Keywords

Forward Looking Information, Disclosure, Annual Reports, Bank Characteristics, Lebanon.

Introduction

As a critical source of disclosure, forward-looking information (FLI) has been receiving an increasing consideration in recent disclosure research (Menicucci and Paolucci, 2017). It is believed that the current role of forward-looking information disclosure (FLID) in economic environment is thus crucial since the dynamic progress of economic conditions along with the economic development highlights the potential insufficiencies of historical disclosure in fulfilling investors’ variegated information needs (Mathuva, 2012). Thus, the insufficiency of historical disclosure raises the need for FLID that yields investors with the needed information to make informed decisions (Menicucci and Paolucci, 2017; Mathuva, 2012).

In fact, FLID refers to providing information that allows stakeholders to assess future performance of a firm (Uyar and Kilic, 2012); this can be found in the firm chairman's report- in the voluntary narrative part of the annual report (Alkhatib, 2014). Such FLID might contain both financial predictions of the firm, such as cash flows, revenues prediction, and sales volume (Alkhatib, 2014; Aljifri and Hussainey, 2007). As well as non-financial predictions of the firm, such as factors that may influence the firm's future performance as risk, future business ambiguity, analysis and evaluation, agency relationship, operations, and general significant information about the firm (Uyar and Kilic 2012; Aljifri and Hussainey, 2007; Celik et al., 2006).

Hence, there are numerous arguments about the benefits of including FLID in annual reports. For instance, Alkhatib (2014; 2012) argued that FLID lessens asymmetry of information between shareholders and firms, which aid interested users making better-informed investment decisions. Aljifri and Hussainey (2007) also claimed that the lack of FLID might guide investors to base their predictions on imprecise information from other sources. In addition, Beretta and Bozzolon (2004) suggested that the disclosure of FLI could enrich financial reporting and enhance the annual report.

Contrary to the benefits of providing FLID in the annual reports, preceding researchers have provided some opinions against the inclusion of them. For instance, Aljifri and Hussainey (2007) argued that, related to the future, there is uncertainty that might be difficult to be precisely expected, and this imprecision might lead the firms to lawsuit. Moreover, Healy and Palepu (2001) revealed that FLID might provide beneficial information to competitors and, henceforth, might influence the competitive position of the firm in product markets.

Despite its significance for numerous stakeholders, this type of information has, somewhat, less or the slightest disclosure rate among other disclosure areas (Uyar and Kilic, 2012; Elsayed and Hoque, 2010; Patelli and Prencipe, 2007). A very limited number of research have investigated the influence of firm characteristics on the disclosure of FLI in the developing countries and even scarcer, such research may be found in Middle Eastern countries (Zhafarina, 2017; Aljifri and Hussainey, 2007).

However, empirical evidence about the impact of firm-specific characteristics on this type of disclosure is uncertain and frequently fails to provide conclusive results (Mathuva, 2012; Donnelly and Mulcahy, 2008). On the other hand, only a relatively small number of research studies have addressed issues related to FLID by banks. Hence, a gap exists in the literature; consequently, a research to convey insights regarding this spring of research specifically in developing countries in general and in Lebanon in particular- where this issue has not been explored- is needed.

Therefore, this research is consequently designed to fill this research gap by empirically investigating the specific characteristics that may affect the extent of FLI disclosed in the narrative sections chairmen’s letters of the annual reports of Lebanese commercial banks for the period 2008-2017. These letters appear to fascinate broad readership than other sections of the corporate annual reports. They consist of double the quantity of information than the back of financial statements part. They have been found to be one of the greatest read sections of the corporate annual reports. Besides prior studies have observed an increase in dependence by both unsophisticated and sophisticated investors on these sections (Rutherford, 2003; Smith and Taffler, 2000; Subramanian et al., 1993).

On the other hand, the Lebanese banking sector was selected because the Lebanese banking sector has played a major role in fueling the economic growth of Lebanon and ensuring the relative stability of the financial sector as a whole (FFA Private Bank, 2009). As well, the Lebanese economy is based on services and the Lebanese banking sector is the most active of these services (Menassa, 2010). Additionally, Lebanese banks are mostly held by families or by controlled shareholders, unlike other countries where ownership structure is more dispersed among public, this shareholding specification of the Lebanese banking sector increases the motivation of conducting the research in this sector (BDL, 2019). As well, the main aim of voluntary disclosure is to provide stakeholders with useful information that helps them in taking rational decisions. Therefore, the selection of the banking sector ensures the availability of a large range of stakeholders, and thus, the whole society is concerned about having information related to the future performance of the banks. Such information is supposed to provide users with confidence and reliability.

Hence, as there are no studies known to the researcher that was investigated the effect of specific characteristics on the extent of FLID in the annual reports of Lebanese commercial banks, this research aids to encourage comparisons to other similar international studies. This may provide some indication of how trends in FLID are developing in the annual reports. It is hoped that this research would contribute to the body of knowledge in the area of financial disclosure; as banks are likely to convey more information about future results, plans and projects to help stakeholders to forecast future financial performance. Additionally, whilst it is becoming important, FLID is not subject to Lebanon mandatory disclosure regulations. Thus, the findings of this research will be of significance to Lebanese commercial banks regulators in assessing their disclosure policies and implement an ideal. The findings will also be beneficial to the regulators and policy-makers from other East Asian countries. Moreover, within the existing literature, the results of the impact of specific characteristics on the extent of FLID are most often mixed. Healy and Palepu (2001) reveal that the differences of results among studies of voluntary disclosure may due to the differences in institutional settings. With Lebanon being a developing economy that is different from those of developed markets, a research on voluntary disclosures of FLI in Lebanon adds another perspective to the existing debate.

