The interest rate swap: Theory and evidence

Journal of Corporate Finance 5 Ž1999. 55–78

The interest rate swap: Theory and evidence Kent T. Saunders

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Le Moyne College, 1419 Salt Springs Road, Syracuse, NY 13214-1399, USA Received 1 March 1996; accepted 1 March 1998

Abstract Nonfinancial firms that use interest rate swaps are compared with nonusers for the years 1991, 1993, and 1995. Swap use grew from 6% of all firms in 1991 to 8% in 1995. Nonfinancial firms use fixed rate payer swaps more often than floating rate payer swaps. Firms that use swaps are significantly larger and have a higher debt to equity ratio relative to nonusers. Fixed rate payers receive a ratings’ upgrade significantly more often than floating rate payers and experience a significantly higher percentage increase in net sales in the year of swap initiation relative to floating rate payers and the industry average. Floating rate payers have a significantly higher S & P bond rating relative to the industry average. The test results lend support to the information asymmetry theory of swap usage wTitman, S., 1992. Interest rate swaps and corporate financing choices, Journal of Finance 47, pp. 1503–1516x and lend some support to the asset substitution portion of the agency cost theory of swap usage wWall, L.D., 1989. Interest rate swaps in an agency theoretic model with uncertain interest rates. Journal of Banking and Finance 13, pp. 261–270x. q 1999 Elsevier Science B.V. All rights reserved. JEL classification: G30 Keywords: Interest rate swap; Interest rate exchange agreement; Hedging; Financial derivative

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Tel.: Žq1. 315 445-4488; fax: Žq1. 315 445-4540; e-mail: [email protected]

0929-1199r99r$ - see front matter q 1999 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 9 - 1 1 9 9 Ž 9 8 . 0 0 0 1 7 - 0

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K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

1. Introduction The swaps market began in the early 1980s, evolving from parallel loan agreements that were popular in the 1970s. 1 The swaps market has grown dramatically. The total notional amount of interest rate and currency swaps Želiminating double counting. has grown from essentially zero in 1980 to US$9.1 trillion at year end 1993. 2 Although many derivative instruments are sometimes classified under the umbrella term ‘swaps’, the focus of this paper is on interest rate swaps. Several theories have been proposed for why nonfinancial firms use swaps. The purpose of this paper is to empirically test theories aimed at explaining interest rate swap use for nonfinancial firms. Section 2 outlines existing theories and proposes a few new theories. Section 3 examines previous empirical work. Section 4 describes the data set. In Section 5, tests of the theories are performed to determine which theories seem to fit real world data.

2. Theories explaining the existence of interest rate swaps 2.1. Information asymmetry Titman Ž1992. develops an asymmetric information model where one company believes that it will have lower borrowing costs in the future and thus has incentives to borrow short and then swap floating for fixed rates in order to reduce interest rate expense. 3 Consider two firms ŽA and B. that are identical except that firm A believes that it will have lower borrowing costs in the future. However, firm A is unable to convince lenders that it is a better credit risk than firm B. Since lenders cannot distinguish between firms, they will offer both short-term and long-term loans to both firms at the same rate. In this situation, firm A would not wish to borrow long-term since it believes that its borrowing costs will fall in the future. Firm B is indifferent between borrowing long or short. Unless the transactions costs of rolling over short-term debt are excessive, firm B would prefer to borrow long. 1 In a parallel loan agreement, both the principal and the coupon payments in one currency are exchanged for the principal and coupon payments in another currency. For example, a US firm may borrow US$1 million in the US and then exchange this debt obligation with a French firm that borrows an equivalent amount of French Francs. The two firms would typically exchange the principal at the start of the agreement based on the current exchange rate. For the duration of the agreement, they would make the coupon payments in the other currency. Then reexchange the principal payments at the end of the agreement. For further discussion of parallel loan agreements and how they relate to currency and interest rate swaps, see Abken, 1991. 2 ‘True size of swap market approximates US$9 trillion.’ Swaps Monitor, Vol. 7, No. 11, March 14, 1994, p. 6. 3 See also Arak et al. Ž1988..

K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

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Suppose both firms initially can borrow at the same long and short rate. If firm A borrows short-term and firm B borrows long-term and A and B swap interest rate payments, then if firm A’s borrowing costs do fall in the future, firm A in effect locks in a lower long-term borrowing rate without exposure to interest rate risk. Firm B is no worse off than if it had chosen to borrow by rolling over short-term debt. 2.2. Agency cost Wall Ž1989. combines the notion of underinvestment ŽMyers, 1977. with the problem of asset substitution ŽJensen and Meckling, 1976. to develop an agency cost theory for the use of swaps. 4 Although, the agency costs of long-term debt can be reduced through the issuance of short-term debt and callable bonds, Wall asserts swaps may be a more efficient alternative in that they allow the firm to reduce the agency costs of long-term debt without exposure to changes in interest rates. Wall proposes that a firm that wishes to lock in a long-term rate but is unwilling to pay the premium required to compensate for the problems of underinvestment and asset substitution when issuing long-term debt can issue short-term debt and enter a swap as a fixed rate payer. Because the firm is monitored each time it enters the short-term debt market, the agency costs of long-term debt are reduced. By entering a swap as a fixed rate payer, the firm is able to lock in a long-term rate of interest. 2.3. ComparatiÕe adÕantage Bicksler and Chen Ž1986. explain swap use with a theory based on comparative advantage in borrowing between companies. When companies go to financial markets to borrow, higher rated companies can borrow for both short Žfloating. and long Žfixed. maturities at a lower rate of interest than a lower rated company. The lower rated company must pay a premium Žquality spread. due to the increased probability of default. Bicksler and Chen contend that higher rated companies should borrow long-term and buy a floating rate payer interest rate swap. Lower rated companies should borrow short-term and buy a fixed rate payer interest rate swap. The combination of borrowing and swap usage allows both

4 Asset substitution is the incentive for companies to shift to high risk projects when long-term noncallable bonds are issued. Underinvestment is the incentive to bypass positive net present value projects when the benefit of the investment accrues to bondholders.

