Maa753 Professional Research And Analysis Assessment Answers

1. Development of hypotheses. You have to provide logical/ theoretical reasoning to develop your hypothesis. The hypothesis has to be developed along the lines of examining the relationship between

CEO age and audit pricing behaviour/ audit fees.

1. Research methods/ design, including
2. sources of information to be used to gather relevant data
3. sampling techniques
4. definition of variables (dependent, independent and some relevant control variables) to be used in the models models to be used to examine the hypothesis/ hypotheses

Answer:

Development of Hypothesis

Based on the standpoint of individual characteristics of CEO, this current paper indicates towards the demographic research technique to assess whether CEO age exerts impact on overall disbursement of premiums audit fee to different auditors who express “high quality” indications.

However, it can be hereby observed from the prior literature on determinants of audit fees that audit fees determinants can be enumerated from client of audit as well as auditor level. Based on the standpoint of the association between the corporation and fees for audit, it can be observed that corporations that deliver “superior quality” indications to market have the tendency to obtain premium level audit fees. For instance, “Big 4” can be observed to obtain higher fees for audit in comparison to other corporations (Leventis et al.  2018). Fundamentally, it is worth observing that these kinds of studies are founded on an implied supposition that assessors at the corporation deliver the same quality of audit and accept the equal level of audit fees. In essence, this is opposing to the inferences drawn by the subsisting literature of individual characteristics of auditors, that divulges the fact that there are variances among assessors and their individual features work directly on different cognitive styles along with behaviours of decision-making and in that way exerting impact on quality of audit (Huang et al. 2014).

The current study essentially intends to analyse the way individual features of CEOs (particularly age is taken into consideration in this regard) affect the decision making regarding auditing of firms. Sundgren and Svanström (2014) suggest that age is a wild card of leadership since head-hunters as well as corporate boards think over trade-offs namely energy level vs. wisdom. It can be observed that an experienced and aged CEO might perhaps help a firm to avert repeating mistakes; however, on the other hand, the flexibility of young and youthful CEOs might perhaps be significant in a situation of speedy adjustments (Sundgren and Svanström 2014). “As anticipated, it was observed from an interaction between particularly situation and age, participants of a study approved older leaders over the younger ones for preserving stability and young leaders over older ones for assisting in bringing about change as per the journal “The Leadership Quarterly”. As per prior reports, it can be said that there are significant differences in attitudes between an old and young CEO. The old ones have greater experience and tend to be risk averse and have the inclination to carry out appropriate audit that can alleviate risks of business. For that reason, they have a tendency to auditors with specialized know-how, higher efficiency and better reputation. (Chen et al.  2015). Managers are essentially negotiators of fees of audit and have authority to make judgement regarding selection of services of audit. The subsisting literature reveals that assessors charge higher amount of fees when they observe an enhancement in audit as well as risk of business in a particular audit engagement (Huang et al.  2014). Therefore, there arises a debate between energy, knowledge, maturity, risk aversion, horizon issues of CEOs that affect the selection of auditors of firms and pricing of audit.

Provided that CEOs of firms do not characteristically decide corporate strategies alone but makes judgements as a member of the entire team, therefore, the risk preference of diverse other senior officials can also contribute towards overall profile of risks of firms. In case, if age of an executive exerts impact on preferences of risk, then executives belonging to similar group of age as the firm’s CEO must reinforce CEOs’ risk-taking behavior. Hrazdil et al. (2018) examined whether preferences of risk affect risk-taking behavior of particularly CEOs. However, it could be observed that firm risk can be recorded to be the lowest at the time when both the CEO and influential executives are necessarily older. Na and Hong (2017) suggest that the financial background of firms’ CEOs also alleviates the risk of firm’s poor performance and existent risk of failures of firms. Also, the background of different CEOs, particularly their risk inclinations are also said to enhance overall quality of financial reporting that lessens over possibility of material misstatements, thereby decreasing the risks associated to the engagement of audit. Essentially, decline in the business along with audit risks are said to translate into low audit fees.