The rest of this research will be constructed as follows; while the second section includes a theoretical framework and a review of the relevant literature, section three will describe data collection and research methodology, section four will include analysis and results, the conclusion will be included in section five.

Theoretical Framework

Recent scandals and corporate failures have placed accounting profession under inspection and have shaken trust in financial reporting (Berndt and Leibfried, 2007; Ramli et al., 2013; Adekunle and Taiwo, 2013). These scandals have happened worldwide owing to deficiency and inappropriate corporate disclosures presented by conventional financial reporting methods (Shehata, 2014). Thus, after a progressive rise of these corporate accounting scandals and financial crises, investors, academicians, regulators and other stakeholders asked for higher transparency from the business world by more comprehensive information disclosure (Uyar et al., 2013). FLID has been receiving an increasing amount of attention in recent disclosure studies. It is believed that disclosure of FLI would improve the ability of investors to assess future cash flows, to forecast future earnings and to make better investment decisions (Hussainey et al., 2003; Menicucci, 2013). The Accounting Standard Setters such as FASB (2001) and IASB (2010) as well as the American Institute of Certified Public Accountants (AICPA, 1994), the Canadian Institute of Chartered Accountants (CICA, 2002) and the Institute of Chartered Accountants in England and Wales (ICAEW, 2003), all draw attention to the significance of FLID for informed investors’ decision making. This increasing trend in FLID has led to the generation of a number of studies that have analyzed the association between firm characteristics and disclosure of FLI (K?l?ç and Kuzey, 2018).

Although this fact, however, empirical evidence about the effect of firm-specific characteristics on this kind of disclosure is uncertain and fails to provide conclusive results (Donnelly and Mulcahy, 2008; Menicucci, 2013). Previous studies examining the effect of firm specific characteristics on FLID have explored various propositions provided by agency theory, signaling theory, stakeholder theory and legitimacy theory. Those theories are used together to understand the determinants of FLID (Elzahar and Hussainey, 2012).

Agency theory is concerned with the associations between two players that are the principal and an agent (Ibrahim, 2011). The principal, who is the owner of the firm, employs an agent to act on the principal‘s interest in managing the firm (Armour et al., 2009); as such, the principal assumes the agent to pursue the interests of the principal (Gailmard, 2012). On the other hand, an agent, being the individual who exercises power, search for their own interests rather than pursuing those of the principal (Husted, 2007). More specifically, an agent can take actions to exaggerate their own usefulness because he is proficient with access to information and are thus better informed about the organization true performance than the principal (Garcia- Osma and Guillamón-Saorín, 2011). These asymmetries in the access to information end in adverse selection and moral hazard troubles on the part of management (Beaver, 1998). Agency theory uses voluntary disclosure as a mechanism for diminishing information asymmetry (Banghøj and Plenborg, 2008). Based upon this theory, the disclosure of FLI diminishes information asymmetry and reduces agency costs (Hassanein and Hussainey, 2015). In this regard, to decrease information asymmetry and agency costs, firms may report a higher level of FLI, which will sustain a better assessment of the future performance of the firms (K?l?ç and Kuzey, 2018).

Another theory used to understand the determinants of FLID is signaling theory. This theory is “useful for describing behavior when two parties (individuals or organizations) have access to different information. Typically, one party, the sender, must choose whether and how to communicate (or signal) that information, and the other party, the receiver, must choose how to interpret the signal” (Connelly et al., 2011:39). This theory affords an explanation of why firms are motivated to make voluntary disclosure (Wolk et al., 2001). Specifically, voluntary disclosure is one of the signalling means, where firms would disclose more information than the mandatory ones required by laws and regulations in order to signal that they are better- than other firms in the market for the purpose of attracting investments and enhancing a favourable reputation (Campbell, 2000). Signaling theory therefore recommends that managers disclose a significant level of information within firm annual reports to send specific signals to the users of those reports (Elzaharand and Hussainey, 2012). Hence, to decrease information asymmetries, firms may deliver signals to their audience by disclosing FLI.

Stakeholder theory claims that the firm has relationships with numerous essential groups (such as employees, customers, government agencies) and that it can provoke and maintain the support of these groups by considering and balancing their significant interests (Evan and Freeman, 1993; Clarkson, 1998; Jones and Wicks, 1999). It advocates that managers are responsible for recognizing the strategic issues that influence each stakeholder, and understanding how to set up and apply strategies for dealing with that stakeholder group (Ibrahim, 2011). Therefore, firms must be reactive to the competing demands of those who carry a stake in the firm by providing sufficient information to permit stakeholders to evaluate the overall performance of the firm (Turnbull, 1997). In relation to disclosure practices, firms have incentives to disclose FLI to particular stakeholders in order to convince them that they are complying with their requirements (Cotter et al., 2011).

