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Do auditors charge a client business risk premium? Evidence from audit fees and derivative hedging in the U.S. oil and gas industry

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Abstract

The literature finds that auditors charge higher fees for riskier clients. One reason for this is that auditors expend greater effort on riskier clients. However, it is unclear whether they also charge an additional client business risk premium. We investigate this issue employing a detailed, hand-collected dataset of hedging derivative usage by U.S. oil and gas exploration and production firms. Even though the auditing of derivative instruments requires greater effort, hedging significantly reduces client business risk. Consistent with the presence of a client business risk premium in audit fees that gets attenuated when clients reduce their risks, we find a negative association between audit fees and the extent of derivative hedging by clients. Further underscoring the role of risk reduction in this relationship, we find the above negative association to be weaker when the risk management efficacy of derivative instruments is comparatively lower. This negative association is also weaker when effort expended in auditing derivatives is likely to be especially high. We contribute to the literature by providing strong evidence for the presence of a client business risk premium in audit fees.

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Notes

  1. See Sect. 2.1 for a discussion of the literature on the relationship between client business risk and audit fees.

  2. We use the term “derivative hedging” throughout this paper to indicate the use of derivative instruments for hedging purposes. In theory, derivatives can also be used for speculation. However, all firms in our sample use derivatives for hedging only. Therefore, even when we simply use the terms “derivatives” and “hedging,” they indicate the use of derivative instruments for hedging purposes only.

  3. Further substantiating the risk reduction role of hedging, in untabulated tests, we also observe a strong negative association between hedging and operating cash flow volatility.

  4. In measuring audit report lag, we follow suggestions of Glover et al. (2021).

  5. There are scores of examples for this. Perhaps the most famous is the case of Enron, which eventually precipitated the collapse of the major audit firm Arthur Andersen.

  6. In a recent paper, using Korean data, Bae et al. (2021) also find that internal control weaknesses are positively associated with not only the number of audit hours employed but also the hourly rate. However, as noted by the authors there are some important institutional differences between the Korean and U.S. settings.

  7. The Bell et al. (2008) sample is approximately evenly split between new and continuing engagements.

  8. Derivatives can also be used for risk-increasing speculation. However, as explained in the subsequent paragraph, firms in our sample do not use derivatives for speculation/trading.

  9. As noted in Sect. 1, for parsimony we label oil and gas exploration and production firms simply as “oil-and-gas firms”. That is, in the subsequent sections, the label “oil-and-gas firms” pertains to oil and gas exploration and production firms only.

  10. For example, according to a 2016 study by Deloitte, 35 U.S. oil-and-gas exploration and production firms filed for bankruptcy between July 2014 and December 2015, following sharp declines in oil prices, and 35% of these firms listed worldwide were facing a high risk of bankruptcy at the end of 2015. (Source:https://www2.deloitte.com/content/dam/Deloitte/ro/Documents/energy-resources/us-er-crude-downturn-2016.pdf). By September 2016, the number of bankruptcies due to this price decline was above 100. Note that this number includes both public and private companies. (Source: https://www.cnbc.com/2016/09/28/oil-bankruptcies-100-down-maybe-100-more-to-go.html).

  11. In contrast, not only do integrated firms explore and produce, they also gather, refine, distribute, and market oil and gas at wholesale and retail levels. Because integrated firms are involved in many layers of the value chain, their profitability is not as closely linked to movements in oil and gas commodity prices. See, Kumar and Rabinovtich (2013, p. 895) for a further discussion of the distinctions between integrated oil and gas firms and oil and gas exploration and production firms.

  12. We verified this during data collection, carefully examining the relevant disclosures made in financial statements.

  13. This need not be the case with some other heavy derivative users, such as banks, which hold derivatives for both hedging and trading purposes.

  14. In our setting, a put option gives the firm the right but not the obligation to sell future oil or natural gas production at the contract price. A collar is created by simultaneously buying a put option and selling a call option. A collar effectively fixes the future price of output at a range between the put price (floor) and the call price (cap).