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58

companies to arbitrage the quality spread differential and lower the borrowing costs for both firms. 5 Two problems arise when using this explanation for swaps. First, if this is the driving force behind swaps, then arbitrage should reduce the quality spread differential to the point where no profitable swaps exist and we should see a decline in the amount of swap transactions. This has not been the case. Secondly, there has to be a reason for the quality spread between companies. Under the comparative advantage theory, the higher rated company is effectively bearing the lower rated company’s default risk. Turnbull Ž1987. shows that in the absence of externalities, swaps are a zero sum game when credit risks are taken into account. That is, when interest rates change, the gains to one party are offset by losses to the other party. 2.4. Expected future downsizing Smith et al. Ž1986, 1988. point out that over time the optimal amount of debt for a firm will change. For example, if a company issues long-term fixed rate debt in order to avoid interest rate risk, then in periods in which the firm wishes to reduce the amount of the debt outstanding it may have to repurchase the outstanding debt at a price above fair market value, due to debt covenants. However, if a firm issues short-term floating rate debt and enters a swap as a fixed rate payer, the firm still avoids interest rate risk and can reduce the amount of debt outstanding by simply not issuing more short-term debt and terminating its swap. The cost of terminating a swap is most likely less than the premium required to refund long-term debt. Typically, a swap can be terminated by paying Žor receiving. the current fair market value of the swap. Also, an offsetting or mirror swap as a floating rate payer can effectively unwind or terminate outstanding fixed rate payer swaps. Therefore, firms that wish to avoid interest rate risk and expect a decrease in the optimal amount of debt can benefit from swap use. These firms will use swaps as a fixed rate payer. This is termed the downsizing hypothesis of Wall and Pringle Ž1989.. The firm that expects downsizing in the future, will not want to be locked into large long-term debt obligations that may be costly to repurchase. By issuing short-term floating rate debt and simultaneously entering a swap as a fixed rate payer, the firm will in effect lock in a fixed rate of interest and have more control of the size of its debt obligations over time.

5

The quality spread is the additional interest a lower rated borrower must pay for the use of funds. The quality spread differential is the difference between the quality spreads at different maturities. For instance, if the quality spread at 6 months is 0.5% and the quality spread at 5 years is 1.5%, the quality spread differential in this case is 1% Ž1.5–0.5%..

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2.5. Project completion As a company grows, it must seek funding to expand its business through the construction of new plants and equipment. There is evidence that using debt, rather than equity, improves managerial decision making ŽMaloney et al., 1993.. As developed by Myers Ž1977., a firm’s shareholders would prefer to finance growth through the issuance of short-term or callable debt. Once a new project is completed, the company wishes to operate its plants efficiently at the optimal capital to labor ratio in order to maximize profits. However, when constructing a new plant, the optimal capital to labor ratio will vary as the price of the goods used in construction change over the course of building a new plant and as interest rates change. For example, if interest rates increase, it may be optimal to decrease the size of the plant. If interest rates decrease, the optimal plant size may be larger. In any case, during project development, interest rates are variable that will affect decision making. A company would like to borrow at short-term floating rates of interest as the plant is being constructed because the optimal sizerscale of the plant will vary during the construction process as input prices of building materials and interest rates change. In fact, most companies finance new plant construction from a variable rate line of credit. Although, once the plant is finished, the capital to labor ratio is fixed and the company would like to lock in a long-term interest rate. Revenues and profits generated from the plant will tend to vary with interest rates; however, there is nothing the company can do to control interest rate fluctuations. Interest rates are no longer a decision variable to which the company can adapt. Once the plant is finished, the company cannot change the scale of the plant. Thus, when the new plant is complete, it would be optimal to divorce interest rate fluctuations from interest expense. A swap where the company receives the floating rate and pays the fixed rate could satisfy this need without the issuance of long-term fixed rate debt. Hence, we would expect to see an initiation of a swap as a fixed rate payer simultaneous with project completion when the new project is financed with short-term floating rate debt.

3. Previous empirical work on interest rate swaps 3.1. Wall and Pringle Wall and Pringle Ž1989. investigate the comparative advantage, agency cost, information asymmetry, and downsizing theories. They find some support for each of the theories listed above; yet, do not find overwhelming support for any one theory. The main concern with the results of this paper is that the data set is taken from 1986 financial reports when there were no disclosure requirements in place for firms to report swap usage. Therefore, there could be sample selection bias in

K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

60

that only firms that had favorable swap transactions reported usage. Also, the data set is based on outstanding swaps in 1986 rather then the year of swap initiation. 3.2. Samant Samant Ž1992. tests the agency cost and information asymmetry explanations of swap use. Samant finds support for the information asymmetry theory. Samant’s data set is based on swaps outstanding in 1990 rather than the year of swap initiation. However, tests of the agency and information asymmetry theories require data on differences in balance sheet variables between swap users and nonusers at the year of initiation rather than simply a year in which interest rate swaps were used. The work of Wall and Pringle, and Samant is hampered on two counts. First, disclosure of swap usage was not required prior to June 15, 1990. Second, the year of swap initiation was not used as a point of reference in comparing changes in relevant variables. This study will take account of both of these problems. This study will use data collected after June 15, 1990 where disclosure is required and the year of swap initiation will be used as a point of reference in comparing changes in relevant variables.

4. Data 4.1. Data sets SFAS no. 105 published by the Financial Accounting Standards Board requires disclosure of interest rate swap usage in financial statements for fiscal years ending after June 15, 1990. With this in mind, SEC on-line in Lexis–Nexis was searched for nonfinancial companies reporting reference to the term ‘interest rate swap’ for annual reports published in 1991, 1993, and 1995. 6 The term was reported in 310 annual reports in 1991, 469 annual reports in 1993, and 526 annual reports in 1995. The 1991, 1993, and 1995 swap user databases were merged with firms where total assets and the stock price at the end of the fiscal year were available on the COMPUSTAT Annual PrimaryrSupplementaryrTertiary, Full Coverage and Research tapes. Information on COMPUSTAT was not available for 13 firms in the 1991 swap user database, 31 firms in the 1993 swap user database, and 29 firms in the 1995 swap user database. Swap users should be large firms. In order for swap intermediaries to profit on the bid–ask spread in a swap contract, the notional amount of the swap must be 6

Financial institutions were excluded from the data set. A financial institution has a primary SIC in the range 6000–6999.

Table 1 Total assets and debt to equity distribution of swap users

Total assets Lowest 25% 2nd 25% 3rd 25% Upper 25% Mean TA Žin millions. Debtr book equity Lowest 25% 2nd 25% 3rd 25% Upper 25% Mean DrME

1991

1993

1995

All firms

Swap users

Percent users Ž%.

All firms

Swap users

Percent users Ž%.

All firms

Swap users

Percent users Ž%.