Legitimacy theory studies the methods in which firms gain, sustain and preserve social acceptance from their stakeholders (Korpivaara, 2015). This theory was based on the supposition that in order to exist and be capable to operate a firm must be accepted by its social environment (Suchman, 1995). In the context of corporate disclosure researches, legitimacy theory is based on society’s perception, thus management is forced to disclose information specifically FLI that would change the external users’ opinion about their firm (Cormier and Gordon, 2001).

While there is no one theory that can fully explain the FLID, the agency theory appears empirically the most robust. This is demonstrated by a very wide literature, which engages this particular theoretical perspective. Hence, this research is grounded in agency theory.

Literature Review and Hypotheses Development

Disclosure of information in corporate annual reports has drawn the attention of a number of researchers in both developed and developing countries (Aljifri and Hussainey, 2007). A number of previous research have analyzed the relationship between firm characteristics and disclosure of FLI. However, the results are most often varied. These factors include profitability; firm size; leverage; sector type; liquidity; auditor type; firm age, and capital expenditure (Table 1).

Table 1 Firm Characteristics and their Relationship with flid Based on Prior Studies
Firm Characteristics	Relationship	Prior Studies
Profitability	NR	Mousa & ElAmir, 2018; K?l?ç & Kuzey, 2018; Aljifri et al., 2013; Uyar & Kilic, 2012.
	+	Menicucci, 2018; Menicucci & Paolucci, 2017; Mohammadi & Jamali, 2017; Zhafarina, 2017; Pratoomsuwan & Vu, 2016; Alkhatib, 2014; Menicucci, 2013; Mathuva, 2012.
	-	Aljifri & Hussainey, 2007; Celik et al., 2006.
Firm Size	NR	Aljifri et al., 2013; Menicucci, 2013; Mathuva, 2012; Aljifri & Hussainey, 2007.
	+	Menicucci & Paolucci, 2017; Mousa & ElAmir, 2018; K?l?ç & Kuzey, 2018; Menicucci, 2018; Mohammadi & Jamali, 2017; Zhafarina, 2017; Pratoomsuwan & Vu, 2016; Alkhatib, 2014; Uyar & Kilic, 2012; Celik et al., 2006.
Leverage	NR	Menicucci & Paolucci, 2017; Menicucci, 2018; Mohammadi & Jamali, 2017; Alkhatib, 2014; Menicucci, 2013; Uyar & Kilic, 2012; Celik et al., 2006.
	+	Mousa & ElAmir, 2018; Aljifri et al., 2013; Mathuva, 2012; Aljifri & Hussainey, 2007.
	-	K?l?ç & Kuzey, 2018; Zhafarina, 2017; Pratoomsuwan & Vu, 2016.
Sector Type	NR	Mousa & ElAmir, 2018; K?l?ç & Kuzey, 2018; Baroma, 2013; Mathuva, 2012; Aljifri & Hussainey, 2007.
	+	Zhafarina, 2017; Pratoomsuwan & Vu, 2016; Alkhatib, 2014; Celik et al., 2006.
Liquidity	NR	Mousa & ElAmir, 2018; Mathuva, 2012.
	-	Zhafarina, 2017.
Auditor Type	NR	Aljifri & Hussainey, 2007.
	+	Mohammadi & Jamali, 2017; Alkhatib, 2014; Baroma, 2013; Uyar & Kilic, 2012.
Firm Age	NR	Uyar and Kilic (2012)
Capital Expenditure	+	Mathuva (2012)

This research considers the following variables: profitability, size, leverage, liquidity, age, and capital expenditures. Industry type and auditor size are excluded. Industry type was excluded because the research takes place in one sector; and concerning the auditor size, it was found that big four audit firms audit all banks operating in Lebanon. Thus, studying these factors are no more valid in this research. Next, the relation results between each factor and the level of disclosure are highlighted.

Profitability

The empirical evidence on the association between profitability (PROF) and FLID is inconclusive. Many researchers such as Mousa and ElAmir (2018); K?l?ç and Kuzey (2018); Aljifri et al. (2013); and Uyar and Kilic (2012) revealed that no obvious association exists between PROF and FLID. Thereby, there is no significant impact created by PROF on FLID. This is in contrast to the numerous studies of Menicucci (2018); Menicucci and Paolucci (2017); Mohammadi and Jamali (2017); Zhafarina (2017); Pratoomsuwan and Vu (2016); Alkhatib (2014); Menicucci (2013) and Mathuva (2012) that demonstrate a positive association exits between PROF and FLID. The advocates of positive association between PROF and FLID claim that most profitable firms can dedicate more resources to FLID to make their operations recognized to the public (Garcia-Sánchez et al., 2013). Additionally, to transmit positive signals to the capital market (Qu et al., 2015). Further, to present better discussion and analysis of their good results to investors (Hassanein and Hussainey, 2015). As well to differentiate themselves from less successful firms and decrease their capital costs (Frias-Aceituno et al., 2014).

However, others such as Aljifri and Hussainey (2007) and Celik et al. (2006) found a significant negative relation between PROF and FLID; indicating that firms with high profitability are more probable to disclose less FLID. One possible explanation for this result is that firms with low profitability would be likely to disclose more FLI and deliver a positive message to the stakeholders. This information generally contains plans and projects which could signal strong reactions, mainly to the market (Aljifri and Hussainey, 2007). Thus, based on this discussion, the following hypothesis is developed:

H₁: There is a positive association between profitability and the level of FLID in annual reports narrative sections of Lebanese commercial banks.

