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Hedge commitments and agency costs of debt: evidence from interest rate protection covenants and accounting conservatism

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Abstract

We provide large sample evidence that credible hedge commitments reduce the agency costs of debt and that accounting conservatism enhances hedge commitments. We examine 2,338 bank loans entered into by 263 mandatory derivative users that are contractually obligated by interest rate protection covenants, 709 voluntary derivative users, and 1,366 non-users. We show that loan contracts are more likely to include interest rate protection covenants when borrowers are less likely to maintain the hedge position once the financing is completed. We find that borrowers who credibly commit to hedge using these covenants significantly reduce their interest rates. While we do not find an average interest savings for voluntary derivative users, we do find a reduction in their loan rates when they practice conservative financial reporting. Our results suggest that accounting conservatism helps borrowers resolve shareholder-creditor conflicts by committing to maintain their hedge positions after completing debt financing.

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Notes

  1. Since virtually all syndicated loans charge variable-rates, banks are more concerned about borrowers’ ability to fulfill interests payment obligations when interest rates increase.

  2. They assume that information asymmetry prevents equity investors from completely adjusting the reporting bias resulting from accounting conservatism. Therefore, when accounting is conservative, low accounting earnings does not necessarily imply low true economic earnings, thereby reducing the benefits of upward earnings management.

  3. An exception is Gezcy et al. (1997), who recognize that lenders may require borrowers to follow certain hedging strategies. They note that at least four of their sample firms have interest rate hedge covenants. However, they do not specifically investigate these mandatory derivative users.

  4. Section 106 of the Bank Holding Company Act Amendments of 1970 prohibits banks from conditioning the availability or terms of loans on the purchase of certain other products and services.

  5. We thank Chris Hunt, Principal at Cardea Partners (http://www.cardeapartners.com/) for providing the institutional knowledge about deal arrangements and information about the hedge accounting treatment for derivative contracts that are entered to fulfill interest rate protection covenant requirements.

  6. The fact that interest rate protection covenants may require hedging for only part of the relevant debt outstanding for a period less than the maturity does not imply that the hedge is ineffective. In a discussion of cash flow hedges, FAS 133 paragraph 28 states: “An entity may designate a derivative instrument as hedging the exposure to variability in expected future cash flows that is attributable to a particular risk. That exposure may be associated with an existing recognized asset or liability (such as all or certain future interest payments on variable-rate debt) or a forecasted transaction (such as a forecasted purchase or sale).” FAS 133 paragraph 98 and 99 example 8 further demonstrates this point. Chris Hunt of Cardea Partners also verified this accounting treatment.

  7. In an interest-decreasing environment, borrowers may want to unwind the pay-fixed receive-floating hedge position and recognize a loss in order to smooth their earnings.

  8. Biddle et al. (2011) document that accounting conservatism reduces the downside risk of operating cash flows through increased cash holdings, reduced customer bargaining power, and increased hedge usage. We differ from Biddle et al. (2011) by separately analyzing mandatory users and voluntary users and by examining how accounting conservatism serves as a commitment mechanism.

  9. We can clearly identify voluntary users when firms explicitly disclose the purpose of the new derivative contracts in their 10-K filings. When firms do not disclose the purpose of their derivative contracts, we examine the change in the notional amount of the variable-to-fixed derivative instruments (swaps, caps, and collars) between the fiscal year of loan origination and the fiscal year prior to loan origination. If the change in the notional amount is positive, we consider the loan to have been (at least partially) swapped to fixed-rate.

  10. An alternative modeling choice is to separately compare non-users with voluntary users, non-users with mandatory users, and voluntary users with mandatory users. However, comparing only two groups at a time ignores the information contained in the third group, thereby reducing the power of the empirical tests. We conduct robustness checks using this alternative design in subsection 5.4, where we discuss any difference in the results.

  11. The principal components analysis shows that only the first eigenvalue is significantly greater than 1. Therefore, one factor captures much of the common variations among the three conservatism measures.

  12. Consistent with previous research, such as Vasvari (2006) and Zhang (2008), we treat these other loan characteristics as exogenous in our models. While we appreciate that all of these characteristics might be endogenously determined, we believe that their choice is not a first order concern in addressing our focal issue of hedge commitment. The large dimensionality of the loan characteristics that we control for makes it undesirable to model all of these characteristics as endogenous choices. For example, if we want to simultaneously model the inclusion of 4 different covenants (sample mean of NCOV is 4) and the security requirement, we need to estimate a system that requires numerical integration over a 5 dimensional normal density to obtain the maximum likelihood. This is a numerically infeasible task. In fact, Freedman (2009) states that “finding maxima in high-dimensional spaces is something of a black art; and the higher the dimensionality, the blacker the art.”

