.000425** (0.011)

C A

0.391***

(7) 0.0000555 (0.563) -0.508*** (0.000) 0.0267*** (0.000) -0.00482*** (0.000) -0.00506 (0.310) 0.0980*** (0.000) -0.261*** (0.000) -0.0950*** (0.000) -0.0534*** (0.000)

0.0778*** (0.000) 0.435***

0.366***

0.147*** (0.000) 0.00140* (0.089) 0.0642** (0.025)

SC*Dividend Payout Constant

(6) 0.000151 (0.114) -0.498*** (0.000) 0.0281*** (0.000) -0.00493*** (0.000) -0.00555 (0.267) 0.0881*** (0.000) -0.270*** (0.000) -0.0706*** (0.000) 0.0363*** (0.000)

0.444***

0.454***

0.439***

0.439***

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Observations R2

(0.000) 9,058 0.071

(0.000) 9058 0.110

(0.000) 9058 0.111

(0.000) 9058 0.109

(0.000) 9058 0.110

(0.000) 9058 0.111

(0.000) 9058 0.117

Notes: This table reports a panel regression with fixed effects for a portfolio of U.S. firms. P-values are reported in parentheses below each coefficient. The dependent variable is Asset Utilization Ratio. Detailed descriptions of variables are available in the methods section. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

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ACCEPTED MANUSCRIPT 34 Table 10 Agency conflicts, debt levels, and corporate governance—what drives lower Q*FCF for SC firms? Q*Free Cash Flow Governance Index Debt/Assets CEO Duality CEO Tenure Firm Age Sales Asset Growth Dividend Payout SC Dummy

(1) -0.0000937*** (0.006) -0.109*** (0.000) 0.00961*** (0.000) -0.000152 (0.475) -0.00200 (0.263) 0.0328*** (0.000) 0.0264*** (0.000) 0.0000588 (0.746) -0.0135*** (0.000)

SC*Debt/Assets SC*Tenure

(3) -0.000074*** (0.001) -0.105*** (0.000) 0.000746 (0.662) 0.000168 (0.228) -0.000362 (0.757) 0.0148*** (0.000) 0.0572*** (0.000) -0.00772*** (0.010) 0.00679*** (0.008)

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(4) -0.000072*** (0.001) -0.0972*** (0.000) 0.000789 (0.644) -0.0000204 (0.906) -0.000358 (0.759) 0.0148*** (0.000) 0.0575*** (0.000) -0.00747** (0.012) 0.00770*** (0.000)

(5) -0.000073*** (0.001) -0.0977*** (0.000) 0.000800 (0.639) 0.000169 (0.226) -0.000380 (0.745) 0.0147*** (0.000) 0.0527*** (0.000) -0.00737** (0.013) 0.00889*** (0.000)

T P

I R

C S

U N

A

D E

T P

E C

SC*Governance Index

(2) -0.0000824*** (0.005) -0.0974*** (0.000) 0.000827 (0.628) 0.000166 (0.232) -0.000370 (0.752) 0.0147*** (0.000) 0.0575*** (0.000) -0.00752** (0.012) 0.00905*** (0.000) 0.0000189 (0.630)

C A

-0.0133*** (0.007) -0.0172

0.00608

0.000351* (0.068) 0.00971 (0.147)

SC*Dividend Payout 0.159***

(7) -0.0000396* (0.076) -0.0962*** (0.000) 0.00129 (0.444) 0.000129 (0.348) -0.000327 (0.778) 0.0116*** (0.000) 0.0558*** (0.000) -0.00954*** (0.001) 0.0351*** (0.000)

0.0139 (0.129)

SC*Asset Growth

Constant

(6) -0.0000744*** (0.001) -0.0963*** (0.000) 0.000805 (0.637) 0.000166 (0.233) -0.000475 (0.684) 0.0147*** (0.000) 0.0569*** (0.000) -0.00239 (0.501) 0.0123*** (0.000)

-0.0167

-0.0153

-0.0163

-0.0166

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Observations R2

(0.000) 9,058 0.065

(0.255) 9058 0.077

(0.296) 9058 0.077

(0.266) 9058 0.077

(0.257) 9058 0.077

(0.240) 9058 0.078

(0.678) 9058 0.094

T P

Notes: This table reports a panel regression with fixed effects for a portfolio of U.S. firms. P-values are reported in parentheses below each coefficient. The dependent variable is Asset Utilization Ratio. Detailed descriptions of variables are available in the methods section. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

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A

D E

M

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E C

C A

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ACCEPTED MANUSCRIPT 36 Table 11 Assessment of agency conflicts in SC and SNC companies—robustness tests using a negative earnings dummy.