  15. In contrast, capturing the extent of hedging either in terms of a derivative user/nonuser binary variable or the total notional value of derivatives employed fails to account for the extent of underlying exposure (Guay and Kothari 2003).

  16. exp(-0.310*0.282)-1 = -0.0837.

  17. Our inferences remain unchanged when we use abnormal accruals measures based on the Jones (1991) model and its variants.

References

  • American Institute of Certified Public Accountants (AICPA). (1983). Audit risk and materiality in conducting an audit. Statement on Auditing Standards No. 47. New York, NY.

  • AICPA. (2000). Auditing Derivative Instruments, Hedging Activities, and Investments in Securities. AU Section 332. New York, NY.

  • Altman, E. (1983). Corporate Financial Distress: A Complete Guide to Predicting, Avoiding, and Dealing with Bankruptcy. New York: Wiley.

    Google Scholar 

  • Aobdia, D. (2019). Do practitioner assessments agree with academic proxies for audit quality? Evidence from PCAOB and internal inspections. Journal of Accounting and Economics 67 (1): 144–174.

    Article  Google Scholar 

  • Bae, G., S. Choi, P. Lamoreaux, and J. Lee. (2021). Auditors’fee premiums and low-quality internal controls. Contemporary Accounting Research 38 (1): 586–620.

    Article  Google Scholar 

  • Barton, J. (2001). Does the use of financial derivatives affect earnings management decisions? The Accounting Review 76 (1): 1–26.

    Article  Google Scholar 

  • Bedard, J.C., and K.M. Johnstone. (2004). Earnings manipulation risk, corporate governance risk, and auditors’ planning and pricing decisions. The Accounting Review 79 (2): 277–304.

    Article  Google Scholar 

  • Bell, T.B., W.R. Landsman, and D.A. Shackelford. (2001). Auditors’ perceived business risk and audit fees: Analysis and evidence. Journal of Accounting Research 39 (1): 35–43.

    Article  Google Scholar 

  • Bell, T.B., R. Doogar, and I. Solomon. (2008). Audit labor usage and fees under business risk auditing. Journal of Accounting Research 46 (4): 729–760.

    Article  Google Scholar 

  • Bratten, B., L.M. Gaynor, L. McDaniel, N.R. Montague, G.E. Sierra. (2013). The audit of fair values and other estimates: The effects of underlying environmental, task, and auditor-specific factors. Auditing: A Journal of Practice and Theory 32(Suppl. 1): 7–44.

  • Cannon, N.H., and J.C. Bedard. (2017). Auditing challenging fair value measurements: Evidence from the field. The Accounting Review 92 (4): 81–114.

    Article  Google Scholar 

  • Carey, P., and R. Simnett. (2006). Audit partner tenure and audit quality. The Accounting Review 81 (3): 653–676.

    Article  Google Scholar 

  • DeAngelo, L.E. (1981). Auditor size and audit quality. Journal of Accounting and Economics 3 (3): 183–199.

    Article  Google Scholar 

  • DeFond, M.L., and C.W. Park. (2001). The reversal of abnormal accruals and the market valuation of earnings surprises. The Accounting Review 76 (3): 375–404.

    Article  Google Scholar 

  • DeFond, M., and J. Zhang. (2014). A review of archival auditing research. Journal of Accounting and Economics 58 (2–3): 275–326.

    Article  Google Scholar 

  • DeFond, M.L., C.Y. Lim, and Y. Zang. (2016). Client conservatism and auditor-client contracting. The Accounting Review 91 (1): 69–98.

    Article  Google Scholar 

  • Dye, R.A. (1993). Auditing standards, legal liability, and auditor wealth. Journal of Political Economy 101 (5): 887–914.

    Article  Google Scholar 

  • Financial Accounting Standards Board. (1998). Accounting for Derivative Instruments and Hedging Activities. Statement of Financial Accounting Standard No.133. FASB: Norwalk, CT.

  • Francis, J. R., K. Reichelt, and D. Wang. (2005). The pricing of national and city-specific reputations for industry expertise in the U.S. audit market. The Accounting Review 80(1): 113–136.