Size

The key findings of prior research concerning the relationship between firm size (SIZ) and FLID are diverse. Aljifri et al. (2013); Menicucci (2013); Mathuva (2012) and Aljifri and Hussainey (2007) found no significant relationship. This reveals that firm SIZ not make a strong and exclusive contribution to explaining the level of FLID.

Whereas, Mousa and ElAmir (2018); K?l?ç and Kuzey (2018); Menicucci (2018); Menicucci and Paolucci (2017); Mohammadi and Jamali (2017); Zhafarina (2017); Pratoomsuwan and Vu (2016); Alkhatib (2014); Uyar and Kilic (2012) and Celik et al. (2006) found a positive significant relationship.

There are numerous explanations for such a positive relationship. Since larger firms are more exposed to public inspection than smaller firms are, they are likely to disclose more information (Alsaeed, 2006). Larger firms have a tendency to disclose more future-oriented information to satisfy a more demand of information by numerous stakeholders, particularly financial analysts (Hussainey and Al-Najjar, 2011). Larger firms have more resources to afford the cost of producing information compared to smaller ones (Aljifri and Hussainey, 2007). Larger firms face a higher level of agency costs affiliated with high-level information asymmetry compared to small firms (Celik et al., 2006). Large firms might have several resources to maintain additional information costs if they provide more disclosure that is pertinent to diverse users (Hassan et al., 2006). Thereby, based on the above argument, the following hypothesis is developed:

H₂: There is a positive association between size and the level of FLID in annual reports narrative sections of Lebanese commercial banks.

Leverage

As regards to the relationship between leverage (LEV) and FLID, evidence from studies are quite varied. For instance, Menicucci (2018); Menicucci and Paolucci (2017); Mohammadi and Jamali (2017); Alkhatib (2014); Menicucci (2013); Uyar and Kilic (2012) and Celik et al. (2006) found no evidence for a relationship between LEV and FLID. This reveals that LEV has an insignificant influence on the level of FLID.

However, others such as Mousa and ElAmir (2018); Aljifri et al. (2013); Mathuva (2012) and Aljifri and Hussainey (2007) reported a significant positive association of LEV on the level of FLID. The positive association could be explained by the fact that, highly leveraged firms may deal with greater agency costs because of excessive auditing fees; so, they will have to disclose more information (Alkhatib, 2014). Further, firms with higher LEV may be likely to disclose more FLI to decline risk premiums in required rates of return on equity (Aljifri and Hussainey, 2007); to gratify their creditors’ information needs (Wang and Hussainey, 2013); and to restore confidence to their shareholders (Aljifri and Hussainey, 2007).

This is in contrast to the studies of K?l?ç and Kuzey (2018); Zhafarina (2017) and Pratoomsuwan and Vu (2016) that demonstrate a negative association exits between LEV and FLID. This could be interpreted that high LEV firms can be regarded as riskier and in essence, managers of these firms are hesitant to provide information to guard themselves from public inspection (Pratoomsuwan and Vu, 2016). Therefore, based on this reasoning, the following hypothesis is developed:

H₃: There is a positive association between leverage and the level of FLID in annual reports narrative sections of Lebanese commercial banks.

Liquidity

As for the relationship between liquidity (LIQ) and FLID, evidence from studies are quite diverse. Surprisingly, few studies have examined the relationship between the two variables. For instance, Mousa and ElAmir (2018) and Mathuva (2012) found no statistical relationship between LIQ and FLID indicating that LIQ has no significant impact on FLID. However, Zhafarina (2017) found a negative association between the two variables suggesting that firms with lower LIQ provide more information in their annual reports. Consequently, based on the previous studies, the following hypothesis is formulated:

H₄: There is a positive association between liquidity and the level of FLID in annual reports narrative sections of Lebanese commercial banks.

Age

Concerning the relationship between age (AG) and FLID, one research only exists that has studied the relationship between the two variables; hence, a gap exists in the related literature. Uyar and Kilic (2012) conducted the only study that examines the association between AG and FLID. They examine the association between AG and FLID in the annual reports of Turkish corporations for the year ended in 2010. The key results revealed that a significant association was not found between AG and FLID demonstrating that AG is insignificant variable in explaining FLID level. Thus, it seems reasonable to postulate the following hypothesis:

H₅: There is a positive association between age and the level of FLID in annual reports narrative sections of Lebanese commercial banks.

Capital Expenditures

With respect to the relationship between capital expenditures (CE) and FLID, one study only exists that has examined the association between the two variables; hence a gap exists in the related literature. Mathuva (2012) conducted the only study that investigates the association between CE and FLID. Mathuva (2012) examined the effect of CE on FLID in the interim financial reports of non-financial firms listed on the Nairobi Securities Exchange for the mid interim periods between 2009 and 2011. The results revealed that the level of FLID is positively related with CE. This finding seems to suggest that the more CE a firm has, the more the level of FLID it provides. The increase FILD is meant to explain to the stakeholders how the firm is presently using its investment in non-current assets. Accordingly, based on the findings of the empirical research, the following hypothesis is proposed:

H₆: There is a positive association between capital expenditure and the level of FLID in annual reports narrative sections of Lebanese commercial banks.

