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United States of America: Selected Issues

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International Monetary Fund
Published Date:
August 2002
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III. Corporate Balance Sheets and Economic Slowdowns1

“… moderate leverage undoubtedly boosts the capital stock and the level of output… the greater the degree of leverage in any economy, the greater its vulnerability to unexpected shortfalls in demand and mistakes.”

Greenspan (2002)

1. The rapid accumulation of corporate debt in the United States during the 1990s and recent high profile bankruptcies raise questions about the vulnerability of the corporate sector and whether corporate balance sheet fragilities could hinder the recovery. This paper presents empirical evidence that corporate indebtedness in conjunction with other fundamentals, such as future growth prospects and current macroeconomic conditions, can explain the likelihood and severity of economic downturns. A Corporate Vulnerability Index is constructed to take into account these fundamentals. The index successfully predicts U.S. economic slowdowns, including the 2001 recession, and their severity.

A. Recent Developments

2. Since late 1994, nonfinancial corporate debt has increased at an average annual rate of 7 percent in real terms (Table 1). Even during the recent recession, debt accumulation continued at about 3 percent—well above the average rate of other post-war recessions. As a result, nonfinancial corporate debt reached an unprecedented 48 percent of GDP by the end of 2001 (Figure 1).

Table 1.United States: Average Annual Growth of Corporate Assets and Debt 1/(In percent)
Financial AssetsTangible AssetsTotal AssetsMarket Debt 2/
1952-2001 average9.33.86.17.2
1952-1994 average5.52.93.64.6
1995-2000 average10.74.77.37.8
2001 average0.4-1.5-0.63.4
Source: Board of Governors of the Federal Reserve, Flow of Funds Accounts of the United States.

In real terms. Nominal figures were deflated by the chain-type GDP deflator.

Market debt is defined as a sum of corporate bonds, commercial paper, bank loans, nonbank loans, and commercial mortgages.

Source: Board of Governors of the Federal Reserve, Flow of Funds Accounts of the United States.

In real terms. Nominal figures were deflated by the chain-type GDP deflator.

Market debt is defined as a sum of corporate bonds, commercial paper, bank loans, nonbank loans, and commercial mortgages.

Figure 1.United States: Market Debt of U.S. Nonfarm Nonfinancial Corporate Sector

(In percent of GDP)

Figure 2.United States: capital Expenditures and P/E Ratios of S&P 500 Composite stock Index

Figure 3.United States: Nonfarm Nonfinancial corporate sector: Funds Raised

Figure 4.United states: Nonfarm Nonfinancial corporate sector: Bank versus Bond Financing

Sources: Haver Analytics; and Board of Governors of the Federal Reserve, Flow of Funds Accounts of the United States.1/ Market debt is defined as the sum of corporate bonds, commercial paper, bank loans, nonbank loans, and commercial mortgages.

3. Several factors contributed to the rapid increase in debt. First, corporations stepped up their borrowing in order to finance new investments—in response to strong growth expectations as evidenced by strong capital expenditure and rich equity valuations (Figure 2). Second, beginning in 1995, U.S. corporations increased the frequency and magnitude of equity buybacks—these amounted to a cumulative net $3.65 trillion during 1995-2000—which were largely financed through issuing debt (Figure 3).2 Third, increased financial intermediation over the last decade may have also facilitated debt expansion. The growth of nonbank intermediaries, the developments of the high-yield and asset-backed bond markets, and the growth of pension funds and money market mutual funds opened up new sources of borrowing for companies that previously depended on internally generated funds or bank loans (Figure 4).

4. The rapid buildup of debt has been suggested to reflect a weakening of corporate balance sheets. However, alternative measures of leverage provide a mixed picture (Figure 5):3

  • The ratio of debt to tangible assets increased rapidly in the late 1990s and reached a historical peak of 54 percent by the end of 2001.4

  • In contrast, the ratio of debt to total assets increased much more modestly and stayed below 30 percent, reflecting the rapid growth in the value of financial assets during 1995-2001 (Table 1.)

  • The ratio of market debt to the sum of debt and equity (market value) also began to increase only in early 2000, after declining throughout the 1990s because of soaring equity prices. Thereafter, the stock market correction coupled with continued strength in corporate borrowing raised this measure of leverage, but still left it well below its 1970–90 average.