  • Fung, S.U.K., F.A. Gul, and J. Krishnan. (2012). City-level auditor industry specialization, economies of scale, and audit pricing. The Accounting Review 87 (4): 1281–1307.

    Article  Google Scholar 

  • Glover, S. M., J. C. Hansen, and T. A. Seidel. (2021). How has the change in the way auditors determine the audit report date changed the meaning of the audit report date? Implications for academic research. Auditing: A Journal of Practice and Theory, forthcoming.

  • Guay, W.R. (1999). The impact of derivatives on firm risk: An empirical examination of new derivative users. Journal of Accounting and Economics 26 (1–3): 319–351.

    Article  Google Scholar 

  • Guay, W., and S.P. Kothari. (2003). How much do firms hedge with derivatives? Journal of Financial Economics 70 (3): 423–461.

    Article  Google Scholar 

  • Gul, F.A. (2006). Auditors’ response to political connections and cronyism in Malaysia. Journal of Accounting Research 44 (5): 931–963.

    Article  Google Scholar 

  • Haushalter, G.D. (2000). Financing policy, basis risk, and corporate hedging: Evidence from oil and gas producers. The Journal of Finance 55 (1): 107–152.

    Article  Google Scholar 

  • Helleiner, E., S. Pagliari, and I. Spagna (eds.). (2018). Governing the world’s biggest market: The politics of derivatives regulation after the 2008 crisis. Oxford University Press.

  • Huss, H. F., and F. A. Jacobs. (1991). Risk containment: Exploring auditor decisions in the engagement process. Auditing: A Journal of Practice & Theory 10(Fall): 16–32.

  • Jin, Y., and P. Jorion. (2006). Firm value and hedging: Evidence from U.S. oil and gas producers. The Journal of Finance 61(2): 893–919.

  • Johnstone, K.M., and J.C. Bedard. (2003). Risk management in client acceptance decisions. The Accounting Review 78 (4): 1003–1025.

    Article  Google Scholar 

  • Johnstone, K. M. (2000). Client-acceptance decisions: Simultaneous effects of client business risk, audit risk, auditor business risk, and risk adaptation. Auditing: A Journal of Practice & Theory 19(1): 1–25.

  • Jones, J.J. (1991). Earnings management during import relief investigations. Journal of Accounting Research. 29 (2): 193–228.

    Article  Google Scholar 

  • Kilic, E., G.J. Lobo, T. Ranasinghe, and K. Sivaramakrishnan. (2013). The impact of SFAS 133 on income smoothing by banks through loan loss provisions. The Accounting Review 88 (1): 233–260.

    Article  Google Scholar 

  • Knechel, W. R., and J. L. Payne. (2001). Additional evidence on audit report lag. Auditing: A Journal of Practice & Theory 20(1): 137–146.

  • Kreutzfeldt, R. W., and W. A. Wallace. (1986). Error characteristics in audit populations: their profile and relationship to environmental factors. Auditing: A Journal of Practice & Theory 6(1): 20–43.

  • Kumar, P., and R. Rabinovitch. (2013). CEO entrenchment and corporate hedging: Evidence from the oil and gas industry. Journal of Financial and Quantitative Analysis 48 (3): 887–917.

    Article  Google Scholar 

  • Lennox, C.S. (1999). Audit quality and auditor size: An evaluation of reputation and deep pockets hypotheses. Journal of Business Finance & Accounting 26 (7–8): 779–805.

    Article  Google Scholar 

  • Lobo, G. J., T. Ranasinghe, and L. Yi. (2020). Hedging, investment efficiency, and the role of the information environment. Journal of Accounting, Auditing & Finance, forthcoming.

  • Lyon, J.D., and M.W. Maher. (2005). The importance of business risk in setting audit fees: Evidence from cases of client misconduct. Journal of Accounting Research 43 (1): 133–151.

    Article  Google Scholar 

  • Minutti-Meza, M. (2013). Does auditor industry specialization improve audit quality? Journal of Accounting Research 51 (4): 779–817.

    Article  Google Scholar 

  • Modigliani, F., and M.H. Miller. (1958). The cost of capital, corporation finance and the theory of investment. The American Economic Review 48 (3): 261–297.