Research Methodology

Data Collection

The list of the names and the websites of the banks included in this research is obtained from association of banks in Lebanon (ABL) official websites. The required data about the variables have been manually extracted. It then calculated from the published annual reports of a sample of banks from their official website for a period of ten consecutive years 2008-2017. Although there are a wide variety of media for information disclosure, however, the annual report has been chosen in this research because it is considered the main source of information disclosure and significant communication tool to diverse user groups (Uyar, 2011). The data is accessible directly free since annual reports of Lebanese commercial banks are published officially on the website; thus, there is no need to spend time to do additional survey to obtain accurate data.

Sample Selection

The whole population of Lebanon banks consists of 65 banks divided as 50 commercial banks and 15 investment banks (ABL, 2019). This research only studies the commercial banks excluding specialized banks, which are involved in only one kind of services in order to enhance comparability among the banks. 21 banks were excluded from the 50 banks due to the unavailability of data, and thus, the research is left with a sample of 29 banks (appendix 1). This sample constitutes 58 percent (29/50) of the total commercial banks in Lebanon. These 29 banks are classified into four different groups according to their total deposits. Alpha group (α) includes 17 banks (58.6%); Beta group (β) includes six banks (20.7%); Gamma group (γ) includes four banks (13.8%) and Delta group (δ) includes two banks (6.9%).

Appendix 1 Sample of the Research
1. BLOM BANK S.A.L.	Alpha	16. CREDIT LIBANAIS S.A.L.	Alpha
2. BANK MED S.A.L.	Alpha	17. FENICIA BANK S.A.L.	Beta
3. BANK OF BEIRUT S.A.L.	Alpha	18. AUDI PRIVATE BANK S.A.L.	Alpha
4. FRANSABANK S.A.L.	Alpha	19. SARADAR BANK S.A.L.	Alpha
5. BANQUE LIBANO-FRANCAISE S.A.L.	Alpha	20. IBL BANK SAL	Alpha
6. B.L.C. BANK S.A.L.	Alpha	21. BANK AUDI S.A.L.	Alpha
7. FEDERAL BANK OF LEBANON S.A.L.	Beta	22. BANQUE BEMO S.A.L.	Beta
8. SOCIETE GENERALE DE BANQUE AU LIBAN S.A.L.	Alpha	23. CREDITBANK S.A.L.	Alpha
9. BBAC S.A.L.	Alpha	24. BANQUE MISR LIBAN S.A.L.	Gamma
10. BYBLOS BANK S.A.L.	Alpha	25. NORTH AFRICA COMMERCIAL BANK S.A.L.	Gamma
11. JAMMAL TRUST BANK S.A.L.	Gamma	26. NATIONAL BANK OF KUWAIT (LEBANON) S.A.L.	Gamma
12. LEBANON AND GULF BANK S.A.L.	Alpha	27. ARAB BANK P.L.C.	Beta
13. MEAB S.A.L.	Beta	28. ARAB AFRICAN INTERNATIONAL BANK	Delta
14. FIRST NATIONAL BANK S.A.L.	Alpha	29. QATAR NATIONAL BANK S.A.Q. - Lebanon	Delta
15. BSL BANK S.A.L.	Beta

The choice of the banks was based on the availability and consistency of data over the period from 2008 to 2017. The data were collected manually from the available reports. It should be noted that the reason for selecting this time-period is mainly due to the progress realized by the Lebanese banking sector over the last ten years because of the appropriate and strong bank regulation and supervision undertaken by the BDL and BCC and the close cooperation of the ABL.

Content Analysis

Parallel to many earlier studies, this research has used bank’s annual reports for data gathering. More specifically, data was collected by analyzing narrative sections (chairmen’s letters) of annual reports of Lebanese commercial banks for the period 2008-2017. Content analysis method, which has been utilized to measure the extent of FLID of firms in numerous preceding research, was used in this research as well. Each annual report was investigated manually. The reason for choosing manual content analysis is due to it has several advantages over competing choices. It “can be applied to examine any written document, as well as pictures, videos, and situations. It is widely used and understood. It can help decipher trends in groups or individuals. It is inexpensive, and can be easily repeated if problems arise. It is unobtrusive and does not necessarily require contact with people. It is useful for analyzing archival material. Establishing reliability is easy and straightforward. Of all the research methods, content analysis scores highest with regard to ease of replication usually the materials can be made available for others to use” (Vitouladiti, 2014).

To identify the sentences that provide FLI, this research follows the same list of keywords utilized by Hussainey et al. (2003), Aljifri and Hussainey (2007), as well Aljifri et al. (2013) with some modification. More specifically, a pilot study was taken based on five annual reports of the Lebanese commercial bank. This led to adding of some additional keywords suitable for the Lebanese reporting environment. The keywords are presented in Table 2.

Table 2 List of Forward-Looking Key Words
Accelerate	Anticipate	Approximate	Assume	Assurance
Assure	Await	Believe	Coming (Financial) Year(S)	Coming Months
Confidence	Confident	Convince	Courage	(Current) Financial Year
Current Risks	Envisage	Estimate	Evaluate	Eventual
Expect	Following	Forecast	Forthcoming	Hope
Influence	Innovative	Intend	Intention	Keep on
Likely	Look Forward	Look Ahead	May	Must
Next	Novel	Optimistic	Ought	Outlook
Persuade	Plan	Planned	Planning	Positive
Predict	Prediction	Present	Prospect	Questionable
Remain	Renew	Renovate	Satisfy	Scope For
Scope To	Seek	Shall	Shortly	Should
Soon	Target	Uncertainties	Unlikely	Well Placed
Well Positioned	Will	Would

Measurement of Variables

Independent Variables

Several methods have been used in prior research to measure the variables of this research (Table 3).