Firm Age Sales Asset Growth Dividend Payout KZ Index

PT

Negative Earnings Dummy SC Dummy

Observations R2

CE

Constant

US

CEO Tenure

AN

T

(3) Q*Free Cash Flow -0.0000751** (0.024) -0.0698*** (0.000) 0.00869*** (0.001) -0.0000888 (0.669) -0.00274 (0.117) 0.0270*** (0.000) 0.0185*** (0.000) -0.000304* (0.085) -0.000500*** (0.000) -0.0495*** (0.000) -0.0124*** (0.000) 0.0867*** (0.000) 8,851 0.128

IP

CEO Duality

M

Debt/Asset

-0.0000734 (0.383) -0.179*** (0.000) 0.0169*** (0.009) -0.000594 (0.258) -0.00801* (0.069) 0.116*** (0.000) 0.0572*** (0.000) -0.000703 (0.115) -0.000717*** (0.000) -0.145*** (0.000) -0.0211*** (0.000) 0.718*** (0.000) 8,851 0.158

ED

Governance Index

(2) Asset Utilization Ratio 0.000172* (0.075) -0.217*** (0.000) 0.0340*** (0.000) -0.00532*** (0.000) -0.00883* (0.082) 0.0825*** (0.000) -0.105*** (0.000) -0.000642 (0.210) -0.000385** (0.024) -0.00728 (0.344) 0.0292*** (0.000) 0.414*** (0.000) 8,851 0.075

CR

(1) Expense Ratio

AC

Notes: This table reports a panel regression with fixed effects for a market portfolio using additional variables. P-values are reported in parentheses below each coefficient. The dependent variable is agency cost as represented by Expense Ratio, Asset Utilization Ratio, and Q*Free Cash Flow. Detailed descriptions of variables are available in the methods section. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

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ACCEPTED MANUSCRIPT 37 Table 12 Assessment of agency conflicts in SC and SNC companies under financial constraints. (1)

(2) (3) (4) (5) (6) Low Financial Constraints High Financial Constraints Expense Ratio Asset Utilization Q*Free Cash Expense Ratio Asset Utilization Q*Free Cash Ratio Flow Ratio Flow *** * Governance Index -0.000241 0.000186 -0.0000920 0.0000166 0.000165 -0.000144* (0.000) (0.327) (0.061) (0.957) (0.418) (0.050) ** *** *** *** *** Debt/Asset -0.0314 -0.322 -0.0524 -0.369 0.161 -0.0867*** (0.040) (0.000) (0.000) (0.000) (0.000) (0.000) CEO Duality 0.00273 0.0381** 0.00635* 0.0596** 0.00925 0.0146** (0.591) (0.011) (0.100) (0.019) (0.581) (0.016) CEO Tenure -0.000512 -0.00490*** -0.000778** -0.00152 -0.00540*** 0.0000438 (0.203) (0.000) (0.011) (0.475) (0.000) (0.931) Firm Age -0.00372 -0.00758 -0.000105 -0.0189 -0.0217** -0.00403 (0.334) (0.502) (0.971) (0.252) (0.046) (0.303) Sales 0.0599*** 0.0797*** 0.0289*** 0.229*** 0.0815*** 0.0398*** (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) Asset Growth 0.00120 -0.0676*** 0.00174 0.208*** -0.103*** 0.0408*** (0.696) (0.000) (0.457) (0.000) (0.000) (0.000) * Dividend Payout -0.00124 -0.00321 -0.000162 -0.00278 -0.00135 -0.00100 (0.076) (0.119) (0.761) (0.474) (0.598) (0.276) *** ** *** *** Negative Earnings -0.127 -0.0442 -0.0595 -0.207 -0.00329 -0.0427*** Dummy (0.000) (0.035) (0.000) (0.000) (0.804) (0.000) ** ** ** *** SC Dummy -0.00938 -0.00141 -0.00836 -0.0550 0.0796 -0.0293*** (0.044) (0.918) (0.018) (0.038) (0.000) (0.000) *** *** *** *** Constant 0.284 0.482 0.0991 1.582 0.143 0.234*** (0.000) (0.000) (0.001) (0.000) (0.238) (0.000) Observations 2,221 2,221 2,221 2,187 2,187 2,187 R2 0.243 0.086 0.124 0.207 0.072 0.171 Notes: This table reports a panel regression with fixed effects for a market portfolio under financial constraints. P-values are reported in parentheses below each coefficient. The dependent variable is agency cost as represented by Expense Ratio, Asset Utilization Ratio,

