The Effect of Financial Leverage and Liquidity on
the Quality of Strategic Risk Disclosure
Master Thesis for the master Controlling at the University of Groningen
Author:
Rocco Zwart
Student number:
S3541525
Email:
r.d.zwart@student.rug.nl
Date:
12-06-2019
Supervisor:
Prof. dr. J.A. Emanuels
ABSTRACT
This study examines whether there is a positive relation between a firm’s financial leverage and liquidity level and the quality of its strategic risk disclosures using annual reports. Signalling theory and prior research has been used to develop and test hypothesises. These tests are controlled for firm size and firm performance. A sample consisting of 342 firm year observations from 114 firms selected from the Fortune 500 is used. Annual reports in the time period 2015-2017 have been used to determine scores for the quality of strategic risk
disclosures using a self-constructed index. The main finding indicates that there is a positive association between the liquidity level of a firm and the quality of strategic risk reporting. This suggest that liquidity does not only impact strategic risk disclosure on a quantitative level, but also on a qualitative level. Therefore, this study bridges the gap between a more generalised measure of risk disclosure with quantitative proxies towards a more specific measure of risk disclosure using a qualitative proxy.
TABLE OF CONTENT
1. INTRODUCTION 4 2. THEORETICAL BACKGROUND 6 2.1 Risk disclosure 6 2.2 Signalling Theory 6 2.3 Financial Leverage 8 2.4 Liquidity 9 2.5 Research Model 9 3. METHODOLOGY 113.1 Data collection & sample 11
3.2 Measure of variables 11
3.2.1 Dependent variable: quality of Strategic Risk Disclosure 11 3.2.2 Independent variables: financial leverage and liquidity 13
3.2.3 Control variables 14
3.3 Statistical Analysis 15
4. RESULTS 17
4.1 Descriptive analysis 16
4.2 General results of tested hypothesises 18
4.3 Sensitivity checks 20
4.4 Additional test 21
5. DISCUSSION & CONCLUSION 23
ACKNOWLEDGEMENTS 25
APPENDIX 26
4
1. INTRODUCTION
In recent years, risk management and risk reporting have been interesting and popular themes among researchers (Linsley & Shrives, 2006). Incentives for risk reporting have been discussed by Dobler (2008). Adding to these incentives, a voluntarily provision of
information on risk management can also be triggered by recent accounting scandals, such as Enron (2001), Worldcom & Tyco (2002), Healthsouth & Freddie Mac (2003), AIG (2005) and Lehman Brothers (2008). Research on voluntary disclosure has been a popular research theme in recent years (Bronson et al., 2006). Disclosure can be beneficial for organisations, as it potentially decreases agency problems (Jensen & Meckling, 1976), agency costs
(Hooghiemstra et al., 2015) and monitoring costs (Foster, 1986; Ahmed & Courtis, 1999). Moreover, disclosure can be a way to explain the current situation of the firm, to justify decisions and to ensure reliability (Amran et al. 2009).
The annual report of a firm is the primary source of disclosure, both financial and non-financial. The annual report is produced every year and provides useful information to
potential investors for better decision-making (Amran et al., 2009). Part of the disclosed information is mandatory and therefore subject to regulation. In order to meet the information needs of shareholders, the traditional financial section alone is inadequate (Maines et al., 2002). This study focuses on the risk reporting section of the annual report, with an emphasis on the quality of the strategic risk disclosures within the annual report narratives.
The financial position of a firm is an important driver on risk reporting, in order to meet the interests of both shareholders and potential investors. In this study, we focus on both financial leverage and liquidity as a measure to assess a firm’s financial position. While the level of financial leverage determines the amount of debt used by a firm, liquidity refers to the ability to pay off debt as and when they come due (Elshandidy et al., 2013).
Previous research on both financial leverage and liquidity was conducted to determine whether a firm’s financial position has an influence on its risk disclosure. According to empirical research, both financial leverage and liquidity impact disclosure levels (Ferguson et al., 2002; Malone, Fries, & Jones, 1993; Wallace et al., 1994). This study aims to bridge the gap between the impact of both financial leverage and liquidity on disclosure levels on a quantitative basis and the actual impact on the quality of these disclosures, focusing on the strategic risk reporting within the annual report of a firm.
5
The goal of this study is therefore to refine the current understanding of the effect of both financial leverage and liquidity on the quality of strategic risk reporting. We use a self-constructed weighted categorical index, following up on that is based on the work of Hooghiemstra et al. (2015).
A likely hypothesis would be that the causality of this research works in both ways, in which case strategic risk reporting can influence financial leverage levels of a firm. However, this relation will not be studied. Our aim is to gain insight in the effect of both leverage and liquidity levels on the quality of strategic disclosure in order to influence firm disclosure in practice, along with investment decisions for potential investors.
This paper makes several theoretical and practical contributions. First, it tries to extend the existing literature on risk disclosure by relating both financial leverage and liquidity to strategic risk disclosure. Second, this research aims to bridge the gap with strategic risk disclosure, as previous studies only focused on risk disclosure in general and therefore didn’t address any specific parts of risk disclosure, such as strategic risk reporting. This contributes to scholarship of an unknown research area. Third and last, this study may give a more reliable proxy of qualitative risk reporting by using a categorical index. Contrary to previous studies that focused on quantitative measures of risk reporting, this study aims to assess risk reporting on a qualitative basis.
The next chapter provides the context of some of the theories that are used and contains a literature review on risk disclosure, financial leverage and liquidity. Following up on this, the research hypothesises are forwarded. Chapter three describes the data collection, sample and research methodology, while in chapter four the results of the research are presented and discussed. The paper ends in chapter five with concluding remarks, discussion and suggestions for future research.