  13. In our sample, 55 % of the deals contain only one facility. Our results are robust to alternative specifications such as using only the facility with the largest borrowing amount or using a weighted average of all facilities in the deal where the weights equal the borrowing amounts. See subsection 5.4 Sensitivity Tests for more discussions.

  14. Faulkender (2005) also finds no association between derivative use and the firm’s natural hedge positions.

  15. Ai and Norton (2003) argue that it can be difficult to interpret an interaction term in non-linear models if the objective is to assess the marginal effect of an independent variable at a point other than the center of the distribution. Since the purpose of the interaction terms in our bivariate Probit model is to examine whether the impact of the natural hedge position on derivative use varies with conservatism, rather than the absolute marginal effect of conservatism, we can rely on the interaction terms to draw inferences (Kolasinski and Siegel 2010).

  16. Zhang (2008) finds a negative association between loan spreads and accounting conservatism only for a sub-sample of loans without performance pricing in her main test. Similarly, Vasvari (2006) documents a negative association between loan spreads and accounting only when managers have below average equity compensation.

  17. Except that when conservatism is measured by Khan and Watts (2009) (i.e., column (3)) the sum of the coefficients on CONSERV and \( {\text{USE}}\widehat{*}{\text{CONSERV}} \) is insignificant (p value = 0.39).

  18. This conclusion applies to conservatism measures CONSERV and CONSERV_SK (columns (2) and (4)). When conservatism is measured as CONSERV_KW (column (3)) and CONSERV_AC (column (5)), the sum of the coefficients on CONSERV, \( {\text{USE}}\widehat{*}{\text{CONSERV}} \), and \( {\text{MAND}}\widehat{*}{\text{CONSERV}} \) is significant at 5 % level.

References

  • Ahmed, A., Billings, B., Morton, R., & Stanford, H. M. (2002). The role of accounting conservatism in mitigating bondholder-shareholder conflicts over dividend policy and in reducing debt costs. The Accounting Review, 77, 867–890.

    Article  Google Scholar 

  • Ai, C., & Norton, E. (2003). Interaction terms in logit and probit models. Economics Letters, 80, 123–129.

    Article  Google Scholar 

  • Almeida, H., Campello, M., Laranjeira, B., & Weisbenner, S. (2010). Corporate debt maturity and the real effects of the panic of August 2007. NBER working paper, University of Illinois. http://www.nber.org/papers/w14990.pdf.

  • Ball, B., Bushman, M. R., & Vasvari, P. V. (2008). The debt-contracting value of accounting information and loan syndicate structure. Journal of Accounting Research, 46(2), 247–287.

    Article  Google Scholar 

  • Barclay, M., & Smith, C. (1995). The maturity structure of corporate debt. Journal of Finance, 50, 609–631.

    Article  Google Scholar 

  • Bartram, S., Brown, G., & Fehle, F. (2009). International evidence on financial derivatives usage. Financial Management, 38, 185–206.

    Article  Google Scholar 

  • Beatty, A., Ramesh, K., & Weber, J. (2002). The importance of accounting changes in debt contracts: The cost of flexibility in covenant calculations. Journal of Accounting and Economics, 33, 205–227.

    Article  Google Scholar 

  • Beatty, A., Weber, J., & Yu, J. (2008). Conservatism and debt. Journal of Accounting and Economics, 45, 154–174.

    Article  Google Scholar 

  • Beaver, W., Landsman, W., & Owens, E. (2012). Asymmetry in earnings timeliness and persistence: A simultaneous equations approach. Review of Accounting Studies. doi:10.1007/s11142-011-9174-3.

  • Bessembinder, H. (1991). Forward contracts and firm value: Investment incentive and contracting effects. Journal of Financial and Quantitative Analysis, 26, 519–532.

    Article  Google Scholar 

  • Biddle, G, Ma, M., & Song, F. (2011). The risk management role of accounting conservatism for operating cash flows. Working paper, The University of Hong Kong. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1695629.