Figure 5.United states: Corporate sector; Leverge Rations 1/

Figure 6.United States: Corporate sector; Gross and set Dept-service Burden

(In percent of corporate profits)

Figure 7.United States: Corporate sector Total Leverage 2/

(In percent)

Figure 8.United states: corporate sector; Maturity composition of market Debt

(In percent)

Figure 9.United states: Corporate Sector; Total Leverage and Corporate Bond Spreads

(In percent)

Figure 10.United states: corporate sector: Historical Rates

(In percent)
Sources: Board of Governors of the Federal Reserve, Flow of Funds Accounts of the United States; Moody’s; and staff estimates.1/ Debt is Measured at book value, and equities are measured at market value2/ Total Leverage is defined as a sum of balance sheet leverage and a stock measure of gross debt burden, converted from flows using a present value technique. Shaded areas indicate recession periods.3/ The spread between yields on the Baa-rated corporate Bond Index and the Composite Treasury Bond Index. Shaded areas indicated recession periods.

5. With a substantially higher level of debt, the corporate debt-service burden has increased (Figure 6). Gross interest on debt reached 106 percent of pre-tax corporate profits in the last quarter of 2001, but stayed well below the historical peak of 245 percent that it reached in the last quarter of 1981.5 Net interest on debt—adjusted for receivables—increased almost two-fold during 1997–2001 to nearly 40 percent of profits, but also remained well below its previous peak. Debt-service burdens also started to decline in late 2001 as a result of lower interest rates.

6. A broader index of total leverage—a sum of the debt-service burden and balance sheet leverage (debt as a share of debt plus equity)—trended up since 1995, as an increase in the debt burden outpaced a decline in balance sheet leverage (Figure 7).6 However, after peaking in the first quarter of 2001, total leverage declined by almost 30 percent as corporations slowed their pace of borrowing and interest rates declined. Leverage is expected to stay at this lower level for some time as corporations have locked in lower borrowing costs by swapping short-term debt for longer-term financing (Figure 8).

B. Corporate Debt and the Macroeconomy

7. The financial conditions of the private sector have long been recognized as exerting a powerful effect on the macroeconomy. For example, the structural theory of corporate debt directly links an increase in leverage with higher corporate default risk and thus higher costs of external financing, which, in turn, tend to reduce investment, depress future cash flows and output, and thus may trigger a slowdown.7 Empirical evidence also suggests that leverage and other balance-sheet indicators have a major influence on investment spending, inventories, and employment.8 Moreover, the financial accelerator theory as in Bernanke, Gertler, and Girchrist (1996) and Bernanke and Gertler (1995) suggests that high corporate leverage can worsen slowdowns by amplifying and propagating initial adverse shocks and by en may inhibit economic recovery by creating liquidity problems that, combined with weak profits, may crowd out productive investments and push up default rates.

8. Recent developments appear to confirm that highly leveraged corporations are seen as more risky and face higher premiums on borrowed funds. Corporate spreads have increased in tandem with total leverage since the mid-1990s, even though the strength of equity prices pointed to optimistic expectations about future earnings growth (see Figure 2 and Figure 9). In addition, rising corporate defaults in both investment grade and high-yield sectors (Figure 10) and declining recovery rates have accompanied the increase in corporate leverage.9 Finally, the data clearly indicate that total corporate leverage tends to increase before and during recessions—on average, its level is about 35 percent higher during recessions than during expansions (see Figure 7).

9. But how much leverage is too much? According to the structural theory of corporate debt, the cost of external funds is not very sensitive to an increase in leverage if the value of corporate assets is well above the default barrier, which in turn depends on the condition of the balance sheet, market structure, and macroeconomic variables.10 Moreover, an increase in leverage may not raise the probability of a corporation going bankrupt if it is offset by improved growth expectations, more favorable debt contract terms, and more accommodative monetary policy. This suggests that the vulnerability of the corporate sector to economic shocks and thus the probability of recessions should be related to a combination of variables, rather than corporate leverage alone. The next section explores this issue in detail.