Thus, audit fees determinants cannot be enumerated only at the level of firm, but also need to be considered at the individual point as well (Lin et al.  2014). Thus, this current paper intends to study specific determinants of fees for audit or audit pricing at individual level based on specific characteristic of CEOs (that is to say, the age of CEOs).

1) Age

Age normally exerts impact on the propensity of risks. There are certain scholars who are of the view that elder individuals are likely to be more mature and don’t prefer risks. Choi et al.  (2018) state that tendency of risk declines linearly as per age, and the elder individuals have greater sensitivity to particularly economic risk. Thus, during the period of real audit procedure, elder assessors are necessarily more vigilant than younger assessors. Similarly, elder CEOs also tend to prefer lesser risks and intend to ensure higher quality of audit of their firms that might involve higher fees. Thus, we make the hypothesis:

H1: Age of CEO has a substantial positive correlation with audit pricing or fees of audit

Research Methodology

Data Collection

The variable that is of interest in this current paper is the age of CEOs of firms.  For that purpose, age of CEOs of top 100 selected firms listed in the Australian Stock Exchange can be acquired directly from published database (annual report) and different missing values can be found out online over a period of 5 years. Again, the natural logarithms of the age of CEOS can be utilized in different multivariate regressions (Leventis et al.  2018). Thereafter, prices of audit (that is complete data on fees of audit in Australia) of the selected firms can be gathered from the official reports disclosing their audit fees (that is obligatory as per regulation). This data on audit fee can be obtained from published reports of companies (Hrazdil et al. 2018). Again, total risk of the firm can be computed by means of the variable that is the stock volatility investigated over a 1 year period by gathering closing prices (on a monthly basis). Monthly closing prices for the year 2017 can be collected for 100 firms and annualised rate of standard deviation can be utilized as a specific measure of overall volatility.

We divide the sample into different parts. The CEO ages above the age of 50 years can be considered to be aged and indicated as “1”and CEO ages below the age of 50 years can be stated to be not aged and indicated as “2”. For this CEO background information (particularly age)of the 100 selected companies can be gathered. However, in order to assess the effect of age of CEOs on fees of audit, correlation and regression analysis can be carried out among the variables under consideration (Age of CEOs in 100 firms and audit fees in the firms).

Sampling Technique

Among the Top 200, ASX listed firms, 100 ASX listed firms will be selected as the sample for the study. Probability sampling refers to a sampling technique where different subjects of the targeted population acquire an opportunity to get selected. Based on the selected firms, the data of age of CEOs and the fees for audit can be calculated (Sundgren and Svanström  2014). Thereafter, after collection of requisite data, summary statistics of the acquired data are presented for CEO age and audit pricing that are expressed in Australian dollars. The data obtained will be analysed using Microsoft Excel and SPSS.  

Definition of variables

The learner intends to examine the nature of association between age of CEOs and fees of audit for the firms. The Age of CEOs is considered as the independent variable and the fees of audit as the dependent variable. Correlation matrix can be enumerated for the identified variables and regression analysis can be undertaken from analysis using SPSS (Ittonen et al. 2015). The hypothesis developed based on review of prior literature leads to a prediction that age of CEO is negatively associated to volatility of stocks as older CEOs tend to be risk averse.  Therefore, risk averse CEOs have the tendency to superior quality audit for reduction of business risks and have the inclination to spend higher amount as audit fees (Duellman et al. 2015). As a result, there need to be positive association between age of CEO and audit fees.

In this case, it can be said that natural logarithm of audit fees is the dependent variable and natural logarithm of age of CEOs is the independent variable.  However, the control variables are also present in this case that refers to the variables that are not of much interest but are associated to the dependent variables (Kalelkar and Khan 2016). For the purpose of the present study, the control variables are volatility of firm’s stocks (indicating risks parameter), financial leverage (risk dimensions) and operating leverage.