1233 1234 1234 1234 Nonusers 58.1

0 6 46 236 Swap users 1,762.8 ) )

0 0 4 19

1379 1380 1380 1380 Nonusers 69.7

0 8 82 348 Swap Users 1,547.1) )

0 1 6 25

1593 1594 1594 1594 Nonusers 71.7

0 15 68 414 Swap users 1,942.0 ) )

0 1 4 26

973 973 973 974 Nonusers 0.31

28 80 102 73 Swap users 0.54 ) )

3 8 10 7

1051 1051 1051 1052 Nonusers 0.18

28 111 154 126 Swap users 0.39 ) )

3 11 15 12

1195 1195 1195 1195 Nonusers 0.19

38 151 155 120 Swap users 0.35 ) )

3 13 13 10

Swap users reported the term ‘interest rate swap’ in their annual report on SEC on-line. Total assets are COMPUSTAT item 6. The debt to equity ratio Ž DrME. is long-term debt plus debt in current liabilities divided by the market value of common equity ŽCOMPUSTAT items Ž9q34.rŽ199=25... The natural logarithm of the each variable was taken prior to calculating the mean. The mean reported is reported in anti-log form. )) Statistically significant at the 1% level.

K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

Quartile

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K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

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Table 2 Total assets and debt to equity ratio by type of use in 1993 Ratio

Fix payers

Float payers

Both

Unknown

Nonusers

TA DrME

828.2 ) ) 0.41) )

1,313.8 ) ) 0.38 ) )

3,473.3 ) ) 0.50 ) )

3,732.0 ) ) 0.33 ) )

69.7 0.18

Swap users reported the term ‘interest rate swap’ in there annual report on SEC on-line. Individual firm annual reports were read to determine the type of interest rate swap usage in 1993. Total assets are COMPUSTAT item 6. The debt to equity ratio Ž DrME. is long-term debt plus debt in current liabilities divided by the market value of common equity ŽCOMPUSTAT items Ž9q34.rŽ199=25... The natural logarithm of the each variable was taken prior to calculating the mean. The mean reported is reported in anti-log form. )) Statistically significant difference relative to nonusers at the 1% level.

large. In the early 1990s, swap intermediaries would not issue a swap contract for a notional amount less than US$5 million. Thus, firms using swaps must have at least US$5 million in debt that they would like to change from a floating to a fixed rate or vice versa. Table 1 examines total assets ŽTA. and the debt to equity ratio Ž DrME. for all firms and swap users. Total assets are COMPUSTAT item 6. Debt includes long-term debt plus debt in current liabilities ŽCOMPUSTAT items 9 q 34.. Equity is the market value of common equity ŽCOMPUSTAT items 199 = 25.. Table 1 verifies that swap users are large firms and they have high debt to equity ratios. Swap users are significantly larger than nonusers in every year that is examined. By 1995, 26% of all firms in the upper 25% quartile of total assets use swaps. Swap users have a significantly higher debt to equity ratio relative to nonusers in every year that is examined. In 1993, the average debt to equity ratio for swap users is more than twice the average ratio for nonusers. The 438 annual reports for 1993 were read in detail to determine whether the company used swaps as a fixed rate payer, a floating rate payer, both fixed and floating rate payer swaps, or if it was impossible to determine the type of use Žunknown.. 7 Total assets and the debt to equity ratio for swap users by type of usage in 1993 are presented in Table 2. Regardless of the type of usage, swap users have significantly more total assets and a significantly higher debt to equity ratio relative to nonusers. Table 3 shows an industry breakdown of interest rate swap use across time. Interest rate swap use has increased in total from 6% of all firms in 1991 to 8% of all public firms on COMPUSTAT in 1995. Between 1991 and 1995, swap use has increased or remained the same in all but the construction industry. Interest rate swap use has grown most dramatically in the transportation, communications, and

7

The 1993 annual reports were used because 1993 was the most complete up-to-date year available on SEC on-line when the study began.

Industry

Industry 2-digit SIC

1991 Total firms

Agriculture, forestry, and fishing Mining Construction Manufacturing Transportation, communications, public utilities Wholesale trade Retail trade Services Total

1993 Swap users

Percent users Ž%.

Total firms

1995 Swap users

Percent users Ž%.

Total firms

Swap users

Percent users Ž%.

01–09

29

1

4

30

1

3

32

3

9

10–14 15–17 20–39 40–49

366 79 2505 543

15 6 180 36

4 8 7 7

356 86 2795 603

29 6 251 66

8 7 9 11

376 99 3205 669

27 4 279 80

7 4 9 12

50–51 52–59 70–89 01–59, 70–89

244 369 800 4935

11 20 19 288

5 5 2 6

286 442 922 5520

15 34 36 438

5 8 4 8

327 507 1160 6375

20 39 45 497

6 8 4 8

Swap users reported the term ‘interest rate swap’ in their annual report on SEC on-line. The total number of firms were those with total assets and the stock price at the end of the fiscal year available on COMPUSTAT. The SIC codes used to separate industries were the primary SIC codes from COMPUSTAT.

K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

Table 3 Industry breakdown of interest rate swap usage across time

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Industry

Industry 2-digit Firms Swap users Fixed Percent users Float Percent users Both Percent users Unk Percent users SIC reporting no in 93 payers fixed Ž%. payers float Ž%. both Ž%. unk Ž%. use in 93

Agriculture, forestry, and fishing Mining Construction Manufacturing Transportation, communications, public utilities Wholesale trade Retail trade Services Total

01–09

0

1

1

100

0

0

0

0

0

0

10–14 15–17 20–39 40–49

2 0 6 3

27 6 245 63

12 3 99 25

44 50 40 40

9 1 47 8

33 16 19 13

0 1 31 9

0 16 13 14

6 1 68 21

22 16 28 33

1 0 1 13

14 34 35 425

4 21 17 182

29 62 49 43

7 7 7 86

50 21 20 20

2 3 7 53

14 9 20 12

1 3 4 104

7 9 11 24

50–51 52–59 70–89 01–59, 70–89

Swap users reported the term ‘interest rate swap’ in there annual report on SEC on-line. Individual firm annual reports were read to determine the type of interest rate swap usage in 1993. The SIC codes used to separate industries were the primary SIC codes from COMPUSTAT.