C. Corporate Vulnerability and Recessions 11

10. In order to examine whether corporate leverage itself provides meaningful information about the business cycle, a model was estimated that related the probability of recession to corporate leverage and a range of other macroeconomic variables. Specifically, a probit model was used with a recession index (Rt) as a dependent variable.12 In addition to total leverage, the independent variables included average weekly hours worked, the Conference Board vendor performance index, housing starts, the slope of the Treasury yield curve, and stock returns.13 The estimation results indicated that corporate leverage was not statistically significant in predicting the probability of recession when controlling for other leading indicators.14

11. However, these results left open the possibility that a broader measure of corporate vulnerability could be relevant in explaining the probability and severity of recessions. In particular, the discussion above suggested that corporate debt represented an incomplete index and that it is also important to take into account a range of other factors in assessing the strength of the corporate sector. Accordingly, a Corporate Vulnerability Index (CVI), which includes a broader range of factors, was constructed using the structural model of perpetual corporate debt by Anderson, Sundaresan, and Tychon (1996) (AST) to estimate the default probability for the entire corporate sector.15 In this model, corporate bond yields depend on leverage, the risk-free interest rate, bankruptcy costs, the recovery rate, and the probability that a corporation will default on its debt obligations. The corporate default probability, in turn, is a nonlinear function of leverage, volatility of the firm’s value, the risk-free interest rate, bankruptcy costs, the recovery rate, and the dividend payout rate.16

12. The theoretical corporate bond yield was fitted using nonlinear least squares to actual yields on the aggregate Baa-rated long-maturity corporate bond index over the period 1969Q1 to 2001Q4.17 The model fits both nominal and real yields well (Figure 11 and Figure 12), with squared errors being less than 10 percent for nominal yields, and less than 14 percent for real yields.18 While parameters of both nominal and real models are similar, the cost of bankruptcy and the recovery rate are somewhat higher when expressed in real terms (Table 2).

Figure 11.United States: Nominal Corporate Bond Yields: Actual and Fitted

(In percent)

Figure 12.United States: Real Corporate Bond Yield: Actual and Fitted

(In percent)

Source: Moody’s Investors Service, and staff estimates.

Table 2.United States: Estimation Results of Fitting the Model to Corporate Yields 1/
Nominal YieldsReal Yields
CoefficientStandard ErrorCoefficientStandard Error
CONST14.352*0.20410.944*0.188
THETA2.004*0.1034.314*0.188
BCOST6.982*0.41410.699*0.568
A0.099*0.0000.178*0.001
BBETA27.599*0.01820.044*0.037
Adj. R-squared = 0.823Adj. R-squared = 0.849

Coefficient significant at a 1 percent level.

The model estimated is: yt = CONST + yt (LEVERt, rt, A SIGMAt, BCOST, THETA, BBETA) + ut, where yt is the yield on a long-maturity Corporate Bond Index; y, (.) is a theoretical corporate bond yield, derived in Anderson, Sundaresan, and Tycon (1996); LEVER t is a measure of total leverage, rt is the yield on a long-maturity Treasury Composite Bond Index, and SIGMA t is equity volatility. CONST, a recovery rate THETA, a volatility scaling factor A, a bankruptcy cost BCOST, and a dividend rate BBETA are constant model parameters, ut is a residual. The model is estimated by nonlinear least squares over the sample from 1969Q1 to 2001Q4.

Coefficient significant at a 1 percent level.

The model estimated is: yt = CONST + yt (LEVERt, rt, A SIGMAt, BCOST, THETA, BBETA) + ut, where yt is the yield on a long-maturity Corporate Bond Index; y, (.) is a theoretical corporate bond yield, derived in Anderson, Sundaresan, and Tycon (1996); LEVER t is a measure of total leverage, rt is the yield on a long-maturity Treasury Composite Bond Index, and SIGMA t is equity volatility. CONST, a recovery rate THETA, a volatility scaling factor A, a bankruptcy cost BCOST, and a dividend rate BBETA are constant model parameters, ut is a residual. The model is estimated by nonlinear least squares over the sample from 1969Q1 to 2001Q4.

13. The CVI was constructed by substituting the estimated parameters into an analytical expression for the probability of default. The resulting CVI is a nonlinear function, increasing in leverage and the risk-free interest rate, and non-monotonic in asset volatility. Since its peak in the early 1980s, which was caused by a combination of high interest rates and leverage, the CVI has generally trended down during most of the 1990s, driven by either declining leverage or lower interest rates (Figure 13). The CVI increased modestly at the end of the 1990s, reflecting a rise in debt levels and an increase in asset volatility, which were partially offset by lower interest rates.