6
2. THEORETICAL BACKGROUND
In this chapter a literature review on risk disclosure, financial leverage and liquidity is presented. Based on this review, hypothesises for this study are developed. Subsequently, the research model of the study for each of the hypothesis will be presented.
2.1 Risk disclosure
One of the main opportunities for an organisation to provide additional disclosures on risk management is the annual report. Publishing an annual report is mandatory and expected to provide useful information for users to increase decision-making (Amran et al., 2009). In order to meet the information needs of shareholders, the traditional financial section alone is inadequate (Maines et al., 2002).
Risk management and subsequent risk reporting refers to the internal controls within a firm, which concerns managerial processes that cannot be directly observed by investors (Hooghiemstra et al., 2015). According to Hooghiemstra et al. (2015), investors rely on voluntary disclosure in order to judge the effectiveness of internal controls and to what extent managerial decisions are in line with the interests of investors. Therefore, managers can voluntarily disclose information in order to influence the perspective of shareholders on their abilities to address and measure risk (Elshandidy et al, 2013), which indicates the use of signalling theory.
Strategic risks are particularly interesting to investors, as they largely determine the potential development of a firm (Miihkinen, 2012). Corporate disclosure of these risks is increasingly regulated (e.g. SEC, 1997-), in order to ensure the quality of these disclosures (Linsley & Shrives, 2006). A good quality of strategic risk disclosure is of great value to the shareholders of a firm (Abraham & Cox, 2007).
2.2 Signalling theory
Using theory and literature on how both financial leverage and liquidity levels can affect disclosure helps with understanding the relation between them. In this paragraph, the relation between financial leverage and liquidity and the quality of strategic risk reporting is further elaborated using signalling theory.
Signalling theory helps to explain the use of voluntary disclosure by the management of a firm. Risk management and reporting is, as mentioned by Bronson et al. (2006), shared
7
with shareholders of an organisation on a voluntary basis and therefore subject to volatility. Managers try to create a positive image among shareholders about the ability of the manager to address and measure risk (Elshandidy et al., 2013), by voluntarily providing information on these topics with the aim to improve their reputation (Abraham & Shrives, 2014;
Hooghiemstra et al., 2015). This is in line with what is described in signalling theory.
Therefore, this study suggests that the management of a firm wants to maximize the quality of risk reporting in order to influence the perception of shareholders and potential investors.
Reasoning from signalling theory, both financial leverage and liquidity are likely to have a positive impact on corporate disclosure levels (Elshandidy et al., 2013). High leveraged firms may have an incentive to voluntary provide more information in order to indicate that they have not violated the conditions of any agreements (Foster, 1986). Furthermore, high leveraged firms may have an incentive to provide more information in order to signal to the market that they are able to manage risks efficiently and effectively (Abraham & Cox, 2007). Firms with a high liquidity level, are likely to disclose more information as well, in order to show their ability to meet short term obligations to shareholders of the firm (Shehata, 2014).
However, other studies using signalling theory mention other incentives to disclose more information. For example, Deschow et al. (1996) describe that firms with higher
financial leverage are more likely to commit fraud, which makes the additional risk disclosure in the annual report a way to communicate information about the reliability of a firm
(Bronson et al., 2006). This strengthens the statement of Amran et al. (2009) that firms use disclosure to explain the current situation of the firm, justify decisions and ensure reliability.
Using these theories and arguments about the purpose and use of risk reporting, including strategic risk reporting, helps with gaining insight in how to overcome difficulties with both high financial leverage and high liquidity (Jensen & Meckling, 1976; Ahn & Lee, 2004; Foster, 1986; Ahmed & Courtis, 1999). Therefore, disclosing risks can be a solution to mentioned problems and be beneficial to both the organisation and its shareholders.
8
In conclusion, the management of a firm can overcome problems arising from either high financial leverage or high liquidity, such as agency problems, high monitoring costs or lack of trust due to suspicion of violating agreements or committing fraud, by voluntary disclosing information in their annual reports. Additional disclosure on these topics can, according to Amran et al. (2009), explain the current situation of the firm, justify decisions and ensure reliability.
2.3 Financial leverage
In order to explain and understand the influence and use of financial leverage in an organisation, the trade-off theory by Modigliani & Miller (1958) can be used. The trade-off theory is used to explain the importance of financial leverage in relation to the capital structure of a firm. It suggests that the benefits of increased financial leverage, such as tax benefits or reduced agency costs, are weighed against the costs of increased financial
leverage, such as bankruptcy costs, in order to determine the optimal amount of leverage for the firm (Korajczyk & Levy, 2003).
In case of optimal financial leverage, an organisation has several advantages. A firm can create value when assets bought with debt capital yield more than the related cost of debt. Another advantage can be, as previously mentioned, the creation of a favourable tax treatment due to tax deductible interest expenses in debt capital. Therefore, ensuring an optimal balance between total debt and shareholder’s equity, or in short, the capital structure of the firm, creates firm value (Modigliani & Miller, 1958).
Empirical research on the association between financial leverage and risk disclosure show mixed results (Elshandidy et al., 2013). As mentioned before, financial leverage, along with liquidity, has impact on a firm’s risk disclosure (Ferguson et al., 2002; Malone, Fries, & Jones, 1993; Wallace et al., 1994). This study builds on previous research, which suggested and found a significant positive relation between financial leverage and risk disclosure (Amran et al., 2009; Marshall & Weetman, 2007; Deumes & Knechel, 2008). According to Foster (1986), this relation might be explained by stating that high leveraged firms experience incentives to provide more information in order to state that they have not violated the
conditions of any agreements. Furthermore, high leveraged firms may have an incentive to provide more information in order to signal to the market that they are able to manage risks efficiently and effectively (Abraham & Cox, 2007).