Table. 3 Measurement of Variables Based on Prior Studies
PROF	• Dividing net income by net sales (Aljifri & Hussainey, 2007) • Return on total assets (K?l?ç & Kuzey, 2018; Mohammadi & Jamali, 2017; Alkhatib, 2014) • Net income after tax scaled by shareholders funds (Mathuva, 2012) • Return on equity (Menicucci, 2018; Uyar and Kilic, 2012) • Amount of profit disclosed by the firms at the end of period (Celik et al., 2006)
SIZ	• Natural logarithm of the company’s sales (Aljifri & Hussainey, 2007)• Natural logarithm of total assets (K?l?ç & Kuzey, 2018; Menicucci, 2018; Pratoomsuwan & Vu, 2016; Mohammadi & Jamali, 2017; Alkhatib, 2014; Aljifri et al., 2013; Mathuva, 2012)• Total sales revenues (Uyar and Kilic, 2012) • Market capitalization (Celik et al., 2006)
LEV	• Dividing total debt by total assets (K?l?ç & Kuzey, 2018; Pratoomsuwan & Vu, 2016; Alkhatib, 2014; Mathuva, 2012; Uyar and Kilic, 2012; Aljifri & Hussainey, 2007) • Proportion of total assets to total liabilities (Aljifri et al., 2013)
LIQ	• Current assets scaled by current liabilities (Mathuva, 2012)
AG	• Listing age (Uyar and Kilic, 2012)
CE	• Ratio of non-current assets scaled by total assets (Mathuva, 2012)

Although the variety of these measures; there is no prevailing theoretical reason to choose one measure rather than another. However, for the purpose of this research, profitability is measured as the percentage of net profit to total assets return on assets (ROA=net income/total assets). Indeed, ROA has been selected because it is a good indicator of an organization‘s profitability (Bergmark and Dahlberg, 2015). It has been used in multiple prior studies. It is one of popular profitability measures (Joo et al., 2011). As well as it is one of the best measurements of efficiency in order to assess the bank‘s performance (Byard and Cebenoyan, 2007). As there is no prevailing theoretical reason to choose one measure rather than another total assets have been selected to measure size of the bank because data regarding total assets are available and they are considered the most popular firm size proxies (Dang and Li, 2015). However, this variable was transformed into Log total assets because it was not normally distributed. Thus, the SIZ of the bank is measured by the natural logarithm of total assets following Menicucci (2018); K?l?ç and Kuzey (2018); Mohammadi and Jamali (2017) and many others. LEV is measured by dividing total liabilities by total assets (Aljifri and Hussainey, 2007; Mathuva, 2012; Uyar and Kilic, 2012; Aljifri et al., 2013; Alkhatib, 2014; Pratoomsuwa and Vu, 2016; Mohammadi and Jamali, 2017; K?l?ç and Kuzey, 2018). LIQ is measured by dividing banks total loans to total deposits (Qin and Pastory, 2012; Adam, 2014). The AG of the bank is measured by the number of years the commercial bank has been operating in Lebanon (Uyar and Kilic, 2012). CE is measured by dividing non-current assets by total assets (Mathuva, 2012).

Dependent Variable

In this research, in order to measure the extent of FLID, data were manually extracted from the chairmen’s letters of the annual reports of Lebanese commercial banks. A disclosure index is then considered on the bases of an item does exit or does not exist in the chairman’s letter that refers to FLI. More specifically, narrative section (mainly the chairman’s letter) for each bank was examined and banks are awarded one point for each relevant sentence and zero for non-relevant sentence. The sentence was considered relevant if it contains forward-looking key word and non-relevant otherwise (Celik et al., 2006; Aljifri and Hussainey, 2007; Mathuva, 2012; Uyar and Kilic, 2012; Aljifri et al., 2013; Alkhatib, 2014; Pratoomsuwa and Vu, 2016; Mohammadi and Jamali, 2017; K?l?ç and Kuzey, 2018). Thus, the extent of FLID was measured as the ratio of the value of the number of relevant sentences (forward-looking sentences) a bank discloses divided by the total sentences in its narrative sections. The disclosure index can be shown as follows:

TDS= FWD/TD

Where:

TDS: Total Disclosure Score

FWD: Total forward-looking sentences disclosed in the narrative section for each bank

TD: total sentences disclosed in the narrative section for each bank.

The Model

An OLS regression model was utilized to test the hypotheses of this research. The model explains the effect of some selected bank characteristics on the level of disclosure of FLI. The model can be stated as follows:

TDS= β₀ + β₁X₁ + β₂X₂ + β₃X₃ + β₄X₄+ β₅X₅+ β₆X₆ + ε

Where: X₁= PROF; X₂= SIZ; X₃= LEV; X₄= LIQ; X₅= AG; X₆= CE; and ε = Error Term.