Figure 13.United States: Real Corporate Vulnerability Index 1/

1/ Shaded areas indicate recession episodes.

Predicting the probability of recession

14. In order to test the relevance of the CVI as an indicator of macroeconomic conditions, it was used as an explanatory variable in the previously described probit model of the probability of a recession. In contrast to the leverage variable, the CVI is a significant predictor of the probability of recession four to six quarters ahead (Table 3). For example, a 10 percent increase in the CVI is associated with a 2.7 percent increase in the probability of recession four quarters in the future. The fact that the CVI is significant in signaling the probability of recession only at longer horizons suggests that as markets recognize an increase in corporate vulnerability, the cost of external funding rises and corporations are forced to work on improving their balance-sheet positions. By the time the economy slips into a recession, corporate balance sheets have typically already begun to improve, thereby lowering the CVI.

Table 3.United States: Predicting the Probability of Recession, Probit Estimations
k=0k=1k=2k=3k=4k=5k=6
CoefficientStandard ErrorCoefficientStandard ErrorCoefficientStandard ErrorCoefficientStandard ErrorCoefficientStandard ErrorCoefficientStandard ErrorCoefficientStandard Error
C1-1.2160.911-1.0601.1730.7161.3981.649***1.0173.034*1.0661.616***0.8952.165**1.022
C2-1.539*0.341-0.900*0.3080.1020.3140.2780.2730.535*0.2891.609**0.7260.2760.375
C3-0.0010.021-0.0050.0200,0220.0220.0270.0170.0340.021-0.0410.028-0.0030.018
C4-0.002*0.001-0.002*0.001-0.002**0.001-0.0010.0010.0010.0010.0000.0010.003*0.001
C50.0070.071-0.242***0.109-0.441*0.108-0.501*0.125-0.613*0.1310.309**0.121-0.671*0.137
C6-6.7992.976-17.201*4.545-11.513*4.159-5.7964.093-2.9983.628-2.4582.6473.9813.703
C063.697*13.53739.099*12.392-4.06113.271-13.7411.118-27.16**12.026-0.4431.151-17.64616.134
Pseudo R20.4760.6020.5670.4780.4660.2080.282
* Coefficient significant at a 1 percent level; ** at a 5 Percent level; *** at a 10 percent level.The model estimated is: Prob (Rt+k = 1) = N(c0 + c1 CVIt + c2 AVGHRSt + c3 VENDORt + c4 HOUSINGt + c5 TRY_STRt + c6 SPRETt) where Rt+k is the NBER recession index; the CVI, is the Corporate Vulnerability Index; AVGHRSt, is average weekly hours worked; VENDORt, is the vendor performance index; HOUSINGt, is housing starts; TRY_STRt, is the Treasury yield curve; and SPRETt, is stock returns. N(.) is a cumulative normal distribution function, k is a forecasting horizon, in quarters.
* Coefficient significant at a 1 percent level; ** at a 5 Percent level; *** at a 10 percent level.The model estimated is: Prob (Rt+k = 1) = N(c0 + c1 CVIt + c2 AVGHRSt + c3 VENDORt + c4 HOUSINGt + c5 TRY_STRt + c6 SPRETt) where Rt+k is the NBER recession index; the CVI, is the Corporate Vulnerability Index; AVGHRSt, is average weekly hours worked; VENDORt, is the vendor performance index; HOUSINGt, is housing starts; TRY_STRt, is the Treasury yield curve; and SPRETt, is stock returns. N(.) is a cumulative normal distribution function, k is a forecasting horizon, in quarters.

15. The model using the CVI outperforms other specifications in predicting the probability of a recession. A high probability of recession was predicted four quarters in advance of the 1990–1991 recession, while other widely used leading indicators failed to do so. For example, the probit model including the CVI predicted an 86 percent probability that the economy would slip into recession in 1990, while the Estrella and Mishkin (1997) model, which uses the Treasury yield curve and stock prices, implied only a 25 percent probability.19

16. The model using the CVI and other leading indicators correctly predicted the recent slowdown four quarters in advance and forecasted a recession in the first quarter of 2001 with 53 percent probability (Figure 14). In contrast, without the CVI, the model did not predict a slowdown and implied only 6 percent probability of a recession in the first quarter of 2001 (Figure 15).