9
High leveraged firms may be unattractive to potential investors due to having higher risks as a result of having more debt. Additional disclosure on a strategic level might
compensate for this, as disclosure on strategic risks largely present the future potential of a firm (Miihkinen, 2012). These additional disclosures need to be of adequate quality to be valuable to potential investors (Abraham & Cox, 2007). Therefore, the following hypothesis is developed:
H1: Financial leverage is positively related with the quality of strategic risk reporting
2.4 Liquidity
Liquidity refers to the ability to pay off debt as and when they come due. The liquidity ratio is used to show how quickly a firm can convert its current assets into cash to pay off liabilities on a timely basis. The ratio plays an important role assessing the financial position of a firm, as it affects both the credit worthiness and the credit rating of a firm. Common ratios used to measure liquidity are current ratio and/or quick ratio.
Firms with a high liquidity are more likely to disclose information on their ability to meet short term obligations to shareholders of the firm (Shehata, 2014). This study builds on previous research, suggesting and finding significant relations between liquidity and risk disclosure levels. According to previous studies, highly liquid firms have more incentives to provide voluntary information (Cooke, 1989; Graham et al., 2005). Adding to these studies, Marshal & Weetman (2007) confirm that there is a positive association between the liquidity level of firm and it’s disclosure levels.
Financial leverage
Liquidity
Quality of strategic risk reporting
H2: + H1: +
10
As liquidity levels affect a firm’s credit rating, firms may disclose more strategic information in order to ensure long-term reliability (Amran et al., 2009). These disclosures need to be of adequate quality to be of value to potential investors (Abraham & Cox, 2007).
Based on theories on risk reporting and the suggested relation with liquidity and the quality of strategic risk reporting, the following hypothesis is developed:
H2: Liquidity is positively related to the quality of strategic risk disclosure
Financial leverage
Liquidity
Quality of strategic risk reporting H2: +
11
3. METHODOLOGY
In this section, first the data collection is described at first together with the method of analysis (3.1). Second, the description of dependent, independent and control variables is described (3.2). Third and last, the order of the statistical analysis is unfolded (3.3). 3.1 Data collection and sample
In order to make a sample, annual reports from the time period 2015-2017 from large companies in Europe, the United States and the United Kingdom have been collected. Firms were chosen using the Fortune 500 Global. Financial firms were excluded from the sample, as risk reporting is harder to analyse in comparison to companies from other industries. This is because financial firms have significantly lower strategic risks. After having excluded the financial firms, the initial sample consists 383 firms from the Fortune 500 Global. From this sample, 125 firms have been manually selected in order to ensure a good mix of firm origin, including the United States, the United Kingdom and Europe. For each of these, three annual reports were collected corresponding with the fiscal years of 2015, 2016 and 2017. For 114 of the 125 firms, all thee annual reports were available. The final sample consisted of 342 firm-year observations from 114 firms over the period 2015-2017. Using the annual reports as a source for observations, the effects of financial leverage and liquidity on the quality of strategic risk reporting were tested. The Orbis database was used to hand-collect the required data.
3.2 Measure of variables
In this section the measurement of each of the variables is discussed. The construction of the weighted index for the measurement of the quality of strategic risk reporting is first presented (3.2.1). Subsequently, the actual measurement of the independent variables is described: financial leverage and liquidity (3.2.2). At last, the control variables are described (3.2.3).
3.2.1 Dependent variable: quality of strategic risk disclosure
This study relies on hand-collected data on strategic risk reporting. With these data, the efforts that individual managers make to manage and mitigate possible agency problems are indicated. This differs from many other studies that use quantitative measures to assess the level of risk reporting within a firm. The information in those studies is, however, not always
12
easily and immediately understood: different methods are used to measure the quality of information (Scaltrito, 2015).
Previous research on the quality of risk reporting and disclosure in general is limited. Most studies used a self-constructed disclosure index, such as Hooghiemstra et al. (2015). The creation of disclosure indexes is one of the most widely used techniques in accounting studies (Scaltrito, 2015) and acts as a general approach to convert natural language text data into a number that can be used for further quantitative analysis (Beattie, 2004). Using pre-selected items, an index can provide a measure to indicate the qualitative level of disclosure (Coy, 1995).
The disclosure index, as used by Hooghiemstra et al., focuses on a limited number of separate items regarding internal disclosure. We follow up on this research by constructing our own disclosure index concentrating on the strategic risk reporting, choosing eight categories of items relating to the strategic risks of a firm. The index is created and used to analyse the quality of strategic reporting by performing three steps.
The first step consists of determining the different items of the strategic index. A total of eight different items regarding strategic risks were chosen based on previous research and literature. Two of these items were mentioned by Hooghiemstra et al. (2015) in their index under the item strategic and operational risk: competition and environment. The other six items were added by using strategic disclosure items that are expected to be relevant to the users of the risk reporting section of the annual report (Srinivasan, 2006). We were guided by the strategic risks that were mentioned by Miihkinen (2010) : industry, technological
development, compliance with regulation, dependence on suppliers, dependence on customers and organisational competencies (See Appendix A).
The second step involved the actual measurement of these items using a four-point score system, implying a score range where a score is attributed to the detected information ranging from a minimum to a maximum (Scaltrito, 2015). In this study, firms receive a maximum of four points on each of the eight items, getting points by: mentioning the risk corresponding to the item (1), mentioning the likelihood that the risk will occur by stating the related event(s) (2), mentioning the impact of the risk (3) and by stating a year-to-year
development of the risk, based on risk disclosure in previous annual reports (4). Using the score system, each firm can get up to a maximum of 32 points. The score indicates the quality of strategic risk reporting within a firm.