    Google Scholar 

  • O’Keefe, T.B., D.A. Simunic, and M.T. Stein. (1994). The production of audit services: Evidence from a major public accounting firm. Journal of Accounting Research 32 (2): 241–261.

    Article  Google Scholar 

  • Palmrose, Z.V. (1988). An Analysis of Auditor Litigation and Audit Service Quality. The Accounting Review 63 (1): 55–73.

    Google Scholar 

  • Palmrose, Z. V. (1987). Litigation and independent auditors: the role of business failures and management fraud. Auditing: A Journal of Practice & Theory 6(2): 90–103.

  • Pincus, M., and S. Rajgopal. (2002). The interaction between accrual management and hedging: Evidence from oil and gas firms. The Accounting Review 77 (1): 127–160.

    Article  Google Scholar 

  • Pratt, J., and J.D. Stice. (1994). The effects of client characteristics on auditor litigation risk judgments, required audit evidence, and recommended audit fees. The Accounting Review 69 (4): 639–656.

    Google Scholar 

  • Rajgopal, S., and T. Shevlin. (2002). Empirical evidence on the relation between stock option compensation and risk taking. Journal of Accounting and Economics 33 (2): 145–171.

    Article  Google Scholar 

  • Ranasinghe, T., S. Sivaramakrishnan, and L. Yi. (2021). Hedging, hedge accounting, and earnings predictability. Review of Accounting Studies, forthcoming.

  • Schelleman, C., and W. R. Knechel. (2010). Short-term accruals and the pricing and production of audit services. Auditing: A Journal of Practice & Theory 29(1): 221–250.

  • Schipper, K. (1991). Discussion of an analysis of auditor litigation disclosures. Auditing: A Journal of Practice & Theory 10: 72–76.

  • Simunic, D. A., and M. T. Stein. (1996). Impact of litigation risk on audit pricing: A review of the economics and the evidence. Auditing: A Journal of Practice & Theory 15: 119–134.

  • Smith, C.W., and R.M. Stulz. (1985). The determinants of firms’ hedging policies. Journal of Financial and Quantitative Analysis 20 (4): 391–405.

    Article  Google Scholar 

  • St. Pierre, K., and J. A. Anderson. (1984). An analysis of the factors associated with lawsuits against public accountants. The Accounting Review 59 (2): 242–263.

    Google Scholar 

  • Stice, J.D. (1991). Using financial and market information to identify pre-engagement factors associated with lawsuits against auditors. The Accounting Review 66 (3): 516–533.

    Google Scholar 

  • Stout, L.A. (2011). Derivatives and the legal origin of the 2008 credit crisis. Harvard Business Law Review 1: 1–38.

    Google Scholar 

  • Wang, Y., and A. C. Chui. (2015). Product market competition and audit fees. Auditing: A Journal of Practice & Theory 34(4): 139–156.

Download references

Acknowledgements

We are thankful for comments and suggestions from participants at the 2019 AAA Annual Conference and workshop participants at American University, Lehigh University, Nanyang Technological University, National University of Singapore, University of New Hampshire, and University of New Mexico. Ling Zhou also thanks the Rich Research Grant and Cochran Accounting Research Grant from the Anderson School of Management at University of New Mexico for financial support.

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Authors and Affiliations

  1. Kogod School of Business, American University, Washington, D.C, USA

    Tharindra Ranasinghe

  2. College of Business, University of Houston–Clear Lake, Houston, TX, USA

    Lin Yi

  3. Anderson School of Management, University of New Mexico, Albuquerque, NM, USA

    Ling Zhou

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  1. Tharindra Ranasinghe
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Correspondence to Tharindra Ranasinghe.

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Appendices

Appendix 1 An Example of the construction of the variable Derivatives

As an example, consider the case of Cabot Oil and Gas Corporation, an independent oil and natural gas producer, for the year 2005.