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ACCEPTED MANUSCRIPT 38 and Q*Free Cash Flow. Detailed descriptions of variables are available in the methods section. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

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ACCEPTED MANUSCRIPT 39 Table 13 Assessment of agency conflicts in SC and SNC companies under variant idiosyncratic risk. (1) Expense Ratio Governance Index Debt/Asset CEO Duality CEO Tenure Firm Age Sales Asset Growth Dividend Payout Negative Earnings Dummy SC Dummy Constant Observations R2

0.0000132 (0.652) 0.0317*** (0.005) 0.00660** (0.014) 0.0000162 (0.936) 0.0107*** (0.000) -0.0241*** (0.000) -0.00656* (0.054) -0.000653** (0.015) -0.0417*** (0.000) 0.00729*** (0.010) 0.324*** (0.000) 2,229 0.068

(2) (3) Low Idiosyncratic Risk Asset Utilization Q*Free Cash Ratio Flow -0.0000888 0.0000717** (0.457) (0.021) *** -0.518 -0.0289** (0.000) (0.016) 0.0271** 0.00413 (0.013) (0.147) -0.00459*** -0.000321 (0.000) (0.134) -0.0348*** 0.00718** (0.004) (0.022) 0.125*** -0.00446 (0.000) (0.233) -0.118*** 0.00959*** (0.000) (0.008) *** -0.00444 -0.000248 (0.000) (0.384) -0.0200 0.00562 (0.452) (0.415) *** -0.0401 0.00938*** (0.001) (0.002) 0.0658 0.105*** (0.606) (0.001) 2,229 2,229 0.178 0.024

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-0.000436 (0.294) -0.327*** (0.000) 0.0846*** (0.004) -0.00559** (0.036) -0.00304 (0.858) 0.240*** (0.000) 0.0857*** (0.000) -0.00156 (0.532) -0.164*** (0.000) -0.0151 (0.502) 1.631*** (0.000) 2,192 0.195

(5) (6) High Idiosyncratic Risk Asset Utilization Q*Free Cash Ratio Flow 0.000153 -0.000141 (0.613) (0.368) *** 0.185 -0.0843*** (0.000) (0.001) 0.0458** 0.0472*** (0.031) (0.000) -0.00742*** -0.00253** (0.000) (0.012) -0.0172 -0.00811 (0.164) (0.204) 0.135*** 0.0484*** (0.000) (0.000) -0.0746*** 0.0230*** (0.000) (0.000) 0.000110 -0.000967 (0.952) (0.304) *** -0.0369 -0.0697*** (0.008) (0.000) 0.0195 -0.00505** (0.233) (0.050) 0.00731 0.247*** (0.951) (0.000) 2,192 2,192 0.107 0.143

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ACCEPTED MANUSCRIPT 40 Notes: This table reports a panel regression with fixed effects for a market portfolio under variant financial constraints. P-values are reported in parentheses below each coefficient. The dependent variable is agency cost as represented by Expense Ratio, Asset Utilization Ratio, and Q*Free Cash Flow. Detailed descriptions of variables are available in the methods section. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively. Table 14 Assessment of agency conflicts in SC and SNC companies—additional robustness tests.

Governance Index

(1) (2) (3) Independent Variables at Previous Year Expense Asset Q*Free Ratio Utilization Cash Flow Ratio -0.0002** -0.0008*** -0.0001 (0.019) (0.000) (0.743)

Debt/Assets CEO Duality CEO Tenure Firm Age Sales Asset Growth Dividend Payout SC Dummy

0.0247 (0.400) 0.0032 (0.650) 0.0003 (0.555) -0.0037 (0.469) -0.0275*** (0.001) 0.0498*** (0.001) -0.0025 (0.848) -0.0466*** (0.000)

-0.2280*** (0.000) 0.0266*** (0.001) -0.0035*** (0.000) -0.0025 (0.663) 0.0160* (0.072) 0.0057 (0.733) -0.0759*** (0.000) 0.0379*** (0.000)

-0.0323*** (0.000) -0.0009 (0.655) 0.0002 (0.157) -0.0004 (0.767) -0.0063*** (0.003) 0.0014 (0.730) -0.0014 (0.680) -0.0152*** (0.000)