K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

Table 4 Breakdown of interest rate swap use by type of use in 1993

K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

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public utility industries. Usage in the transportation, communications, and public utility industries has grown from 7% of firms in 1991 to 12% of firms in 1995. The industry average debt to equity ratio for the transportation, communications and public utility industry was 0.61, 0.41, 0.47 in 1991, 1993, and 1995, respectively, which is larger than both the swap user and nonuser average for each year. Table 4 shows an industry breakdown of type of use in 1993. Of the 438 firms that reported the term ‘interest rate swap’, 13 firms used the term to describe previous or forthcoming use of swaps. Thus, there are 425 actual swap users in the 1993 data set. In total and in each industry except for wholesale trade, nonfinancial firms use fixed rate payer swaps more often than they use floating rate payer swaps. Forty-three percent of firms report using fixed rate payer swaps exclusively compared to only 20% of firms reporting use of floating rate payer swaps exclusively. This would imply that financial institutions ŽSIC 60–69. are net floating rate payers in order for the market to balance. Twelve percent of firms report using both fixed and floating rate payer swaps. In 1993, it was impossible to determine the type of usage for 24% of the swap users. To test the theories of swap usage, a data set based on the year of swap initiation was formed. Firms that used swaps directly related to currency swaps were excluded from the data set. The year of initiation is the year a firm first started to use swaps with no swap usage in the previous year. If the year of swap initiation was not specified in the 1993 annual report, then previous year annual reports were searched for reference to the year of initiation. In some cases, the year of initiation was implied. For instance, if there was a specific swap mentioned in the 1993 and 1992 annual reports but none in the 1991 and 1990 annual reports, then the year of initiation was assumed to be 1992. This method was used to trace specific swaps back to 1990. Swaps were not traced back prior to the 1990 annual report since swap usage was not required to be reported before this time. The year of swap initiation was available for 200 of the 438 swap users in the 1993 data set. This data set consists of 126 fixed rate and 74 floating rate payers. The fact that this data set is based on the year of swap initiation is what sets it apart from other empirical studies of the swaps market.

5. Tests of interest rate swap theories 5.1. Test Õariables The test variables used to compare fixed and floating rate payer swap users with each other and the industry were taken from the COMPUSTAT Annual PrimaryrSupplementaryrTertiary, Full Coverage and Research tapes and are summarized in Table 5. From Table 1, we know that total assets ŽTA. and the debt

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Theory

Variable

Proxy

Abbr.

COMPUSTAT Formula

Prediction

Table 1 Table 1 Inf. asymm.

Size Debt use Rating upgrade Actual growth Growth prospects Growth prospects Actual growth Growth prospects Growth prospects Discret. funds Bond rating Debt reduction New fixed assets

Total assets Debtrequity S&P rating upgrade Percent Dsales Mkt. eqty.rBook eqty. Pricerearnings per share Percent Dsales Mkt. eqty.rBook eqty. Pricerearnings per share Free cash flow S&P bond rating Total debt New PPErold PPE

TA DrME BUP Percent Dsales MErBE Pr E Percent Dsales MErBE Pr E FCrME Rating DOWNSIZE NewKrNetK

6 Ž9q34.rŽ199=25. 0,1 dummy for increase in 280 % D12 Ž199=25.r60 199r58 % D12 Ž199=25.r60 199r58 Ž12–16q D 35–15–19–21.rŽ199=25. 280 0,1 dummy if debt falls )10% 128r8

Users) Non Users) Non Fix ) FloatrNon Fix ) FloatrNon Fix s FloatrNon Fix s FloatrNon Fix ) FloatrNon Fix ) FloatrNon Fix ) FloatrNon Fix ) FloatrNon Float) FixrNon Fix ) FloatrNon Fix ) FloatrNon

Agency cost

Comp. adv. Downsizing Proj. comp.

K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

Table 5 Test variables

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67

to equity ratio Ž DrME. are larger for swap users relative to nonusers when not controlling for year of initiation. An implication of the information asymmetry theory is that fixed rate payers should experience an increase in their bond rating after initiating a swap. The ratings upgrade will allow fixed rate payers to reduce their interest expense. BUP is a dummy variable that takes on a value of one if a firm’s S & P bond rating increases from the year before to the year after swap initiation. It must be noted that S & P does not assign a bond rating for all firms available on the COMPUSTAT tapes. The S & P bond rating information is only available for a limited portion of the entire sample. The percentage change in sales Žpercent Dsales. is used to proxy actual growth and will be used to test the information asymmetry and agency cost theories. Fixed rate payers should have higher rates of actual growth compared to floating rate payers and nonusers according to both theories. Percent Dsales is calculated using the change in net sales ŽCOMPUSTAT item 12.. The market to book ratio ŽMErBE. and the price to earnings ratio Ž PrE . are used to proxy for the markets perception of growth opportunities and will be used to test the agency cost and the information asymmetry theories. According to the information asymmetry theory, fixed rate payers are not thought to have above average growth opportunities; thus, the information asymmetry theory predicts no difference or lower values of MErBE and PrE for fixed rate payers relative to floating rate payers and nonusers. According to the agency cost theory, fixed rate payers are expected to have underinvestment problems; thus, the agency cost theory predicts higher values for MErBE and PrE in the year prior to initiation for fixed rate payers relative to floating rate payers and nonusers. MErBE is the market price at the end of the fiscal year multiplied by the number of common shares outstanding divided by the book value of common equity ŽCOMPUSTAT items Ž199 = 25.r60.. PrE is the market price at the end of the fiscal year divided by the earnings per share ŽCOMPUSTAT items 199r58.. Undistributed free cash flow is used to proxy for the amount of discretionary funds available. A firm with an abundance of free cash flow is more likely to experience the asset substitution agency problems associated with a long-term debt issue. Based on the agency cost theory, fixed rate payers should have higher values of free cash flow compared to floating rate payers and nonusers. Free cash flow is calculated as in the work of Lehn and Poulsen Ž1989., operating income before depreciation minus total income tax plus the change in deferred taxes minus interest expense minus preferred dividends minus common dividends weighted by the book value of common equity ŽCOMPUSTAT items Ž12–16 q D 35–15–19– 21.r60.. The comparative advantage theory predicts that floating rate payers will have a higher debt rating than fixed rate payers and nonusers. Rating is the S & P bond rating where a AAA bond has a value of 22, AA q has a value of 21, and so on down to a D bond with a value of 1 Žtransformed COMPUSTAT 280..