  • Campbell, T., & Kracaw, W. (1990). Corporate risk management and the incentive effects of debt. The Journal of Finance, 45, 1673–1686.

    Article  Google Scholar 

  • Campello, M., Lin, C., Ma, Y., & Zou, H. (2010). The real and financial implications of corporate hedging. Working paper. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1544048.

  • Carey, M., Prowse, S., Rea, J., & Udell, G. (1993). The economics of the private placement market. Board of Governors of the Federal Reserve System, Staff Studies 166.

  • Chen, Q., Hemmer, T., & Zhang, Y. (2007). On the relation between conservatism in accounting standards and incentives for earnings management. Journal of Accounting Research, 45, 541–565.

    Article  Google Scholar 

  • Chidambaran, N. K., Fernando, C., & Spindt, P. (2001). Credit enhancement through financial engineering: Freeport McMorans gold-denominated depositary shares. Journal of Financial Economics, 60, 487–528.

    Article  Google Scholar 

  • Denis, D., & Mihov, V. (2003). The choice among bank debt, non-bank private debt, and public debt: Evidence from new corporate borrowings. Journal of Financial Economics, 70, 3–28.

    Article  Google Scholar 

  • Doherty, N. (2000). Integrated risk management: Techniques and strategies for managing corporate risk. New York: McGraw-Hill.

    Google Scholar 

  • Faulkender, M. (2005). Hedging or market timing? Selecting the interest rate exposure of corporate debt. Journal of Finance, 60, 931–962.

    Article  Google Scholar 

  • Faulkender, M., & Petersen, M. (2006). Does the source of capital affect capital structure? Review of Financial Studies, 19(1), 45–79.

    Article  Google Scholar 

  • Freedman, D. (2009). Statistical models: Theory and practice, revised edition. Cambridge: Cambridge University Press.

  • Froot, K., Scharfstein, D., & Stein, J. (1993). Risk management: Coordinating investment and financing policies. Journal of Finance, 48, 1629–1658.

    Google Scholar 

  • Geczy, C., Minton, B., & Schrand, C. (2007). Taking a view: Corporate speculation, governance, and compensation. Journal of Finance, 62, 2405–2443.

    Article  Google Scholar 

  • Gezcy, C., Minton, B., & Schrand, C. (1997). Why firms use currency derivatives. Journal of Finance, 52, 1323–1354.

    Google Scholar 

  • Givoly, D., & Hayn, C. (2000). The changing time-series properties of earnings, cash flows and accruals: Has financial reporting become more conservative. Journal of Accounting and Economics, 29, 287–320.

    Article  Google Scholar 

  • Graham, J. R., & Mills, L. F. (2007). Using tax return data to simulate corporate marginal tax rates. Working Paper, Duke University. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=959245.

  • Graham, J., & Rogers, D. (2002). Do firms hedge in response to tax incentives? Journal of Finance, 57, 815–839.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Jensen, M. C., & Meckling, W. (1976). Theory of the firm: Managerial behavior, agency costs, and ownership structure. Journal of Financial Economics, 3, 305–360.

    Article  Google Scholar 

  • Kanageratnam, K., Mathieu, R., & Shehata, M. (2009). Usefulness of comprehensive income reporting in Canada. Journal of Accounting and Public Policy, 28, 349–365.

    Article  Google Scholar 

  • Khan, M., & Watts, R. (2009). Estimation and empirical properties of a firm-year measure of accounting conservatism. Journal of Accounting and Economics, 48, 132–150.

    Article  Google Scholar 

  • Kolasinski, A., & Siegel, A. (2010). On The economic meaning of interaction term coefficients in non-linear binary response regression models. Working paper, University of Washington. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1668750.

  • Larcker, D., & Rusticus, T. (2010). On the use of instrumental variables in accounting research. Journal of Accounting and Economics, 49, 186–205.

    Article  Google Scholar 

  • Leland, H. E. (1998). Agency costs, risk management, and capital structure. Journal of Finance, 53, 1213–1243.

    Article  Google Scholar 

  • Loktionov, Y. (2009). Does accounting quality mitigate risk shifting? Dissertation, Massachusetts Institute of Technology. http://dspace.mit.edu/handle/1721.1/58377.

  • Mayers, D., & Smith, C. (1982). On the corporate demand for insurance. Journal of Business, 55, 281–299.