0.0001 (0.410)

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-0.240*** (0.000) 0.0103 (0.110) 0.0005 (0.307) 0.0035 (0.416) 0.0689*** (0.000) 0.215*** (0.000) 0.0489*** (0.000) -0.0303*** (0.000)

(7) (8) (9) Alternate Governance Proxy with Industry and Year Fixed Effects Asset Q*Free Expense Asset Q*Free Utilization Cash Flow Ratio Utilization Cash Flow Ratio Ratio -0.0003*** 0.0001 (0.010) (0.809) 0.0001 0.0001 0.0001 (0.462) (0.750) (0.434) -0.408*** -0.0760*** -0.149*** -0.419*** -0.0686*** (0.000) (0.000) (0.000) (0.000) (0.000) 0.0048 -0.0005 0.0136** -0.0051 -0.0012 (0.489) (0.742) (0.040) (0.544) (0.529) *** ** *** -0.0032 0.0003 -0.0005 -0.0031 0.0004*** (0.000) (0.034) (0.341) (0.000) (0.003) ** *** 0.0097 0.0015 0.0023 0.0182 0.0021 (0.036) (0.140) (0.639) (0.003) (0.109) *** *** *** *** 0.126 0.0076 0.0846 0.112 0.0066*** (0.000) (0.000) (0.000) (0.000) (0.000) *** *** *** *** -0.317 0.0520 0.170 -0.312 0.0468*** (0.000) (0.000) (0.000) (0.000) (0.000) *** * *** -0.0373 -0.0048 0.0352 -0.0174 -0.0075** (0.002) (0.086) (0.003) (0.254) (0.033) 0.0164*** -0.0162*** -0.023*** 0.0309*** -0.0236*** (0.009) (0.000) (0.001) (0.000) (0.000)

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0.3280*** (0.000) 7,594

0.940*** (0.000) 7,594

0.1350*** (0.000) 7,594

-0.464*** (0.001) 9,058

0.256 (0.208) 9,058

-0.595** (0.049) 5,589

0.0098 (0.708) 9,058

-0.294 (0.409) 5,589

0.0643 (0.173) 5,589

Notes: This table reports a panel regression with fixed effects for a market sample. P-values are reported in parentheses below each coefficient. The dependent variable is agency cost as represented by Expense Ratio, Asset Utilization Ratio, and Q*Free Cash Flow. Detailed descriptions of variables are available in the methods section. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

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ACCEPTED MANUSCRIPT 42 Table 15 Assessment of agency conflicts in SC and SNC companies—additional robustness tests using a generalized method of moments (GMM) approach. (1) Expense Ratio

(2) Asset Utilization Ratio

0.152*** (0.000)

CEO Tenure Firm Age

Asset Growth

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SC Dummy

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Observations AR (1) [P Value] AR(2) [P Value] Sargan Test [P Value]

0.365*** (0.000) -0.0000968*** (0.000) -0.131*** (0.000) 0.00146 (0.578) 0.000101 (0.686) -0.000718 (0.695) 0.0184*** (0.000) 0.0320*** (0.000) -0.00682 (0.111) -0.000680* (0.093) -0.0623** (0.021) 7,597 0.0480 0.6895 0.5951

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CEO Duality

0.000375*** (0.000) -0.279*** (0.000) 0.0234*** (0.008) -0.00243*** (0.001) -0.00417 (0.468) 0.356*** (0.000) -0.424*** (0.000) -0.0696*** (0.000) 0.00420** (0.030) -2.418*** (0.000) 7,597 0.0490 0.6579 0.6215

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Debt/Assets

-0.000102*** (0.000) -0.208*** (0.000) 0.00472 (0.343) 0.000338 (0.450) 0.00342 (0.355) 0.0859*** (0.000) 0.0799*** (0.000) 0.00187 (0.787) -0.00894* (0.068) -0.571*** (0.000) 7,597 0.0450 0.7401 0.6501

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L.Asset Utilization Ratio L.Q*Free Cash Flow

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L.Expense Ratio

Constant

(3) Q*Free Cash Flow

Notes: This table reports results of estimations using a GMM approach. P-values are reported in parentheses below each coefficient. The dependent variable is agency cost as represented by Expense Ratio, Asset Utilization Ratio, and Q*Free Cash Flow. Detailed descriptions of variables are available in the methods section. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.

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