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K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

The downsizing hypothesis asserts that fixed rate payers will experience a reduction in their amount of debt subsequent to the initiation of a swap. DOWNSIZE is a 0,1 dummy variable taking the value of one if the value of total debt falls by 10% or more from the year of initiation to the year after initiation. The project completion theory predicts that fixed rate payers will complete new capital projects coincident with the initiation of a swap. New capital expenditures weighted by net capital is NewKrNetK ŽCOMPUSTAT items 128r8.. Fixed rate payers should have higher values of NewKrNetK relative to floating rate payers and nonusers. 5.2. Tests of means The tests of means were conducted using a T-test with the results presented in Table 6. 8 The natural logarithm of each variable was taken prior to calculating the mean. 9 Means are reported in anti-log form. The T-tests on the left hand side of Table 6 are designed to identify differences between fixed and floating rate payer swap users. The T-tests on the right hand side of Table 6 use the percentage difference from the industry average Ži. to test for differences between users and nonusers of swaps within an industry and Žii. to test for differences between fixed and floating rate payer swap users while controlling for industry variation. 5.2.1. Tests of total assets and the debt to equity ratio In Tables 1 and 2, it was shown that swap users had significantly higher values for total assets and the debt to equity ratio relative to nonusers. Table 6 shows that in the year prior to swap initiation both fixed and floating rate payers have significantly higher values for total assets ŽTA. and the debt to equity ratio Ž DrME. relative to the industry average. Thus, when comparing swap users to nonusers in multivariate comparisons, it is necessary to control for total assets and the debt to equity ratio. There are no significant differences in total assets or the debt to equity ratio between fixed and floating rate payers. 5.2.2. Tests of the information asymmetry theory In the information asymmetry theory, fixed rate payers should exhibit higher than expected growth subsequent to swap initiation. The information asymmetry 8 The TTEST procedure in SAS was used to conduct the T-tests. The hypothesis of a normal distribution could be rejected at the 5% level for all variables except TA, DrME, and NewKrNetK for the combined fixed and floating rate payer sample. The hypothesis of a normal distribution could be rejected at the 5% level for all variables expressed as a percentage difference from the industry mean except TA, DrME, Rating, and NewKrNetK for the combined fixed and floating rate payer sample. Tests comparing the medians were also conducted. The Wilcoxon test of the UNIVARIATE procedure in SAS was used and the results were virtually identical to the T-test results. 9 In some cases, it was necessary to add a constant to the variable prior to taking the natural logarithm since it is impossible to log a negative number. In the case of the percentage change in sales, 100 was added to the variable prior to taking the natural logarithm. In the case of free cash flow weighted by market equity, 1 was added to the variable prior to taking the natural logarithm.

Fixed Floating Fixed Floating Fixed Floating Fixed Floating Fixed Floating Fixed Floating Fixed Floating Fixed Floating Fixed Floating Fixed Floating

TA Iy 1

114 71 113 66 38 34 114 71 107 70 89 61 110 71 42 38 114 62 111 61

N

614.31 888.69 0.41 0.41 0.26 0.08 21.34 7.74 1.83 1.95 17.93 21.99 0.11 0.09 13.43 14.27 0.30 0.24 0.20 0.16

Mean

y1.81 H 1: T / 0 0.95 H 1: T / 0 2.00 ) H 1: T ) 0 3.08 ) ) H 1: T ) 0 y0.73 H 1: T / 0 y1.72 H 1: T / 0 0.95 H 1: T ) 0 y1.19 H 1: T ) 0 0.79 H 1: T ) 0 0.84 H 1: T ) 0

T : fix s float

200.81 230.14 34.21 31.77 8.50 y10.85 10.76 y1.10 y1.33 5.16 y1.92 13.68 2.02 1.01 0.61 9.68 y3.33 y7.53 5.47 y2.01

Mean H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1: H 1:

T)0 T)0 T/0 T/0 T)0 T/0 T)0 T/0 T/0 T/0 T/0 T/0 T)0 T/0 T/0 T)0 T)0 T/0 T)0 T/0

T : fix s float y1.40 H 1: T / 0 0.12 H 1: T / 0 2.22 ) H 1: T ) 0 3.11) ) H 1: T ) 0 y0.74 H 1: T / 0 y1.36 H 1: T / 0 0.71 H 1: T ) 0 y1.79 ) H 1: T - 0 0.60 H 1: T ) 0 0.66 H 1: T ) 0

T : mean s 0 15.11) ) 14.65 ) ) 2.34 ) 2.31) 1.21 y2.10 ) 3.06 ) ) y0.74 y0.21 0.83 y0.26 1.60 1.82 ) 1.12 0.18 2.62 ) ) y0.79 y1.34 0.73 y0.27

Variable as percent diff. from industry avg.

Total assets ŽTA ., the debt to equity ratio Ž D rME ., the market to book ratio ŽMErBE ., the price earnings ratio Ž P r E ., free cash flow weighted by market equity ŽFCrME ., and the S&P bond rating ŽRating . are reported for the year prior to initiation. The percentage change in sales Žpercent D sales . is calculated using the change in net sales from the year before initiation to the year of initiation. BUP is a 0,1 dummy variable taking a value of one if the S&P bond rating increased from the year prior to the year after initiation. DOWNSIZE is a 0,1 dummy variable taking the value of one if the value of total debt falls by 10% or more over the interval in question. The new fixed assets proxy ŽNewKrNetK . is new capital expenditures in the year of initiation weighted by net capital in the year prior to initiation. The natural logarithm of the each variable except BUP and DOWNSIZE was taken prior to calculating the mean. The mean reported is reported in anti-log form. The results were produced from the TTEST and UNIVARIATE procedures in SAS. ) Statistically significant difference relative to nonusers at the 5% level. )) Statistically significant difference relative to nonusers at the 1% level.