13
In the third a final step, a total of 342 annual reports of 124 firms were examined and scored using the eight items of the self-constructed index along with the four-point score system for each of the items in order to measure the quality of strategic risk reporting. We looked at the strategic risk section of the annual report in order to determine a score. Information is collected exclusively from annual reports, as the annual reports is easy to compare between firms and is a good source of information for both stakeholders and potential investors. Besides that, using the annual report complements on previous studies (Amran et al., 2009; Maines et al., 2002) in that the annual report can provide non-financial information regarding strategic risk reporting which can be useful for potential investors.
The quality of strategic risk reporting within a firm, denoted as ‘SRDQ’, is determined by the sum of each of the eight scores. In line with the index of Hooghiemstra et al. (2015), all eight items are equally weighted, as user preferences are unknown. The sum of the scores gives a value ranging from 0 (lowest possible quality of strategic risk reporting) to 32 (highest possible quality of strategic risk reporting).
In order to test the reliability of the strategic risk disclosure index the Cronbach’s alpha is calculated to test the internal consistency of the eight-item scale for measuring the quality of strategic risk disclosure. The result of the test shows a Cronbach’s Alpha of .69, which is sufficient enough for newly constructed indexes to apply to research.
3.2.2 Independent variables: financial leverage and liquidity
Like previous studies (Deumes & Kneichel, 2008; Bronson et al., 2006; Amran et al., 2009), the financial leverage (‘LEV’) is measured by dividing the total liabilities of a firm with the total assets of a firm. This ratio gives insight in the total debt load within a firm, in order to be able to compare it with the equity or assets. This ratio is widely used by investors to analyse the financial position of a firm.
In order to measure the liquidity (‘LIQ’) of a firm, several liquidity ratios can be used (e.g. current ratio, quick ratio, acid test ratio). This study follows signalling theory to suggest the association between liquidity and the quality of strategic risk disclosure. Therefore, the current ratio is used to determine the liquidity level of a firm. This ratio is calculated by dividing the current assets of a firm with the current liabilities of this firm and gives insight in the ability of a firm to pay off debt as and when they come due (Elshandidy et al., 2013).
14
3.2.3. Control variables
Several control variables were included in this study to account for the impact on strategic risk disclosure quality other than financial leverage and liquidity. First, this study controls for firm performance using two different variables: the year-on-year growth of sales (‘SGROWTH’) and the return on assets (‘ROA’).
Second, this study controls for the size of a firm as a measure of impact on risk disclosure quality. Firm size is positively related with risk disclosure, according to previous studies (e.g. Ahmed & Courtis, 1999; Linsley & Shrives, 2006; Abraham & Cox, 2007). Firm size as a control variable is denoted as ‘SIZE’ and is measured by the total assets (in $
millions) of a firm.
Third, industry dummies were included to control for cross-sectional differences in quality of strategic risk disclosure. A five-sector classification model was used based on a firm’s SIC-code. The different industry types used are MANUFACTURING (SIC
2000-3999); Transportation, Communications, Electric, Gas and Sanitary service, TCEGS (SIC 4000-4999); Wholesale and retail trade, TRADE (SIC 5000-5999); SERVICE (SIC 7000-8999); and OTHER (SIC 0100-1799, SIC 9100-9729), including among others agriculture,
forestry, fishing, mining and construction.
Fourth and last, year dummies were included for the years 2015-2017 in order to control for time-series differences in quality of strategic risk disclosure.
15
Dependent variable
SRDQ The quality of the strategic risk disclosure of a firm, measured by a self-constructed index with eight items related different categories of strategic risks. Score ranges differ from 0 (lowest possible quality of strategic risk disclosure) to 32 (highest possible quality of strategic risk disclosure) Independent variables
LEV Referring to the level of debt financing a firm uses, measured by dividing the total liabilities of a firm with the total assets
LIQ Referring to the ability of a firm to pay off debt as and when they come due, measured by the current ratio : total assets / total liabilities
Control variables
PERF : Firm performance, measured by two different variables, including :
SGROWTH Equal to the firm’s year-on-year growth of sales in %
ROA Equal to the firm’s return on assets (net income/ total assets)
SIZE The size of a firm, measured by the natural logarithm of total assets
Sector dummies MANUFACTURING, TCEGS, TRADE, and SERVICE are sector dummies that receive the value of 1 when a firm is active in that sector and 0 otherwise. The hold-out group is OTHER
Year dummies Variables Y2015, Y2016 and Y2017 take the value of 1 if the annual report is from the fiscal year 2015, 2016 or 2017, respectively, and 0 otherwise
TABLE 1 Variable definitions Variable Description
16
3.3 Statistical Analysis
The empirical model to test our hypothesises is described in this section. This study aims to test the association between financial leverage and strategic risk disclosure quality (H1) and the association between liquidity and strategic risk disclosure quality (H2). The empirical model to test the association between financial leverage and liquidity on the one hand and the quality of strategic risk disclosures on the other is shown below.
SRDQi, j = β0 + β1·LEVi, j + β2·LIQi, j + β3·SGROWTHi, j + β4·ROAi, j + β5·SIZEi, j + β7·Y2015i, j + β8·Y2016i, j + β9·Y2017i, j + ∑ β10·SECTORi, j + εi, j (H1/H2)
The empirical model above consists of an intercept (β0), which is the standard score for the
quality of strategic risk disclosure. Dependent variables (β1+β2) and control variables (β3-β10)
are added to or subtracted from the intercept, depending on the relation with the quality of strategic risk disclosure. The standard error (ε) indicates the standard deviation of the sample distribution. SRDQi, j is the quality of strategic risk disclosure of the firmi for the year j. All
other variables are defined in table 1 Variable definitions.