Research Findings

Descriptive Statistics

Table 4 reports the minimum, maximum, mean, standard deviation (SD), skewness and kurtosis for the variables in the sample data set. The PROF ranges from 0.000 to 0.031 with a mean of 0.009 and a SD of 0.006. The SIZ (in logarithms) range from 5.640 to 12.000 with a mean of 8.091 and a SD of 1.612, while the debt equity ratio ranges from 0.801 to 0.927 with a mean of 0.897 and SD of 0.033. The loans to deposits ratio ranges from 0.000 to 1.000 with a mean of 0.276 and a SD of 0.448, whereas the banks AG ranges from 1.000 (less than 50 years) to 4.000 (more than 150 years) with a mean of 1.748 and a SD of 0.731. The CE ranges from 0.000 to 0.316 with a mean of 0.029 and a SD of 0.055. The table also provides some information about disclosure. The extent of disclosure of FLI ranges from 0.000 to 1.000 with a mean of 0.621 and a SD of 0.486. The coefficients of skewness and kurtosis in Table 4 show that all the variables are normally distributed. A normal distribution should have a skewness equal to zero and a kurtosis equal to 3, although this fact, however, an absolute skewness value ≤2 or an absolute kurtosis (excess) ≤4 may be used as reference values for determining considerable normality (Kim, 2013).

Table 4 Descriptive Statistics
Description	Minimum	Maximum	Mean	Std. Deviation	Skewness	Kurtosis
TDS	0.000	1.000	0.621	0.486	0.030	-0.730
PROF	0.000	0.031	0.009	0.006	1.486	2.894
SIZ	5.640	12.000	8.091	1.612	0.229	-1.365
LEV	0.801	0.927	0.897	0.033	-1.919	2.514
LIQ	0.000	1.000	0.276	0.448	0.910	1.020
AG	1.000	4.000	1.748	0.731	1.232	2.305
CE	0.000	0.316	0.029	0.055	0.832	0.392

Correlation Analysis

The correlation between each of the variables is not excessively high as shown in Table 5. The highest correlation found between PROF and CE (-0.365) is very satisfactory. Table 5 also presents the variance inflation factor (VIF), and the results show that the VIF was lower than the threshold value "3" for each of the independent variables, which reveals the absence of the problem of multi-collinearity (Chakroun and Hussainey, 2014).

Table 5 Correlation Analysis
	TDS	PROF	SIZE	LEV	LIQ	AGE	CE	VIF
TDS	1.000
PROF	0.051	1.000						1.21
SIZE	0.045	-0.105	1.000					1.15
LEV	0.001	-0.078	0.009	1.000				1.17
LIQ	-0.299	-0.110	0.079	0.000	1.000			1.18
AGE	-0.057	0.057	-0.189	0.247	-0.104	1.000		1.12
CE	0.118	-0.365	-0.017	-0.059	-0.009	-0.026	1.000	1.18

Regression Analysis

As in many prior disclosure studies, multivariate analysis is carried out using an OLSregression model in order to explore the effect of specific characteristics on the level of FLI in the annual reports of the selected banks. Regression coefficients and their p-values are presented in Table 6, which shows the contribution of the independent variables to the model.

Table 6 Regression Analysis
Determinants	Un-standardized coef?cients B	Std. error	t	Sig.
(Constant)	-0.723	0.956	-0.756	0.450
PROF	9.467	4.973	1.904	0.050
SIZ	-0.031	0.018	-1.761	0.079
LEV	1.670	1.047	1.595	0.112
LIQ	0.182	0.066	2.747	0.006
AG	-0.063	0.042	-1.510	0.132
CE	2.135	0.617	3.461	0.001
TDS	-0.723	0.956	-0.756	0.450

The contributions of PROF, LIQ and CE (p ≤ 0.05) are found to be statistically significant. The direction of the first coefficient (PROF) suggests that banks with high PROF are more likely to disclose more FLI. Thus, H₁ is supported. This is consistent with the results of previous disclosure studies of Menicucci (2018); Menicucci and Paolucci (2017); Mohammadi and Jamali (2017); Zhafarina (2017); Pratoomsuwan and Vu (2016); Alkhatib (2014); Menicucci (2013) and Mathuva (2012) who find a positive association between PROF and the extent of disclosure. This could be explained by the fact that banks that are more profitable are more positive about the future and thus, these banks are motivated to provide more future information. Furthermore, banks that are more profitable may disclose more FLI as they want to distinguish themselves from the less profitable banks and improve their competitive advantage from the market (Pratoomsuwan and Vu, 2016).

Regarding the second coefficient (LIQ), the results indicate that banks with high loans to deposits ratio are more likely to disclose FLI. Thus, H₄ is supported. The results of this research are inconsistent with previous studies that report no association between LIQ and the extent of information disclosure (Mousa and ElAmir, 2018; Mathuva, 2012). One possible explanation for this result is that banks with a higher degree of LIQ maintain a sounder financial position. Thus, they are keener to disclose information than those experiencing a low degree of LIQ (Lan et al., 2013).

Concerning the third coefficient (CE), the results reveal that CE is associated with higher disclosure of FLI. Thus, H₆ is supported. This is consistent with the result of previous research of Mathuva (2012). This could be explained by the fact that banks provide more disclosures if their investments in CE is expected to increase. This implies that further disclosures would be meant to diminish agency problems and increase investor confidence in the bank’s management (Mathuva, 2012).