Figure 14.United States: Probability of Recession, Predicted with the corporate Vulnerability Index 1/

Figure 15.United States: Probability of Recession, Predicted without the Corporate Vulnerability Index1/

Source: Staff estimates.

1/ Shaded areas indicate recession episodes.

17. It is noteworthy that after edging up since 1999, the CVI declined in the fourth quarter of 2001 by 23 percent compared to the first quarter of 2001, indicating a decrease in recessionary risks.20

Predicting the severity of recession

18. The CVI can also be used to assess whether the health of the corporate sector is related to the severity of recession. A Severity of Recession Index (SRI) is constructed as follows. First, the magnitude of a cumulative decline of real GDP between the pre-recession quarter and the last quarter of the recession, normalized by the length of the recession, is calculated. Second, recessions are then ranked, with a smaller rank representing a less severe recession or a group of less severe recessions (Table 4). The SRI is zero during expansion periods.

Table 4.United States: The Severity of Recession Indices
Real GDP Decline Cumulative (percent)Length QuarterReal GDP Decline per Quarter (percent)Rating: Inidvidual*Rating/Grouped Decline per QuarterRating GroupedRating: Recession Length
RecessionsNo. 1**No. 2***
Q3 1953-Q2 19542.640.653323
Q4 1957-Q2 19584.231.474432
Q3 1960-Q2 19610.730.222212
Q1 1970-Q4 19700.140.011113
Q1 1974-Q1 19752.750.543324
Q2 1980-Q3 19804.322.285531
Q4 1981-Q4 19822.250.433224
Q4 1990-Q1 19912.621.364421
Q2 2001-Q4 2001 (?)0.330.111112

Rated according to a decline per quarter.

Grouped according to a total cumulative real decline during a recession:

Rating12345
Cumulative decline, percent0-0.10.1-0.50.5-1.01.0-1.51.5

Grouped according to a cumulative real decline: 1- light; 2 - average; 3 - severe.

Rated according to a decline per quarter.

Grouped according to a total cumulative real decline during a recession:

Rating12345
Cumulative decline, percent0-0.10.1-0.50.5-1.01.0-1.51.5

Grouped according to a cumulative real decline: 1- light; 2 - average; 3 - severe.

19. The SRI is then used as a dependent variable in an ordered probit equation, which includes the CVI and other leading indicators that were used in the previous section in predicting the probability of recession as explanatory variables. The estimation results indicate that an increase in the CVI is associated with an increase in the probability of a more severe recession three to six quarters ahead (Table 5). When recessions are ranked according to their length (as opposed to depth), the estimation results indicate that a higher CVI also raises the probability of a longer recession (Table 5, bottom panel).

Table 5.United States: Predicting the Severity of Recessions, Ordered Probit Estimations 1/
k = 3k = 4k = 6
CoefficientStandard ErrorCoefficientStandard ErrorCoefficientStandard Error
SRI, Rating: Individual
C11.248**0.6651.939*0.7311.598*0.696
C20.1220.2230.1600.2550.1700.293
C30.0150.0140.0220.0170.0000.016
C4-0.0000.0010.001*0.0010.003*0.001
C5-0.447*0.098-0.489*0.098-0.571*0.091
C6-4.6303.324-2.3592.7153.5953.523
Pseudo R20.2820.2710.236
SRI, Rating: Group No. 1
C11.323**0.6551.970*0.7281.798*0.673
C20.0840.2230.1420.2580.1820.290
C30.0160.0140.0220.0170.0000.016
C40.0000.0010.001*0.0010.003*0.001
C5-0.440*0.097-0.482*0.098-0.566*0.089
C6-4.4853.278-2.4592.7093.2303.531
Pseudo R20.2860.2710.237
SRI, Rating: Group No. 2
C11.904*0.7742.576*0.8332.223*0.733
C20.0800.2450.1500.2860.1570.313
C30.0160.0140.0260.015-0.0020.017
C40.0000.0010.001**0.0010.003*0.001
C5-0.487*0.105-0.536*0.113-0.605*0.108
C6-4.6863.401-1.8132.7202.7783.670
Pseudo R20.3650.3740.295
SRI, Rating: Recession Length
C13.040*0.9324.516*0.9782.7201.017
C20.2450.2950.691*0.2950.1510.375
C30.054*0.0170.056*0.020-0.0010.019
C40.0000.0010.0010.0010.0030.001
C5-0.492*0.125-0.652*0.152-0.6940.145
C6-5.7954.181-2.7023.5203.6123.767
Pseudo R20.4160.4030.308
* Coefficient significant at a 1 percent level; ** at a 5 percent level; *** at a 10 percent level