From December 31, 2005, annual report (10-K), we find the annual production to be 73,879 million cubic feet (Mmcf) of natural gas and 1,739 thousand barrels (Mbbl) of crude oil. Applying the industry standard conversion rate of 1 barrel of oil being equivalent to 6,000 cubic feet natural gas, this translates into an annual oil equivalent production of 14,052 Mbbl [(73,879/6) + 1,739].

Annual report (10-K) of 2004 and quarterly financial reports (10-Q) for the first three quarters of 2005 reveal the presence of following hedging contracts covering the production for 2005.

Natural gas (swaps and collars):35,713 Mmcf.

Crude oil (collars):365 Mbbl.

Therefore the volume of derivative contracts covering 2005 production in oil equivalent units is 6,317 Mbbl [(35,713/6) + 365].

This implies that the price risk of 44.95 percent of 2005 production is hedged via derivatives (6,317/14,052 = 0.4495). Accordingly, for Cabot, Derivatives takes the value of 0.4495 for the year 2005.

Appendix 2 Variable Definitions

Variable

Definition

LnAuditFee

Natural log of audit fees

Derivatives

The extent of derivative hedging measured as the fraction of annual oil and gas production covered by derivative contracts

LnTA

Natural log of total assets

NBusSeg

Natural log of 1 plus the number of business segments

Foreign

Absolute value of income/loss from foreign operations scaled by the absolute value of operating income/loss

Quick

The ratio of current assets (less inventories) to current liabilities

ROA

Return on assets measured in terms of the ratio of net income to beginning total assets

Lev

Leverage measured in terms of the ratio of year-end total liabilities to total assets

Loss

A binary variable taking the value of 1 if the firm reported a loss in the current year or either one of the previous two years and 0 otherwise

BTM

Ratio of book value of equity to market value of equity

Growth

Annual growth rate in sales

GoingConcern

A binary variable taking the value of 1 if the firm received a going-concern modified opinion and 0 otherwise

BigN

A binary variable taking the value of 1 if the firm employs a Big N auditor and 0 otherwise

Tenure

A binary variable taking the value of 1 if the firm kept the same auditor for three or more years and 0 otherwise

DecYE

A binary variable taking the value of 1 for firms with December fiscal year-ends and 0 otherwise

AuOp

A binary variable taking the value of 1 if the firm received one of the following opinions from auditors (qualified opinion, no opinion, unqualified with additional language, or adverse opinion) and 0 if the firm receives the unqualified opinion from auditors

NumDerivative

The number of different types of derivative contracts the firm uses to hedge energy price risk in a given year

Nonlinear

A binary variable taking the value of 1 if the firm uses nonlinear derivatives to hedge energy price risk in a given year and 0 otherwise

DAccSigned

Signed abnormal working capital accruals computed as per Carey and Simnett (2006)

DAccAbs

Absolute value of abnormal working capital accruals computed as per Carey and Simnett (2006)

Restate

A binary variable taking the value of 1 if a given year’s financial statements are subsequently restated and 0 otherwise

JustMeet

A binary variable taking the value of 1 if a given year’s earnings just meets the consensus analyst forecast or beats it by one cent and 0 otherwise

LnMV

Natural logarithm of market value of equity

ROAL

Lagged return on assets

CFO

Cash flow from operations scaled by average total assets

AbsAccL

Absolute value of lagged total accruals scaled by average total assets

Altman

Altman’s (1983) financial distress score

StdEarn

Standard deviation of earnings before extraordinary items for the past four years

Post_crisis

A binary variable defined to be 1 for year 2010 and afterward and 0 for years before 2008

ReportLag

The natural logarithm of the number of days between fiscal year end-date and the earnings announcement date

Accelerated

A binary variable taking the value of 1 if the firm is regarded as an accelerated filer for SEC filing deadline purposes and 0 otherwise

LargeAccelerated

A binary variable taking the value of 1 if the firm is regarded as a large accelerated filer for SEC filing deadline purposes and 0 otherwise

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Ranasinghe, T., Yi, L. & Zhou, L. Do auditors charge a client business risk premium? Evidence from audit fees and derivative hedging in the U.S. oil and gas industry. Rev Account Stud 28, 1107–1139 (2023). https://doi.org/10.1007/s11142-021-09665-x

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