NewK I rNetK Iy 1

DOWNSIZE I,Iq 1

Rating Iy 1

ŽFCrME . Iy 1

Ž P r E . Iy 1

ŽMErBE . Iy 1

Percent D sales I

BUPIy 1,Iq 1

Ž D rME . Iy 1

Payer

Variable

Table 6 Test of means

K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78 69

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lies in that the market did not expect the improved financial well-being. More specifically, the theory predicts that fixed rate payers should experience a ratings upgrade subsequent to swap issuance. The ratings upgrade will allow the fixed rate payer to borrow at a lower short-term rate of interest than they are receiving in their swap contract allowing borrowing costs to fall. Table 6 indicates that fixed rate payers experience a S & P bond rating ŽBUP. increase significantly more often than floating rate payers. This result supports the information asymmetry theory. The percentage increase in net sales Žpercent Dsales. for fixed rate payers is significantly higher than both floating rate payers and the industry average in the year of initiation. Because the increased sales figures are not known to the lender at the time of initiation, significantly higher sales performance in the year of swap initiation supports the information asymmetry argument. In the year prior to initiation, fixed rate payers have a lower ratio of market equity to book equity and a lower price earnings ratio than both floating rate payers and the industry average. These results are consistent with the information asymmetry theory. The preceding results taken together support the information asymmetry theory. The market does not believe the growth rates for fixed rate payer swap users are exceptional. Yet, fixed rate payer swap users experience a ratings upgrade more often than floating rate payers and exhibit significantly higher growth in sales in the year of initiation than floating rate payers and the industry. 5.2.3. Tests of the agency cost theory Firms that have a lot of discretionary funds are likely to experience the agency cost of asset substitution when issuing long-term fixed rate debt. If firms are using swaps to synthetically create long-term fixed rate debt to avoid the asset substitution problem it would follow that these firms would have a lot of free cash flow. The ratio of free cash flow relative to market equity ŽFCrME. in the year prior to swap initiation is used as a proxy for discretionary funds. Fixed rate payers should have a higher ratio of free cash flow to market equity relative to floating rate payers and the industry average. Firms with an abundance of growth opportunities are likely to encounter the agency cost of underinvestment. The ratio of market to book equity ŽMErBE. and the price earnings ratio Ž PrE . for the year prior to swap initiation are used to proxy growth opportunities. The percentage change in net sales in the year of initiation will measure actual growth. Fixed rate payers should have more growth and growth opportunities than floating rate payers and the industry average. Table 6 shows fixed rate payers have a higher ratio of free cash to market equity relative to floating rate payers and a significantly higher ratio relative to the industry average. This result is consistent with the agency cost theory. Fixed rate payers have a lower ratio of market to book equity and a low price earnings ration compared to both floating rate payers and the industry average, but

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neither of these findings is statistically significant. These findings are not consistent with the agency cost theory. Thus, the market does not view fixed rate payers as firms with exceptional growth opportunities. However, in the year of swap initiation, fixed rate payers have a significantly higher percentage change in net sales relative to floating rate payers and the industry. Taken together, the results lend some support to the asset substitution portion of the agency cost theory of swap usage. Fixed rate payers have significantly more free cash flow than their industry average. Excess free cash flow would create an asset substitution concern for lenders. Fixed rate payers experience actual growth that is significantly larger than the industry average; however, the market does not perceive that these companies will continue to experience rapid growth in the future. 5.2.4. Tests of the comparatiÕe adÕantage theory According to the comparative advantage theory, the credit rating for a floating rate payer should be higher than that of a fixed rate payer at the time of swap initiation. The S & P bond rating for the year prior to swap initiation ŽRating Iy1 . used to test the comparative advantage theory in Table 6. Floating rate payers do have a higher mean S & P bond rating compared to fixed rate payers; however, this result is not statistically significant when not controlling for industry variation. The average floating rate payer rating of 14.27 is between an S & P rating of BBB Ž14. and BBB q Ž15.. On the other hand, the average fixed rate payer rating of 13.43 is between BBB y Ž13. and BBB Ž14.. When controlling for industry variation, floating rate payers have a significantly higher S & P bond rating relative to fixed rate payers. Floating rate payers have a S & P bond rating that is significantly higher than their industry average. Firms that enter swaps as floating rate payers average a S & P bond rating that is 9.68% higher than the industry average. For example, if the industry average were BBB, the average floating rate payer in that industry would have an S & P bond rating of BBBq . In summary, there is evidence that firms that enter floating rate payer swaps have higher credit ratings than fixed rate payers and nonusers. These results lend some support to the comparative advantage theory. Arguably, swap intermediaries prefer higher ratings for floating rate payers because the floating rate payer in a swap is taking on more interest rate risk than a fixed rate payer. It must be noted that S & P does not assign a bond rating for all firms available on the COMPUSTAT tapes. The S & P bond rating information is only available for a limited portion of the entire sample. 5.2.5. Tests of the downsizing theory A firm that expects the possibility of future downsizing recognizes that it may have to refund its long-term debt. If the expected cost of refunding its long-term debt is greater than the cost of unwinding a fixed rate payer swap used in

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conjunction with short-term floating rate debt, then firms that expect downsizing would enter fixed rate payer swaps and issue short-term rather than long-term debt. A dummy variable ŽDOWNSIZE. that is set equal to one if the firm experiences a 10% reduction in total debt Žlong-term debt plus debt in current liabilities. from the year of to the year after initiation and set equal to zero otherwise is used to test this theory. According to the downsizing theory, firms using fixed rate payer swaps should experience downsizing relatively more often than floating rate payers and the industry average. Table 6 shows that fixed rate payers experience a 10% or larger decrease in total debt more often than floating rate payers, although these results are not statistically significant. Furthermore, fixed rate payers experience downsizing less frequently than the industry average. Thus, the results do not support the downsizing theory of swap usage. 5.2.6. Tests of the project completion theory The project completion theory implies fixed rate payers enter their swaps at the time of new project completion. During the production phase, borrowing at a floating rate of interest allows managers to manipulate the scale of the project when interest rates change. Once the project is complete, interest rate changes no longer effect the efficient operation of the new capital. A swap is a way to convert the floating rate of interest on the debt used to fund the project to a fixed rate of interest. If the project completion theory does explain the use of swaps, fixed rate payers should exhibit more new capital expenditures in the year of swap initiation relative to floating rate payers and nonusers. New capital expenditures scaled by net capital in the year prior to initiation ŽNewKrNetK. is the variable used to test this theory. Table 6 shows fixed rate payers do not have a significant differences in new capital expenditure scaled by net capital relative to floating rate payers or the industry average. This result does not support for the project completion theory. 5.3. Logistic regressions 5.3.1. Logistic regressions: Fixed and floating rate payers Õs. the 1993 nonusers Logistic regression analysis was conducted in order to compare swap users to nonusers in a multivariate sense. Nonusers with annual reports filed between January 1, 1993 and December 31, 1993 are used as the control group. A binary response variable that can take on one of two possible values Ža swap user or a nonuser. is used as the dependent variable. The regressions were run using both the variable itself and the percentage difference from the industry average for the various financial variables as the independent right hand side variables. When calculating the percentage difference from the industry average for swap users, the year of initiation is used as the year of reference. Since the nonusers did not

