Effects of Board Size, Board Committees Characteristics and Audit Quality on Audit Report Lags


The paper examines the effects of board size, audit committee characteristics and audit quality on audit report lag (ARL) of listed banks in Nigeria. Using a sample of 14 banks, the study covers a five year period from 2008 to 2012. The findings of the study based on robust OLS model reveals that audit quality represented by the Big 4 firms has a significant impact on ARL. Board size, board meetings, total assets as well as board gender also have significant positive associations with ARL. However, the study is not able to find a significant relationship between audit committee size, risk management committee size and board expertise on ARL. Generally, shareholders should maintain the use of big 4 so that report is presented at the right time to enhance confidence of the stakeholders as well as regulators. The current study is limited to few corporate governance characteristics of the listed banks. Other potentials variables such as Company complexity, ethnicity, leverage and IFRS complexity is not included and beyond the scope of this study. Their inclusions could have given clearer picture of the determinants of Audit Report Lag in Nigerian listed banks.

Keywords: Audit report lagboard sizeaudit committee sizerisk management committee sizeaudit quality


Audit report lag is the number of days from company’s financial year end to audit report date (Lee & Jahng, 2008). ARL plays a key role in transforming audit information to the stock market (Lai et al., 2005). Afify (2009) argues that ARL is one of the basic indices of audit efficiency and thus, should be timely. In the same vein, regulators, professional accountants and auditors have considered timeliness of financial reporting as one of the most important features of financial reporting quality (Hendriksen & Breda, 1992; McGee & Tarangelo, 2008).

Several prior studies in developed countries have provided empirical evidence that audit timeliness is the most influential factor in the audit of financial statements (Al-Sehali & Spear, 2004). Further researches have been conducted on the causes of audit report lag (ARL) by Leventis & Ceramanic, (2005). The results of their studies indicate that ARL is affected by client size, complexity of an audit, and types of transaction information. Moreover, Jaggi & Tsui (1999) also find shorter ARL in their study signifying more timely information. Similarly, Alali and Elder (2014) argue that ARL is determined by such factors as profitability, size, restatement and abnormal fees. In a most recent study, Blankley et al., (2015) find a positive relationship between unexpected ARLs and future restatements.

Prior empirical studies dwell on audit report lags from various emerging economies across the globe. For instance, on Malaysian emerging economy (Che-Ahmad & Abidin, 2008) conclude that their study is consistent with previous studies done in Western countries. Their findings report size, directors’ shareholdings, and complexity, size of auditor, audit opinion and profitability as the major determinants of audit delay. This study investigates whether board of director’s size through different board committees, such as audit committee size, risk management committee size and audit quality impact positively on audit report lags of listed banks in Nigeria, and to the best of the researcher’s knowledge, this study is either among the few or one of the pioneer studies of audit report lag in Nigerian banking sector.

Literature Review and Hypothesis Development

Audit Report Lag

Studies on audit reporting have been on for more than three decades. Empirical study by (Beaver, 1968; Gilling, 1977; and Davies & Whittered, 1980) state that ARL is determined by company’s fiscal year end at the highest of its audit season in non-financial companies. In contrast, studies by Whittered & Zimmer, (1984) show that longer ARL is associated with companies that have qualified audit opinion or those in distressed financial situations. In the same vein, study by Ashton et al., (1987) show that ARL is determined by company size, complexity of operation, listing status, profitability and risk factors. In addition, Carslaw & Kaplan, (1991) found company debt as determinant of audit report lags. Ashton, et al., (1989) argued that ARL is generally longer for highly structured audit firms than audit firms with critical audit process (Henderson & Kaplan, 2000).

Additionally, Alali and Elder (2014) found profitability; size, restatements and abnormal audit fees are significant determinants of ARL. Whilst abnormal audit fees significantly relate with ARL, the provision of non-audit services is associated with shorter ARL for large banks but not for small banks. A most recent study by Blankley et al., (2015) found that there is a positive association between unexpected ARLs and future restatements. Moreover, the authors argued that companies with unexpected delays in their audits were subject to increased time pressure.

Audit Quality

Accounting literature have shown that large audit firms provide higher quality audits and therefore, offer more credible financial statements than small audit firms (Eichenseher et al., 1989). It is argued that with the increased presence of institutional investors in developing countries and emerging capital markets, an effective audit by ‘Big 4’ is seen as precondition for the success of financial institutions (Gillan & Starks, 2003).

However, Che-Ahmad & Houghton, (1996) analysed the supply of auditors to medium-size companies of UK and Australia; they found that Big eight auditors are not paid higher premium than other auditors in the sector. Their study was also in line with much previous research which found Company’s size; Risk and complexity significantly determine audit fees. However, auditor location was insignificant predictor of audit fees. Consequently, it is hypothesized that:

H1: There is a significant relationship between audit quality and Audit report lag.