To test the two hypothesizes within the context of using the empirical model, the ordinary least squares (OLS) regression method is used. For the statistical analysis, the IBM
17
4. RESULTS
4.1 Descriptive analysis
The descriptive statistics of the dependent variable, independent variables and control variables are presented in table 2. This table shows that the average quality of strategic risk disclosure is 15.56 on a scale from 0 to 32, using the index described in Appendix A and the score system of Appendix B. The average financial leverage ratio of the sampled firms is 4.31, while the average liquidity ratio of those firms is 1.33. Furthermore, the data shows average annual sales growth of 1.15% during the years 2015 to 2017, an average return on assets of 4,54% and an average of 71.37 million dollars as firm size, measured by the total assets of a firm.
TABLE 2 Descriptive Statistics
Variable Mean SD Min. Max.
SRDQ (index score) 15.560 4.098 5.00 28.00
LEV (ratio) 4.312 5.978 .10 29.63
LIQ (ratio) 1.331 .577 .59 3.36
SGROWTH (%) 1.150 16.286 -39.00 42.00
ROA (%) 4.538 4.624 -5.81 16.65
SIZE (in $ million) 71,366.74 93,113.33 8.00 506,336.00
MANUFACTURING .430 .496 .00 1.00
TCEGS .219 .414 .00 1.00
TRADE .202 .402 .00 1.00
SERVICE .079 .270 .00 1.00
OTHER .070 .256 .00 1.00
This table includes the descriptive statistics for both the continuous and dichotomous variables for the final sample. Data for LEV, LIQ, SGROWTH and ROA have been windsorized at the 95% level.
18
The correlations between dependent, independent and control variables are shown in table 3. As can be read in the table, none of the variables are correlated at .6 or higher, which excludes possible multicollinearity issues (Hooghiemstra et al., 2015). Most striking is that the service sector shows a negative correlation with liquidity (r = -.45). This could be explained due to the service sector lacking inventory, which directly impacts the current assets of a firm. Therefore, the liquidity level, measured by the current ratio, is negatively affected.
Furthermore, certain sector dummies show relatively high correlations in among each other, for instance MANUFACTURING with TCEGS (r = -.46) and TRADE (r =-.44). To double-check if no multicollinearity issues arrive from these correlations, all variables were
controlled on variance inflation factors. These variance inflation factors were less than 5 in all cases. Therefore multicollinearity, based on variance inflation factors, is not an issue (Ringle et al., 2015). TABLE 3 Correlation Matrix 1 2 3 4 5 6 7 8 9 10 1 SRDQ 1.00 2 LEV -.00 1.00 3 LIQ .15 -.23 1.00 4 SGROWTH .05 -.02 .14 1.00 5 ROA .08 -.13 .25 .15 1.00 6 SIZE .05 -.03 -.07 .02 -.15 1.00 7 MANUFACTUR ING .11 -.20 .09 .02 .12 -.02 1.00 8 TCEGS -.03 .29 -.25 -.13 -.26 .18 -.46 1.00 9 TRADE -.02 .09 -.14 .05 .03 -.20 -.44 -.27 1.00 10 SERVICE -.01 -.12 -.45 .12 .22 -.02 -.25 -.16 -.15 1.00
This table includes the Pearson correlation coefficients between the dependent, independent and control variables. Correlations greater than the absolute value of .14 are statistically significant on the 1% level (two-tailed) and correlations greater than the absolute value of .10 are statistically significant on the 5% level. Data for LEV, LIQ, SGROWTH and ROA have been windsorized at the 95% level.
19
4.2 Effect of financial leverage and liquidity on the quality of strategic risk disclosure In this paragraph the effect of financial leverage and liquidity on the quality of the strategic risk disclosures is described. Table 4 includes the beta coefficients from the ordinary least squares (OLS) regressions with the standard errors in parentheses. A total of 328
observations are used in order to run the regressions.
Column 1 presents the effects of firm characteristics on the quality of strategic risk disclosure. The results of hypothesis 1, the effect of financial leverage on the quality of strategic risk disclosure, are given in column 2. Although the beta coefficient of financial leverage is positive, the test shows no significant relation between financial leverage and the quality of strategic risk reporting. When looking at column 3, the results confirm the proposed relation in hypothesis 2, where liquidity is positively related with the quality of strategic risk disclosure (β = 1.321, p = <.01). This result suggests that firms with a higher liquidity level generally disclose higher quality information on a strategic level, which is in line with signalling theory. Column 4 shows the results of the regression when testing both the effects of financial leverage and liquidity on the quality of strategic risk disclosure. The significance of these results remains unchanged in comparison to previous regressions.
When looking at the results of the control variables, it can be concluded that firm size positively associates with the quality of strategic risk reporting (p = <.01). These findings are in line with prior research (e.g. Ahmed & Courtis, 1999; Linsley & Shrives, 2006; Abraham & Cox, 2007). Furthermore, the results suggest that the quality of strategic risk disclosure increases over time, as the beta coefficients of year dummies Y2015 (β = -773) and Y2016 (β = -315) are negative. However, this association has not been found significant. Besides that, regressions show a significant positive relation between the manufacturing sector and the quality of strategic risk disclosure at the 5% significance level (β = 1.901, p = <.05), which indicates that firms active in the manufacturing sector disclose strategic information of a higher quality in comparison with other sectors. Results for sales growth (SGROWTH), return on assets (ROA) and sectors other than the manufacturing sector are insignificant in all regressions.