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initiate a swap, 1993 is considered the year of initiation for the control group and used as the year of reference when calculating the percentage difference from the industry average for all variables. The right hand side variables are primarily used to test the different theories pertaining to the likelihood that a firm would enter a swap as either a fixed or a floating rate payer. All of the variables from Table 6 were used as explanatory variables. For all of the variables in the combined swap user and control group sample, the null hypothesis of a normal distribution could be rejected at the 5% level for both the variable itself and the percentage difference from the industry average. Of all of the variables in the combined swap user and control group sample, only one set of variables had a correlation coefficient above 0.5. MErBE with DrME had a correlation coefficient of y0.63. Of all of the variables expressed as a percentage difference from the industry average in the combined swap user and control group sample, only two sets of variables had a correlation coefficient above 0.5. Percent Dsales with NewKrNetK had a correlation coefficient of 0.60 and MErBE with DrME had correlation coefficient of y0.52. Table 7 presents the results from the multivariate analysis. 10 Panel A compares fixed rate payers to the 1993 nonusers. Panel B compares floating rate payers to the 1993 nonusers. The results were produced from the LOGISTIC procedure in SAS. Panel A of Table 7 highlights total assets ŽTA. and the percentage change in net sales Žpercent Dsales. as two distinguishing financial variables between fixed rate payers and nonusers. Increases in both of these variables increase the likelihood that a fir is a fixed rate payer swap user relative to a nonuser. The coefficient estimates for total assets and the percentage change in net sales are statistically significant in all of the regressions reported in Panel A. The results from Panel A of Table 7 lend support to the information asymmetry theory. In a multivariate sense, above average sales growth in the year of initiation distinguishes fixed rate payer swap users from nonusers. The coefficient estimate for growth opportunities ŽMErBE. should not be significantly different from zero or negative according to the information asymmetry theory. The coefficient estimate for MErBE is not significantly different from zero in any of the regressions. The results from Panel A of Table 7 lend some support to the agency cost theory. Sales growth in the year of initiation is significantly higher for fixed rate payer swap users compared to nonusers. The coefficient estimate for the amount of discretionary funds ŽFCrME. is not significantly different from zero; but, it does have the positive sign predicted by the agency cost theory. The coefficient

10 Analysis including BUP and Pr E is not reported in Table 7 or Table 8. The significant results that are reported are not altered when BUP andror Pr E are included; but, the sample size is decreased. The coefficient estimates for BUP and Pr E are not significant in a multivariate sense.

Variable

H1

Coef. estimate

29.25 ) ) 45.81) ) 3.02 8.22 ) ) 0.15 0.93 – 1.43

Panel B: floating rate payers Õs. the 1993 nonusers Intercept – y6.00 10.65 ) ) TA Iy 1 float/ non y0.00 0.00 Ž DrME. Iy 1 float/ non 0.07 0.18 Rating Iy 1 float) non 1.28 2.27 Percent concordant 55.5 Model x 2 4.3 Float sample 37 Nonuser sample 546

Coef. estimate

x2

Variable as percent diff. from industry avg. Coef. estimate

x2

Coef. estimate

x2

y7.85 0.32 0.15 0.66 0.10 1.23 0.25 0.18 71.8 48.7 96 2157

19.66 ) ) 36.94 ) ) 2.80 4.14 ) 0.36 1.43 1.08 1.44

y3.7652 0.0044 0.0012 0.0108 0.0026 0.0127 – 0.0012 77.6 88.2 101 2556

642.80 ) ) 64.14 ) ) 2.09 13.22 ) ) 2.78 1.47 – 0.62

y3.6476 0.0041 0.0011 0.0091 0.0029 0.0162 0.0001 0.0012 75.9 71.39 96 2157

566.73 ) ) 53.49 ) ) 1.57 8.47 ) ) 3.11 2.15 0.00 0.56

y6.50 0.46 0.06 – 81.8 73.1 66 3370

224.25 ) ) 63.49 ) ) 0.58 –

y3.1754 0.0014 0.0008 0.0162 63.9 9.8 37 546

65.73 ) ) 0.93 0.22 2.65

y4.5362 0.0043 0.0001 – 82.4 82.9 66 3370

603.06 ) ) 74.59 ) ) 0.01 –

Total assets ŽTA., the debt to equity ratio Ž DrME., the market to book ratio ŽMErBE., free cash flow weighted by market equity ŽFCrME., and the S&P bond rating ŽRating. are reported for the year prior to initiation. The percentage change in sales Žpercent Dsales. is calculated using the change in net sales from the year before initiation to the year of initiation. DOWNSIZE is a 0,1 dummy variable taking the value of one if the value of total debt falls by 10% or more over the interval in question. The new fixed assets proxy ŽNewKrNetK. is new capital expenditures in the year of initiation weighted by net capital in the year prior to initiation. The natural logarithm of the each variable except DOWNSIZE was taken prior to calculations. The results were produced from the LOGISTIC procedures in SAS. ) Statistically significant difference relative to nonusers at the 5% level. )) Statistically significant difference relative to nonusers at the 1% level.

K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

Panel A: fixed rate payers Õs. the 1993 nonusers Intercept – y8.95 TA Iy 1 fix / non 0.35 Ž DrME. Iy 1 fix / non 0.15 Percent Dsales I fix ) non 0.87 ŽMErBE. Iy 1 fix / non 0.06 ŽFCrME. Iy 1 fix ) non 0.93 DOWNSIZE I,Iq1 fix ) non – NewK I rNetK Iy1 fix ) non 0.18 Percent concordant 74.0 Model x 2 62.7 Fix sample 101 Nonuser sample 2556

x2

74

Table 7 Logistic analysis comparing fixed and floating rate payers to 1993 nonusers