Board Size

Board size plays an important role in corporate governance of listed companies in Nigeria and the world in general (Salihi & Jibrin, 2015). Several empirical researches in accounting literature argued as to whether or not small or large board is effectively enhancing the quality of management responsibilities (Hassan, 2016). Larger board according to Akhtaruddin et al., (2009) with their collective expertise will be more capable of executing their duties and will equally abridge management control (Hussainey & Wang, 2010). In addition, Jensen (1993) indicated that board with at least eight members may be efficient and serve as an effective board performance. Based on the importance of board size and previous literature it is hypothesized that:

H2: There is a significant relationship between board size and audit report lag.

Audit Committee Size

The size of audit committee determines the effectiveness of committee’s ability to discharge its responsibilities (Al-Matari et al., 2012). Extant literature has shown that three members should be ideal size of this committee New York Stock Exchange, (2002). However, in Nigeria, Security and Exchange Commission (SEC) is required under section 359 (3 & 4) of Companies and Allied Matters Act (1990) to provide six members as audit committee size, which comprises of three directors and three shareholders. A study by Kim & Yoon (2005) showed that there is positive and significant relationship between audit committee size and earning management in Korean listed firm. Other study by Hamdam et al ., (2009) revealed negative relationship between audit committee size and earning management in Jordanian companies.

H3: There is a significant relationship between audit committee size and audit report lag.

Risk Management Committee Size

Corporate attention has been given to risk related factors in order to enhance the confidence of investors, hence, managers are compelled to properly explain how risk are being managed and to enable the investors assess corporate information and performance (Hassan, 2014; Oliveira, 2011). The strategy and policy used by the board of directors in managing risks have a positive impact on prospective investors (Oliveira et al., 2013). In Nigeria, the risk management committee size is determined by the board of directors (SEC, 2011). It is therefore hypothesized that:

H4: There is a significant relationship between risk management committee size and audit report lag.

Board Meeting

In his study, Vefeas (1999) found that, effective corporate governance has significant relationship with meeting frequency. Additionally, Cheung et al., (2010) reported that good corporate governance eminent from frequent committee meetings and associated with lower risk and higher stock returns. Therefore, the study hypothesized that:

H5: there is a significant relationship between Board meeting frequency and audit report lag.

Board Committees

Board of directors over the world often establish board committees and assign some responsibilities to make decisions which enhance corporate strategies (Jiraporn et al., 2008). These important committees such as audit committee, risk committee, finance and accounting committee’s performance have influence corporate activities much more than the overall board (Klein, 1998). The study hypothesized that:

H6: There is a significant relationship between board committee and audit report lag.

Board Committee Expertise

The role played by Board of directors is central to the company’s control and decision (Fama & Jensen 1983) thus, displaying their expertise mainly on monitoring and advising top and senior managers. Several researches have focus particularly on director’s expertise in financial, advice and political connections Kang et al., (2013). Consequently, Güner et al ., (2008) show that, even within non-financial firms, the inclusion of financial experts on board can positively affect corporate decisions. It is hypothesized that there is a significant relationship between board expertise and audit report lag.

Board Committee Gender

Mingeuez-Vera (2007) found that there is a significant impact of percentage of women on the board of directors. In the same manner, Adams and Ferreira, (2009) revealed a positive effect of female director on the company’s performance. Thus, the study hypothesized that;

H8: There is a significant relationship between female on the board committee and audit report lag.

Control Variables

Firm Size

The present study control for firm size, firm size is the book value of total assets using its natural log. The study therefore, measured the size of the firm as: Log total assets (Anderson et al., 2003). Based on previous studies, it is expected that increase in firm size will lead to shorter audit report lag.


The risk factor in a company is measure by either profit or loss, this study control for risk committee size by loss. Following Alali and Elder (2014) the variable is measured using dummy variable; one if bank report net loss and zero otherwise.

Research Methodology

The study uses secondary data obtained from the company’s annual reports and accounts. The study cover listed Nigerian banks within the period of five years from 2008 to 2012. The populations of this study comprise of 14 banks that are listed on Nigerian Stock Exchange (NSE) as at December 31, 2012. This study employ panel data technique to analyse the relationship between audit quality, audit committee size, risk committee size, board meeting frequency, board committees and board committee gender and audit report lag in Nigeria. The model is specified in Equation [1].

ARLit = β0 + β1AUDQit + β2BSIZEit + β3ACSIZEit + β4RCSIZE+ β5BMEETit + β6BCMTsit +

β7BCEXPTit + β8BCGEN + β9LTASSET + β10LOSS + Ɛit (1)

where ARL is audit report lag, AUDQ means audit quality, BSIZE, ACSIZE, RCSIZE, BMEET, BCMTs, BCEXPT, BCGEN represent board size, audit committee size, risk committee size, board meeting, board committees, board expertise, board committee gender. LTASSET and LOSS represent log total and net loss respectively. The symbol Ɛ denotes error term which is white noise process and the subscripts ‘it” indicates entity over time.