20
TABLE 4
Ordinary Least Squares (OLS) Regression Results
Dependent variable (1) SRDQ (2) SRDQ (3) SRDQ (4) SRDQ Intercept 11,756*** (1.214) 11,678*** (1.219) 10,331*** (1.295) 10,131*** (1.305) LEV (ratio) .029 (.0039) .045 (.039) LIQ (ratio) 1.321*** (.452) 1,393*** (.456) SGROWTH (%) .003 (.015) .003 (.015) -.002 (.015) -.003 (.015) ROA (%) .053 (.051) .056 (.052) .036 (.051) .039 (.051) SIZE (in $ million) .573***
(.183) .581*** (.184) .526*** (.182) .536*** (.182) Y2015 -.572 (.592) -.601 (.594) -.720 (.588) -.773 (.589) Y2016 -.184 (.576) -.209 (.578) -.272 (.570) -.315 (.571) MANUFACTURING 2,018** (.929) 1,984** (.931) 1,958** (.918) 1,901** (.750) TCEGS .624 (.986) .446 (1.015) 1,006 (.983) .750 (1.007) TRADE 1,077 (.996) .968 (1.007) 1,302 (.987) 1.144 (.996) SERVICE 1,489 (1.195) 1,485 (1.196) .401 (1.239) .335 (1.239) R-squared .057 .058 .082 .086 #N observations 328 328 328 328
This table includes the results of the ordinary least squares (OLS) regressions. Data for LEV, LIQ, SGROWTH and ROA have been windsorized at the 95% level. Data for SIZE is log transformed with a base of 10. The results given are beta coefficients, while the numbers in parentheses are standard errors. One-tailed test are conducted for the independent variables and two-tailed tests for control variables. Significance is indicated as; *** = p < .01, ** = p <.05, * = p <.10
21
4.3 Sensitivity check
To test the robustness of the regressions considering the sample size and potential variation in the overall population, confidence intervals on significant results were obtained. These
confidence intervals estimate the range in which the results are located, using a certain percentage of confidence. When looking at table 5, the test shows that the beta coefficient of liquidity on the quality of strategic risk disclosure, as shown in the regressions of table 4, is 90% confident to be located between .641 and 2.145 when testing another sample within the same population. This test strengthens the finding of liquidity levels being positively related with the quality of strategic risk disclosure.
TABLE 5
Confidence Intervals of liquidity (β) on the quality of strategic risk disclosure
(2) (3)
Lower bound .575 .641
Liquidity coefficient (β) 1.321 1.393
Upper bound 2.067 2.145
This table presents the confidence intervals of the liquidity beta coefficient on the quality of strategic risk disclosure, as shown in the results of the ordinary least squares (OLS) regressions described in table 3. The number in parentheses refer to the corresponding tests described in table 3. A confidence interval of 90% is used for this test, which indicates that the actual beta coefficient is 90% sure to be located between the lower and upper bound when using a different sample from the overall population.
4.4 Additional test
The results of the ordinary least squares (OLS) regressions show a significant positive association between firm size and the quality of strategic risk disclosure at the 1%
significance level. However, as data for firm sizes were logged, a clear interpretation of the strength of this relation is missing. Therefore, as an additional test, total assets in U.S. dollars as a measure of firm size is stratified into three brackets: SMALL (<25 $ billion dollars), MEDIUM (>25 - <75 $ billion dollars) and LARGE (>75 $ billion dollars). Using these variables instead of ‘SIZE’, table 6 presents the results of the regression. Compared to the firms of ‘MEDIUM’ size, the results show that smaller firms indeed have a lower quality of strategic risk disclosure (β = -.866, p = <.05). Of interest is that larger firms do not
necessarily have a higher quality of strategic risk disclosure, as the regression analysis shows (β= .003, p = <.01).
22
TABLE 6
Ordinary Least Squares (OLS) regression using stratified firm sizes
Dependent variable (5) SRDQ Intercept 12,689*** (1.130) LEV (ratio) .041 (.039) LIQ (ratio) 1,511*** (.463) SGROWTH (%) -.004 (.016) ROA (%) .043 (.052) SMALL LARGE -.866** (.184) .003*** (.565) Y2015 -.778 (.596) Y2016 -.309 (.578) MANUFACTURING 1,616* (.927) TCEGS .739 (1.033) TRADE 1,068 (1.010) SERVICE -.209 (1.241) R-squared .069 #N observations 328
This table includes the results of the ordinary least squares (OLS) regression using a stratified approach to firm size. Data for LEV, LIQ, SGROWTH and ROA have been windsorized at the 95% level. The results given are beta coefficients, while the numbers in parentheses are the standard errors. Significance is indicated as; *** = p < .01, ** = p <.05, * = p <.10
23
CONCLUSIONS & DISCUSSION
This study aims at an increased understanding of the influence of both financial leverage and liquidity on the quality of strategic disclosure. In order to create a theoretical background and to develop it’s hypothesises, mainly signalling is used. According to signalling theory, financial leverage and liquidity both positively impact disclosure (Elshandidy et al., 2013). The goal for this study was to discover if financial leverage and liquidity also positively impact the quality of these disclosures on a strategic level.
The data used in this study, including a sample of 114 firms with 342 firm-year observations in the period 2015-2017, shows that there is no significant relation between the financial leverage of a firm and the quality of strategic risk disclosure after being controlled for firm characteristics. Therefore, hypothesis 1 is rejected. A possible explanation can be that the incentives to improve the quality of strategic risk disclosure due to increased leverage, such as indicating that the firm has not violated the conditions of any agreements (Foster, 1986) or to indicate that the firm is able to manage risks efficiently and effectively (Abraham & Cox, 2007), are off-set by incentives not to increase or improve the quality of strategic risk reporting, such as the increased fear of increased monitoring or a change in the creditor’s pressure stemming due to having high levels of risk (Abid & Shaiq, 2015).
Furthermore, the results show that a firm’s liquidity level, measured by the current ratio, is positively related with the quality of strategic risk disclosures after being controlled for firm characteristics. Therefore, hypothesis 2 is accepted. Additionally, a positive
association between firm size and the quality of strategic risk disclosures was found, which is in line with prior research (e.g. Ahmed & Courtis, 1999; Linsley & Shrives, 2006; Abraham & Cox, 2007).