Models to be utilized to examine the hypothesis/ hypotheses

The learner intends to analyse results from regression associating to age of CEO to audit pricing for 100 firms listed under ASX for last 5 years (2013 to 2017). Different descriptive statistics will be used for elucidating CEO age categories (above the age of 50 years and below the age of 50 years. The mean age difference between oldest CEOs and the youngest CEOs utilizing a t-test can be examined and placed next to the value of mean of the oldest CEO values. Assuming a specific significance level of 0.05, the learner intends to examine whether the significant values are higher than 0.05 (Huang et al. 2014). However, based on this result, the learner will be able to state whether the oldest and the youngest CEOs age groups differ significantly among this tested variables (using t test) (Chen et al. 2015). The model for the study includes Log Audit Pricing as dependent variable. Different control variables include volatility of firm’s stocks, financial leverage (debt/equity) and operating leverage. The model of the study examining the association between age and audit pricing shall present the coefficient results from the study of regression (that is to say, relation between age of CEOs and audit pricing).

Conclusion

The study intends to examine the nature of association between the age of CEOs and audit pricing. The findings of the obtained result shall be explained and remarks will be presented regarding importance of the same. Based on theoretical premises it can be seen that the old CEOs have considerably higher experience, know-how and level of maturity and are likely to be risk averse. This shows the way towards their inclination to undertake superior quality of work of audit by specialised assessors even with higher fees so as to ensure that the audit can alleviate business risk encountered. It is for this reason; they have a tendency to hire auditors with specialized skills, superior efficiency and reputation to carry out superior quality audit and even without negotiation of audit fees.  Thus, this study devises a hypothesis that highlights examination of effect of age of CEO on pricing of audit. It is seen that audit opinions that are signed in the nation Australia and divulging audit fees in AUD-Australian dollars have enhanced from AUD183m to roughly AUD518m during the period 2000 to 2011. Therefore, this study intends to study the age of CEOs in the ASX listed firms from composition of the board (mentioned in company reports) and their respective fees (mandatory disclosure). This way the learner intends to examine the positive association between age and pricing of audit.

References

Chen, Y., Gul, F.A., Veeraraghavan, M. and Zolotoy, L., 2015. Executive equity risk-taking incentives and audit pricing. The Accounting Review, 90(6), pp.2205-2234.

Choi, Y.S., Hyeon, J., Jung, T. and Lee, W.J., 2018. Audit pricing of shared leadership. Emerging Markets Finance and Trade, 54(2), pp.336-358.

Duellman, S., Hurwitz, H. and Sun, Y., 2015. Managerial overconfidence and audit fees. Journal of Contemporary Accounting & Economics, 11(2), pp.148-165.

Hrazdil, K., Novak, J., Rogo, R., Wiedman, C.I. and Zhang, R., 2018. Measuring CEO Personality Using Machine-Learning Algorithms: A Study of CEO Risk Tolerance and Audit Fees.

Huang, H.W., Parker, R.J., Yan, Y.C.A. and Lin, Y.H., 2014. CEO turnover and audit pricing. Accounting Horizons, 28(2), pp.297-312.

Ittonen, K., Johnstone, K. and Myllymäki, E.R., 2015. Audit partner public-client specialisation and client abnormal accruals. European Accounting Review, 24(3), pp.607-633.

Kalelkar, R. and Khan, S., 2016. CEO financial background and audit pricing. Accounting Horizons, 30(3), pp.325-339.

Leventis, S., Dedoulis, E. and Abdelsalam, O., 2018. The impact of religiosity on audit pricing. Journal of Business Ethics, 148(1), pp.53-78.

Lin, Y.C., Wang, Y.C., Chiou, J.R. and Huang, H.W., 2014. CEO characteristics and internal control quality. Corporate Governance: An International Review, 22(1), pp.24-42.

Na, K. and Hong, J., 2017. CEO Gender And Earnings Management. Journal of Applied Business Research, 33(2), p.297.

Sundgren, S. and Svanström, T., 2014. Auditor?in?charge characteristics and going?concern reporting. Contemporary Accounting Research, 31(2), pp.531-550.