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estimate for growth opportunities ŽMErBE. should be positive according to the underinvestment argument of the agency cost theory. The coefficient estimate for MErBE is not significantly different from zero; but it does have the positive sign predicted by the agency cost theory. The regressions in Panel B of Table 7 indicate that when total assets, debt to equity, and the S & P bond rating are used as independent variables, no variable distinguishes floating rate payers from nonusers. The fact that S & P only gives a bond rating to a limited number of firms on the COMPUSTAT tapes severely limits the sample. Firms that have bond ratings are large firms with high levels of debt just like floating rate payer swap users. When only total assets and the ratio of debt to equity are used as independent variables, it is seen that floating rate payers have significantly higher amounts of total assets relative to nonusers. 5.3.2. Logistic regressions: Fixed Õs. floating rate payers Logistic regression analysis was conducted in order to estimate how the financial variables affected the likelihood that a firm used a swap as a fixed rate payer relative to a floating rate payer. A binary response variable that can take on one of two possible values Ža fixed rate payer or a floating rate payer. is used as the dependent variable. The regressions were run using both the variable itself and the percentage difference from the industry average for the various financial variables as the independent right hand side variables. For all of the variables in the combined fixed and floating rate payer sample, the null hypothesis of a normal distribution could be rejected at the 5% level for all of the variables except TA, DrME, and NewKrNetK. For all of the variables expressed as a percentage difference from the industry average in the combined fixed and floating rate payer sample the null hypothesis of a normal distribution could be rejected at the 5% level for all of the variables except TA, DrME, Rating, and NewKrNetK. Of all of the variables in the combined fixed and floating rate payer sample, only two sets of variables had a correlation coefficient above 0.5. MErBE with DrME had a correlation coefficient of y0.57 and NewKrNetK with percent Dsales had a correlation coefficient of 0.62. Of all of the variables sample expressed as a percentage difference from the industry average in the combined fixed and floating rate payer sample, only two sets of variables had a correlation coefficient above 0.5. DrME with Rating had a correlation coefficient of y0.51 and MErBE with DrME had correlation coefficient of y0.59. Table 8 presents the results from the multivariate analysis. The results were produced using the LOGISTIC procedure in SAS. Table 8 highlights the percentage change in net sales Žpercent Dsales. as the main distinguishing feature between fixed and floating rate payers in a multivariate sense. The percentage change in net sales coefficient estimate is statistically significant at the 5% level in two of the four regressions presented and significant at the 1% level in one of the four regressions presented. As the percentage change in net sales increases, the likelihood of a firm using a fixed rate payer swap

76

Table 8 Logistic analysis comparing fixed to floating rate payers H1

Coef. estimate

x2

Coef. estimate

x2

Variable as percent diff. from industry avg. Coef. estimate

Intercept Percent Dsales I ŽMErBE. Iy 1 ŽFCrME. Iy 1 Rating Iy 1 DOWNSIZE I,Iq1 NewK I rNetK Iy1 Percent concordant Model x 2 Fix sample Float sample

– fix ) float fix / float fix ) float fix - float fix ) float fix ) float

y15.16 3.42 y0.41 2.61 – 0.37 0.27 66.4 12.38 96 57

)

5.11 5.96 ) ) 1.67 1.51 – 0.79 0.91

y18.34 4.83 0.25 2.37 y1.46 0.70 0.41 66.3 11.2 36 33

1.40 2.59 0.16 0.54 1.04 1.05 0.49

0.5077 0.0372 y0.0045 0.0163 – 0.0033 0.0029 66.2 11.95 96 57

x2 ))

7.90 6.38 ) 1.98 0.62 – 0.63 0.98

Coef. estimate

x2

0.4718 0.0742 0.0050 0.0252 y0.0277 0.0042 0.0000 72.6 15.79 36 33

1.98 4.90 ) 0.49 0.55 3.87 0.33 0.00

Total assets ŽTA., the debt to equity ratio Ž DrME., the market to book ratio ŽMErBE., free cash flow weighted by market equity ŽFCrME., and the S&P bond rating ŽRating. are reported for the year prior to initiation. The percentage change in sales Žpercent Dsales. is calculated using the change in net sales from the year before initiation to the year of initiation. DOWNSIZE is a 0,1 dummy variable taking the value of one if the value of total debt falls by 10% or more over the interval in question. The new fixed assets proxy ŽNewKrNetK. is new capital expenditures in the year of initiation weighted by net capital in the year prior to initiation. The natural logarithm of the each variable except DOWNSIZE was taken prior to calculations. The results were produced from the LOGISTIC procedures in SAS. ) Statistically significant difference relative to nonusers at the 5% level. )) Statistically significant difference relative to nonusers at the 1% level.

K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

Variable

K.T. Saundersr Journal of Corporate Finance 5 (1999) 55–78

77

increases. The coefficient estimate for the market to book ratio is not significant in any of the four regressions which is consistent with the predictions of the information asymmetry theory. The significance of percent Dsales in connection with the positive coefficient estimates for free cash scaled by market equity lend support to the asset substitution argument of the agency cost theory. The number of observations in regressions that include the S & P bond rating are limited due to a lack of a reported value in COMPUSTAT for many firms. These regressions are included because a difference in bond rating is the primary testable implication of the comparative advantage theory. The coefficient estimates on the bond rating variable are the correct sign according to the theory, but, not statistically significant.

6. Conclusion The market for interest rate swaps is a growing market where most nonfinancial firms use fixed rate payer swaps. Regardless of whether the firm is a fixed or a floating rate payer, interest rate swap users are significantly larger than their industry counterparts and have a significantly higher debt to equity ratio relative to nonusers. In the year of initiation, fixed rate payers experience a percentage increase in net sales that is significantly larger than floating rate payers and the industry average. The results of this paper support the information asymmetry theory ŽTitman, 1992.. Fixed rate payers experience a ratings upgrade from the year before to the year after swap initiation significantly more often than floating rate payers and have significantly higher sales growth in the year of initiation relative to floating rate payers and nonusers. Further, the expected growth proxies ŽMErBE and PrE . are not significantly different from floating rate payers and nonusers. The asset substitution argument of the agency cost theory ŽWall, 1989. is supported by the fact that fixed rate payers have significantly more discretionary funds relative to nonusers in the year prior to initiation and have a significantly higher rate of growth in the year of initiation relative to nonusers. However, the amount of discretionary funds is not a significant distinguishing variable in a multivariate sense. The floating rate payer side of the market is not well developed theoretically or empirically. Floating rate payers have a significantly higher S & P bond rating relative to nonusers when controlling for industry variation. This is most likely a result of swap intermediaries selling the riskier floating rate payer side of the contract to highly rated firms rather than a result of floating rate payer firms trying to use their comparative advantage ŽBicksler and Chen, 1986. in the debt market. Future theoretical and empirical work should develop more explanations for the use of floating rate payer swaps by nonfinancial firms.

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Acknowledgements This article includes work from my dissertation at Clemson University. I would like to thank the editor, Cotton M. Lindsay, Robert E. McCormick, Michael T. Maloney, and Raymond D. Sauer for their comments and suggestions.

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