Conversely, SIZ, LEV, and AG variables are found to have an insignificant impact on the level of disclosure. This is in contrast to hypotheses (H₂, H₃, and H₅). However, these results are consistent with a number of research which report an insignificant association between these variables and the level of disclosure (Menicucci, 2018; Menicucci and Paolucci, 2017; Mohammadi and Jamali, 2017; Alkhatib, 2014; Aljifri et al., 2013; Menicucci, 2013; Mathuva, 2012; Uyar & Kilic, 2012; Aljifri and Hussainey, 2007; Celik et al., 2006).

The reported insignificant result between SIZ and FLID indicates that banks of differing SIZ tend to have no significant differences in their FLID (Aljifri and Hussainey, 2007). From this result, it can be indicated that banks often assess the cost-benefit of such disclosures and if the cost surpasses the benefit, disclosure of FLI may not be made regardless of the bank SIZ (Nawaiseh et al., 2015).

The insignificant relationship between LEV and FLID in this research indicate that higher debt to equity ratio does not make banks disclose more information; the obligations and commitments included in the bank are essentially an agreement between the creditors and the bank. Upon appraisal, the creditor providing credit or loan will take into consideration numerous factors such as character, the capability to borrow, the aptitude to produce revenue, capital, collateral and broad economic conditions (Jaya et al., 2016).

Bank AG was expected to have positive impact on FLID. However, hypothesis testing yielded no significant result. Thus, FLID is independent of bank AG. This result can be explained by the fact that recently operated banks need to disclose more information to minimize scepticism and enhance confidence of investors who may recognize them as riskier (Haniffa and Cooke, 2002).

Conclusions, Limitations and Future Research

In light of increasing importance on corporate information transparency, particularly FLI, this research aims to explore the effect of six main variables on the extent of FLID in the narrative sections of the annual reports of 29 Lebanese commercial banks for the period 2008 to 2017. For this purpose, different theoretical approaches were employed, notable agency theory, signaling theory, stakeholder theory and legitimacy theory.

An interesting number of findings emerge. First, the results reveal that PROF, LIQ, and CE is associated with higher disclosure of FLI. These findings were consistent with the findings of some prior research studies. Hence, it suggests that Lebanese commercial banks who experience a significant increase in loans to deposits ratio and a significant increase in ROA as well as significant increase in CE are more likely to disclose more FLI. Specifically, more profitable- banks tend to have a superior bargaining power. They are thus capable to source funds from numerous sources. Providing more FLID aids as a means of showing that they are profitable and this enhances investor and creditor trust in the bank (Mathuva, 2012). Further, highly - liquid banks have greater monitoring costs. Such banks may seek out to diminish these costs by disclosing more information in their annual report narrative (Elshandidy et al., 2013). In addition, the bank that has invested greatly in capital investments is likely to disclose more FLI (Mathuva, 2012).

Second, a strong association between each of SIZ, LEV as well as AG and FLID was not found. The lack of a significant relationship between these variables and FLID suggests that banks of differing sizes, with different years of operations, with different debt ratios, tend to have no significant differences in their FLID.

The findings of this research have important implications. First, the results provide comprehensive insight into the current FLID practices in Lebanon and can be a useful evidence for preparers of financial reporting, since in Lebanon no research paper yet has examined the determinants of FLI in chairman’s letter. Secondly, the research will assist Lebanese and Middle Eastern investors in their decision-making process and will especially be significant for the institutional investors looking for profitable and secure investment opportunities. This research has also practical implications especially for managers, who may strategically use this information when they design disclosure policies to influence investors. Moreover, this research has also implications for regulators in the preparation of rules and recommendations about disclosure requirements since it encourages further efforts to promote FLI. Furthermore, the present research has some implications for banks. As FLI is among the most disclosed items in analyst reports, analysts attribute great importance to FLI, and put forward this information in attracting attentions of investors’ banks’ shares. Therefore, banks should behave in accordance with the knowledge that investors take their positions primarily based on future expectations. Thus, FLID practices of Lebanese commercial banks could be improved by initiatives of regulatory bodies and auditing firms and stakeholders’ information demand from banks. Overall, this research provides readers with an overview of the current state of corporate FLID in Lebanon. Consequently, the research recommends Lebanese commercial banks to provide more FLI in their annual reports to efficiently decrease informational asymmetries between the management and owners of the banks.

This research has some limitations; the research was conducted exclusively on banking industry; the results may not be generalizable for other industries such as manufacturing and merchandising industries. The sample of research contained a small number of banks due to the data access problem. Therefore, the small sample size restricts the generalizability of the results. This research utilized solely the annual reports of banks as the information disclosure source; further sources such as web sites, press releases, and prospectuses were not used. The research investigates the impact of six bank characteristics and ignores others. Finally, the findings of the research may not be generalised to different countries with different environments.

Further research could address the following suggestions; making a new research to investigate the impact of bank characteristics on FLID in the annual reports of financial and nonfinancial institutions. New research may be conducted by increasing the number of banks to rise the strength of evidence that presented in this research. Future research is encouraged to examine information disclosure in different channels such as newspaper, media or website. Future research is also needed to embrace more bank characteristics variables and corporate governance attributes. Future researches may need to conduct in other countries.

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