This study makes several theoretical and empirical contributions. First, by assessing the impact of a firm’s financial position, in terms of financial leverage and liquidity, on the quality of strategic risk disclosures. Moreover, this study bridges the gap towards a more specific measure on risk disclosures by assessing strategic risk disclosure as instead of measuring total risk disclosure. At last, by using a categorical index this study gives a more reliable proxy of the quality of risk reporting instead of focusing on quantitative measures. Therefore, the results of this study add to the findings of Marshal & Weetman (2007) by determining that liquidity levels do not only impact the quantity of risk disclosure levels, but also the quality of these disclosures on the strategic level.
24
Despite the promising results, the study is limited in its scope. First, the sample that is used to test the hypothesises consists of firms from the Fortune 500 Global, which limits the ability to generalise into the direction of smaller firms. Future research can be conducted on smaller firms or private firms in order to strengthen the reliability of these results towards smaller firm sizes. It will be interesting to see if the findings of this study hold when using a sample based on smaller firms. Second, although this study examined the quality of strategic risk disclosures cross-nationally, the constructed index and subsequent scoring system have not been adjusted for mandatory disclosure forms and rules, such as the U.S. 10K form. Future research might examine these cross-national differences in mandatory disclosure rules to determine significant differences in the quality of these disclosures. Third and last, this study focuses on the quality of the strategic disclosures within a firm. It would be interesting to see if the results of this study also hold when measuring the effect of financial leverage and liquidity on the quality of tactical and operational disclosures.
Adding to these limitations, the self-constructed index used in this study leaves room for debate. Although the Cronbach’s Alpha of .69 indicates a sufficient score for internal consistency, no additional reliability tests have been conducted in order to confirm internal consistency. Adding to that, the items used in the index are not analysed separately.
Therefore, we can not conclude that all items used within the index are of equal value to the validity of the model. Furthermore, as there is no universal definition of ‘quality’, the four-point score system and subsequent coding process can be considered subjective.
This study shows that changes in the quality of strategic risk disclosures are affected by liquidity levels. Prior research showed that liquidity levels positively affect disclosure levels (Marshal & Weetman, 2007), which is in line with signalling theory. The relation can be explained when firms have incentives to provide voluntary information (Cooke, 1989; Graham et al, 2005), such as to show their ability to meet short term obligations to
stakeholders of the firm (Shehata, 2014) or to signal their high performance and ability to manage risks successfully (Elshandidy et al, 2013). As liquidity levels affect a firm’s credit rating, firms may disclose more strategic information in order to ensure their long-term reliability to stakeholders (Amran et al., 2009). As disclosure increases when liquidity levels increase, according to prior research, it is likely that these disclosures are of higher quality, as disclosure needs to be of adequate quality in order to be of value to potential investors
(Abraham & Cox, 2007). This study proves that liquidity levels do not only positively affect disclosure levels at the strategic level, but also the quality of the disclosure efforts.
25
ACKNOWLEDGEMENTS
I would like to express my gratitude to my supervisors prof. dr. J.A. Emanuels and F.J. Bos (University of Groningen) for their helpful comments and suggestions during the
development of this master thesis. Next to that, my gratitude goes out to D. Bijman, D. Veldhoen, R. Helmantel and J.J. Spoler (co- master students Accountancy & Controlling at the University of Groningen) for their involvement in developing this master thesis and especially in developing the strategic risk disclosure index. On top of that, I would like to thank dr. M. Popkema (Windesheim University of Applied Sciences) for his helpful comments, suggestions and quality check on the drafts and concept of this master thesis.
26
APPENDIX A : Strategic risk categories
The table below shows the eight items used to measure the quality of strategic risk reporting within the annual reports of a firm, along with a description and source.
Item Description
Environment Risk category related to the business environment of a firm (e.g. sustainability)
Source : Hooghiemstra et al. (2015)
Industry Risk category related to the operating industry of a firm Competition Risk category related to the competition a firm is facing
within the operating industry (e.g. pricing, rivalry)
Source : Hooghiemstra et al. (2015)
Technological development Risk category related to a firm’s technological level and development (e.g. research and development)
Source : Miihkinen (2010)
Compliance with regulation Risk category related to regulation (e.g. privacy, constraints)
Source : Miihkinen (2010)
Dependence on suppliers Risk category related to a firm’s dependence on suppliers (e.g. supplier power)
Source : Miihkinen (2010)
Dependence on customers Risk category related to a firm’s dependence on customers (e.g. customer demand)
Source : Miihkinen (2010)
Organisational competencies Risk category related to a firm’s capabilities (e.g. retaining management & personnel, firm structure decisions,
27
APPENDIX B : Scoring system
The table below presents the score range of the study by measuring pre-determined aspects of strategic risk reporting. Used to assess the score of items mentioned in Appendix A to create a proxy for the quality of strategic risk reporting.
Measure Requirement
Mentioning risk Equal to 1 point if the annual report discloses information on risk(s) related to the item in appendix A
Mentioning likelihood Equal to 1 point if the likelihood of the risk is mentioned (e.g. stating the related events and their possibility)
Mentioning impact Equal to 1 point if the impact of the risk is mentioned, either financial or non-financial impact
Mentioning risk development Equal to 1 point if the risk development across time is mentioned (e.g. prognosis and development of a risk within different annual reports)
28
REFERENCES
Abraham, S., & Shrives, P. J. (2014). Improving the relevance of risk factor disclosure in corporate annual reports. The British accounting review, 46(1): 91-107.
Abraham, S. & Cox, P. 2007. Analysing the determinants of narrative risk information in UK FTSE 100 annual reports. British Accounting Review, 39: 227–248.
Ahmed, K., & Courtis, J. K. (1999). Associations between corporate characteristics and disclosure levels in annual reports: A meta-analysis. The British Accounting Review, 31(1), 35–61.