Result and Discussion

The descriptive statistics indicates (not reported here base on space limitation) that the Nigerian listed banks approximately take 4 months before audited report is presented to shareholders. Moreover, most of the banks seem not to comply with regulatory dateline of 90 days. The descriptive results indicate serious variations between year-end and first presentation of financial reporting.

Panel Model Selection Criteria

Based on the data characteristics, two different tests are conducted to determine the appropriateness of the preferred panel model. These are Hausman specification test and Breusch and Pagan Lagrange Multiplier (B-P LM), the former reveals not significant probability value indicating that random effect model is preferred over fixed effect model, while the latter is to determine preferred model between random effect and pooled ordinary least squares (OLS) model. The result shows that the test is not significant thus, favouring pooled OLS regression over the random effect model. Although the random and pooled OLS results seem to be the same but the statistical test distinguish between the two in favour of OLS. The possible differences are normally related to factors such as managerial style and philosophy of the sampled entities. However, in the present study, the result shows that the variations are not distinct to account for such differences. Therefore, the study presents the robust OLS result in Table 1 below.

Table 1 -
See Full Size >

Table 1 depicts the panel regression result. The pooled OLS result show that four of the eight independent variables, AUDQ, BSIZE, BMEET and BCGEN have relationship with audit report lag. The result indicates that on average using Big4 audit firm reduces audit report lag by approximately 48 days. This result is consistent with Alali & Elder, (2014) where engaging Big 4 audit firms reduce audit report lag due to their expertise and availability of technology which is line with the study hypothesis. In the same manner, one additional member in to the board size reduces audit delay by averagely four days.

Moreover, board meeting frequency indicates that on average additional one sitting of the board of directors in the banks reduces audit report lags by approximately 6 days. Furthermore, board committee gender show negative results at 1% (0.001) level of significance indicating that, on average increase in one board female member leads to corresponding reduction of audit report lags by 11 days. The results also show that, ACSIZE, RCSIZE, and BCMTS are negative but not significantly associated with audit report lag. Though the three variables are not significant, however, the results indicate that on average addition of one member to the committees will reduce audit report lay by 4days, 1day and 4days respectively. However, BCEXPT is positive but not significantly associate with audit report lag this implies that increase in one expertise member will increase ARL by an average of 6 days.

Consequently, the result further indicates that size of the company as measured by total assets was negative and not significant therefore; it reduces ARL by 2 days on average. This is similarly documented in some previous studies (Hossaini & Tailor, 1998; Carslaw & Kaplan, 1991). Moreover, the size of the firm may reduce ARL due to effective monitoring by trade unions, regulators and investors (Ashton, et al., 1989).

The model adequacy is assessed using wald chi square statistics. Additionally, the significant wild chi2 statistics (50.32) at 1% (p-value = 0.0000) indicates that the whole model is statistically fit. It further confirms the theoretical and statistical relationship between audit report lag and independent variables. Similarly, R2 is another measure for model fitness. Interestingly, the coefficient of determination has explained 47% variation in audit report lag by the regressors in the model. In line with econometric modelling, the OLS estimate (model 4) in Table 4.1 has been subjected to robust estimation to ensure that the model meets the basic OLS assumptions. The model is free from the problems of heteroskedasticity, normality, model specification and multi collinearity.


The paper examines the relationship between corporate governance characteristics such board size, audit committee size and risk management committee size and audit report lag in Nigerian listed banks. 14 out of 17 banks were used in the study due to data availability. Data were collected from corporate governance report section of the annual reports and accounts of all the 14 banks that made up of the sample from 2008 to 2012. The result highlights the importance of audit report lags in respect of the impact of the timeliness of earning announcement of the banks. The findings further reveal the minimum and maximum period for banks to present financial report to shareholders is 55 and 330 days respectively, signifying non-compliance with regulations. The effect of Big 4 audit firms on audit report lag is consistent with studies by Ali and Elder (2014). The result also indicates that including women in the various committees shortens audit report lag. In addition, board size and board meeting also reduce audit report lag. Generally, shareholders should maintain the use of big 4 so that report is presented at the right time to enhance confidence of the stakeholders as well as regulators. This study adds to the literature by providing new evidence on the ability of various committees’ impact on determining audit report lag. However, the study is not able to examine other corporate variables such as regulatory complexity, profitability and leverage. Future research may also consider other potential variables such as ethnic diversity as it may affect audit committee membership and audit report lag.


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Ahmed, M. I., & Che-Ahmad, A. (2016). Effects of Board Size, Board Committees Characteristics and Audit Quality on Audit Report Lags. In B. Mohamad (Ed.), Challenge of Ensuring Research Rigor in Soft Sciences, vol 14. European Proceedings of Social and Behavioural Sciences (pp. 810-818). Future Academy. https://doi.org/10.15405/epsbs.2016.08.114