    Article  Google Scholar 

  • Mian, S. (1996). Evidence on corporate hedging policy. Journal of Financial and Quantitative Analysis, 31, 419–439.

    Article  Google Scholar 

  • Mohrman, M. B. (1996). The use of fixed GAAP provisions in debt contracts. Accounting Horizons, 10(3), 78–91.

    Google Scholar 

  • Nance, D., Smith, C., & Smithson, C. (1993). On the determinants of corporate hedging. Journal of Finance, 48, 267–284.

    Article  Google Scholar 

  • Nikolaev, V. (2010). Debt covenants and accounting conservatism. Journal of Accounting Research, 48, 137–176.

    Article  Google Scholar 

  • Page, S., Russ, C., & Remington, R. (2011). Why this “anti-bond” asset class may be more compelling than ever. Eaton Vance Investment Managers, White Paper.

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

    Article  Google Scholar 

  • Sufi, A. (2007). Information asymmetry and financing arrangements: Evidence from syndicated loans. Journal of Finance, 62, 629–668.

    Article  Google Scholar 

  • Taylor, A., & Sansone, A. (2006). The handbook of loan syndications and trading. New York: McGraw-Hill.

    Google Scholar 

  • Thatcher, J. (1985). The choice of call provision terms: Evidence of the existence of agency costs of debt. Journal of Finance, 40, 549–561.

    Article  Google Scholar 

  • Vasvari, F. (2006). Managerial incentive structures, conservatism and the pricing of syndicated loans. Working Paper, London Business School. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1128249.

  • Vickery, J. (2008). How and why do small firms manage interest rate risk? Evidence from commercial loans. Journal of Financial Economics, 87, 446–470.

    Article  Google Scholar 

  • Watts, R. (2003a). Conservatism in accounting part I: Explanations and implications. Accounting Horizons, 17(3), 207–221.

    Article  Google Scholar 

  • Watts, R. (2003b). Conservatism in accounting part II: Evidence and research opportunities. Accounting Horizons, 17(4), 287–301.

    Article  Google Scholar 

  • Wooldridge, J. M. (2010). Econometric analysis of cross-section and panel data (2nd ed.). Cambridge: The MIT Press.

    Google Scholar 

  • Zhang, J. (2008). The contracting benefits of accounting conservatism to lenders and borrowers. Journal of Accounting and Economics, 45, 27–54.

    Article  Google Scholar 

Download references

Acknowledgments

Beatty thanks Deloitte & Touche, for financial support. We are grateful for helpful comments and suggestions from an anonymous reviewer, Gauri Bhat, Chitru Fernando, Rich Frankel, Scott Richardson (the editor), Florin Vasvari (the discussant), the workshop participants at Boston College, The Ohio State University, the University of California at Irvine, McGill University, Massachusetts Institute of Technology, Southern Methodist University, University of Illinois at Chicago, Washington University at St. Louis, and the participants at the 2009 Midwest Accounting Research Conference, the 2009 American Accounting Association annual conference, and the 2011 Review of Accounting Studies annual conference.

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Authors and Affiliations

  1. Fisher College of Business, The Ohio State University, 442 Fisher Hall, 2100 Neil Avenue, Columbus, OH, 43210, USA

    Anne Beatty

  2. Sloan School of Management, Massachusetts Institute of Technology, 100 Main Street, E62-669, Cambridge, MA, 02142, USA

    Reining Petacchi

  3. Fisher College of Business, The Ohio State University, 436 Fisher Hall, 2100 Neil Avenue, Columbus, OH, 43210, USA

    Haiwen Zhang

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  1. Anne Beatty
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Correspondence to Haiwen Zhang.

Appendix: Variable definitions

Appendix: Variable definitions

AISD:

Loan spreads over LIBOR calculated for each deal. If one deal consists of multiple facilities, AISD is measured as the average spreads across all the facilities

COMPRATE:

S&P rating ranging from 1 for AAA to 22 for D for firms with ratings. Set to missing value for firms without ratings

CONSERV_KW:

Decile ranking of the accounting conservatism constructed for each firm-year based on Khan and Watts (2009)

CONSERV_AC:

Decile ranking of the accounting conservatism measured as the average non-operating accruals scaled by total assets over the 3-year period before the loan origination

CONSERV_SK:

Decile ranking of the accounting conservatism measured as the difference between the skewness of operating cash flows scaled by total assets and the skewness of income before extraordinary items scaled by total assets. The skewness of earnings and cash flows are calculated for the firm-year before the loan origination using information from the previous 12 quarters with minimum 5 quarters data

CONSERV:

Decile ranking of the principal component of the three accounting conservatism measures based on non-operating accruals, difference in the skewness of cash flows and earnings, and Khan and Watts (2009)

LEV:

Book leverage measured as the sum of the long-term debt and debt in current liabilities divided by total assets

LOANSIZE:

Total borrowing amount scaled by lagged assets

MAND:

Indicator variable that equals 1 if a bank loan includes an interest rate protection covenant (i.e., mandatory users), 0 for non-users and for voluntary users

\( {\text{M}}\widehat{\text{A}}{\text{ND}} \) :

Predicted joint probability of USE = 1 and MAND = 1 from the bivariate Probit model (Eqs. (1) and (2)), where the explanatory variables include the three instrumental variables and all other exogenous variables

\( {\text{MAND}}\widehat{*}{\text{CONSERV}} \) :

Fitted value from regression Eq. (6)

MATURE:

Natural log of number of months between the loan start and end dates

MTR_Resi:

We first calculate the before-financing simulated marginal tax rate (MTR) using the coefficients estimated in Graham and Mills (2007) for predicting pre-financing marginal tax rate. MTR_Resi is the residual calculated from regressing MTR on multiple measures of profitability (i.e., operating loss carry forward, pre-tax loss, and operating income before interest expense, tax, depreciation, and amortization scaled by lagged total assets). We use MTR_Resi to capture hedge incentives arising from marginal tax rate that is unrelated to AISD

NATURAL:

Firms’ natural hedge position measured as the sum of the coefficients on current and one period lagged 12-month treasury rates from a regression of sales scaled by total assets on these variables, as well as a constant, time trend, and log time trend. The regression is estimated at 2-digit SIC industry level. This measure is similar to the natural hedge position measured in Vickery (2008)

NATURAL_P:

Equals NATURAL if NATURAL > 0 and set to 0 otherwise

NATURAL_N:

Equals NATURAL if NATURAL < 0 and set to 0 otherwise

NCOV:

Number of financial covenants

NLENDER:

Number of lenders involved in the syndicated loans

PERFORM:

Indicator variable that equals 1 if the loan includes performance pricing, 0 otherwise

PM:

Gross profits scaled by sales revenue

PROP:

Proportion of existing debt maturing after 1 year

RATE:

Indicator variable that equals 1 if a borrower has S&P credit ratings prior to loan origination, 0 otherwise

RD:

Research and development expense scaled by sales. Set to 0 when research and development expense data is missing

SECOND:

Indicator variable that equals 1 if a “Term Loan” is followed by letter A-H, 0 otherwise

SECURE:

Indicator variable that equals 1 if the loan is secured, 0 otherwise

SIZE:

Natural log of sales revenue

SPRATE:

S&P rating ranging from 1 for AAA to 22 for D for firms with ratings and equal to 0 for firms without ratings

TAKEOVER:

Indicator variable that equals 1 if the loan is used for takeover purpose, 0 otherwise

TERM:

Indicator variable that equals 1 if any facility is a term loan, 0 otherwise

USE:

Indicator variable that equals 1 if a borrower uses derivative contracts to fix the borrowing rate (both voluntary users and mandatory users), 0 for non-users

\( {\text{U}}\widehat{\text{S}}{\text{E}} \) :

Predicted probability of USE = 1 from the bivariate Probit model (Eqs. (1) and (2)), where the explanatory variables include the three instrumental variables and all other exogenous variables

\( {\text{USE}}\widehat{*}{\text{CONSERV}} \) :

Fitted value from regression Eq. (5)

YIELD:

Difference in yields (basis points) between a 10-year Treasury bond and a 1-year Treasury bond measured in the month of loan initiation

All accounting variables are measured at the end of the fiscal year prior to loan origination, except for MTR_Resi. Before-financing marginal tax rate (MTR_Resi) is measured at the end of the fiscal year of the loan origination.

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Beatty, A., Petacchi, R. & Zhang, H. Hedge commitments and agency costs of debt: evidence from interest rate protection covenants and accounting conservatism. Rev Account Stud 17, 700–738 (2012). https://doi.org/10.1007/s11142-012-9189-4

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