Ahn, T.S. and Lee, J. (2004). Determinants of voluntary disclosures in management
discussion and analysis (MD&A): Korean evidence. paper presented at the 16th Asian Pacific
Conference on International Accounting Issues, Seoul, November 7-10.
Andersen, T.J. (2005). Risk management, capital structure, and performance: a real options perspective. Global Business & Economics Anthology, 1-19.
Amran A., Bin, A.M.R., Bin Che Haat, M.H. (2008). Risk reporting: An exploratory study on risk management disclosure in Malaysian annual reports. Managerial Auditing Journal, 24(1): 39-57
Ashbaugh-Skaife, H., Collins, D. W., & Kinney, W. R., 2007. The discovery and reporting of internal control deficiencies prior to SOX-mandated audits. Journal of Accounting and
Economics, 44: 166–192.
Beattie, V., McInnes, B., and Fearnley, S. (2004). A methodology for analysing and
evaluating narratives in annual Report: A comprehensive descriptive profile and metrics for disclosure quality attributes. Accounting Forum, 28 (3), 205-236
Beyer, A., Cohen, D. A., Lys, T. Z., &Walther, B. R. (2010). The financial reporting
environment: Review of the recent literature. Journal of Accounting and Economics, 50(2–3): 296–343.
Bronson, S. N., J. V. Carcello, and K. Raghunandan. (2006). Firm characteristics and
voluntary management reports on internal control. Auditing: A Journal of Practice & Theory, 25 (2): 25–39.
Coy, D.V. (1995). A Public Accountability Index for Annual Reporting by NZ Universities.
Unpublished PhD thesis, University of Waikato, Hamilton, New Zealand.
Cooke, T. (1989). Disclosure in the corporate annual report of Swedish companies.
Accounting and Business Research, 19(74): 113–122.
Deumes, R. & Knechel, W. R. (2008) Economic incentives for voluntary reporting on internal risk management and control systems. Auditing: A Journal of Theory and Practice, 27: 35– 66.
Dechow, P. M., R. G. Sloan, and A. P. Sweeney. (1996). Causes and consequences of earnings manipulation: An analysis of firms subject to enforcement actions by the SEC.
29
Dobler, M. (2008). Incentives for risk reporting—A discretionary disclosure and cheap talk approach. The International Journal of Accounting, 43(2): 184-206.
Elshandidy, T., Fraser, I., & Hussainey, K. (2013). Aggregated, voluntary, and mandatory risk reporting incentives: Evidence from FTSE all-share. International Review of Financial
Analysis, 30, 320–333.
Ferguson, M. J., Lam, K. C. K., & Lee, G. M. (2002). Voluntary disclosure by state-owned enterprises listed on the stock exchange of Hong Kong. Journal of International Financial
Management and Accounting, 13(2), 125–152.
Foster, G. (1986). Financial statement analysis (2nd ed.) Englewood Cliffs, NJ: Prentice-Hall Graham, J., Harvey, C., & Rajgopal, S. (2005). The economic implications of corporate financial reporting. Journal of Accounting and Economics, 40(1–3): 3–73.
Hooghiemstra, R., Hermes, N., & Emanuels, J. (2015). National culture and internal control disclosures: A cross-country analysis. Corporate Governance: An International Review 23(4): 357-377.
Jensen, M., and W. Meckling. (1976) Theory of the firm: Managerial behaviour, agency costs and ownership structure. Journal of Financial Economics, 3(4): 305–360.
Jordan, J., Lowe, J. and Taylor, P. (1998). Strategy and financial policy in UK small firms.
Journal of Business Finance and Accounting, 25(1): 1-27.
Kale, J.R., Thomas, H.N. and Ramirez, G.G. (1991). The effect of business risk on corporate capital structure: theory and evidence. The Journal of Finance, 46(5): 1693-715.
Korajczyk, R.A. and Levy, A. (2003). Capital structure choice: macroeconomic conditions and financial constraints, Journal of Financial Economics, 68(1): 75-109.
Linsley, P.M., & Shrives, P.J. (2006). Risk reporting: A study of risk disclosures in the annual reports of UK companies. The British Accounting Review 38(4): 387-404.
Maines, L.A., Bartov, E., Fairfield, P.M., Hirst, D.E., Iannaconi, T.E., Mallett, R., Schrand, C.M., Skinner, P.J. and Vincent, L. (2002). Recommendations on disclosure of non-financial performance. Accounting Horizons, 16(4): 353-62.
Malone, D., Fries, C., & Jones, T. (1993). An empirical investigation of the extent of
corporate financial disclosure in the oil and gas industry. Journal of Accounting, Auditing and
30
Marshall, A., &Weetman, P. (2007). Modelling transparency in disclosure: The case of foreign exchange risk management. Journal of Business Finance & Accounting, 34(5–6): 705–739.
Michaelas, N., Chittenden, F. and Poutziouris, P. (1999). Financial policy and capital structure choice in UK SMEs: empirical evidence from company panel data. Small Business
Economics, 12(2): 113-30.
Miihkinen, A. (2010). What drives quality of firm risk disclosure? The impact of a national disclosure standard and reporting incentives under IFRS. The International Journal of
Accounting, 47: 437-468
Scaltrito, D. (2015). Assessing disclosure quality: a methodological issue. Journal of Modern
Accounting and Auditing, 11(9): 466-475
Shehata, F. (2014). Theories and determinants of voluntary disclosure. Accounting and
Finance Research, 3(1): 18-26
Srinivasan, R. (2006). Indigenous, ethnic and cultural articulations of new media.
International Journal of Cultural Studies, 9(4): 497-518
Ringle, C.M., Henseler, J., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academy of
Marketing Science, 43(1): 115-135
Wallace, R. S. O., Naser, N., & Mora, A. (1994). The relationship between the
comprehensiveness of corporate annual reports and firm specific characteristics in Spain.