The model estimatedis: Prob (Rt+k = 1) = N(c0 + c1 CVIt + c2 AVGHRSt + c3 VENDORt + c4 HOUSINGt + c5 TRY_STRt + c6 SPRETt), where Rt+k is the NBER recession index, M is one of the Severity of Recession Index (SRI) modifications from Table 4; the CVIt, is the Corporate Vulnerability Index, AVGHRSt, is average weekly hours worked, VENDORt, is the vendor performance index, HOUSINGt is housing starts, TRY_STRt is the Treasury yield curve, and SPRETt is stock returns N(.) is a cumulative normal distribution function, k is a forecasting horizon, in quarters.

* Coefficient significant at a 1 percent level; ** at a 5 percent level; *** at a 10 percent level

The model estimatedis: Prob (Rt+k = 1) = N(c0 + c1 CVIt + c2 AVGHRSt + c3 VENDORt + c4 HOUSINGt + c5 TRY_STRt + c6 SPRETt), where Rt+k is the NBER recession index, M is one of the Severity of Recession Index (SRI) modifications from Table 4; the CVIt, is the Corporate Vulnerability Index, AVGHRSt, is average weekly hours worked, VENDORt, is the vendor performance index, HOUSINGt is housing starts, TRY_STRt is the Treasury yield curve, and SPRETt is stock returns N(.) is a cumulative normal distribution function, k is a forecasting horizon, in quarters.

List of References

Prepared by Iryna Ivaschenko.

The reasons for this trend are not well understood. However, corporate finance theory argues that firms generally prefer issuing debt to equity because debt reduces information asymmetry and thus reduces firms’borrowing costs. See Myers and Majluf (1984). However, some observers suggest that corporations increasingly substituted debt for equity in order to boost stock prices. See, for example, Cookson (2001).

Influential work by Merton (1974) suggests balance sheet leverage–defined as a ratio of debt to the firm’s value– as an indicator of a firm’s financial vulnerability. The true value of a firm is usually unknown and is approximated by firms’ assets or a sum of debt and equity.

Standard measures of debt derived from the balance-sheet data understate the true amount of leverage in the economy as they do not fully account for off-balance-sheet liabilities. Nevertheless, these measures, calculated from the officially reported balance-sheet data, have proved to be useful even when measuring the performance of such major derivative players as Enron and LTCM.

Gross debt payments are calculated for each component of aggregate corporate liabilities, using appropriate interest rates. Corporate profits are adjusted for inventory valuation and capital consumption.

In order to combine the flow value of the debt-service burden with the stock value of balance-sheet leverage the debt burden is converted into a stock using a present value technique. Alternatively, the debt-service burden can be rescaled so that its mean/standard deviation ratio is comparable to that of balance-sheet leverage. See Anderson and Sundaresan (2000).

See, for example, Merton (1974). There are a number of other theories which model the costs of external financing as a function of a firm’s balance sheet. See, for example, Kiyotaki and Moore (1997); and Carlstrom and Fuerst (1997). In addition, high leverage may lead to credit rationing that limits the sources of funding for corporations, depressing investment and output. However, with the development of alternative sources of funding for corporations, full-blown credit rationing has become less of an issue, at least for the corporate sector as a whole. Indeed, while some segments of the economy– such as high-yield bond issuers in late 2000– felt credit squeezes in the recent times, overall, the corporate sector has appeared to retain access to funding.

See, for example, Hoshi, Kashyap, and Scharfstein (1991), Kashyap, Lamont, and Stein (1994), and Sharpe (1994). Bernanke and Gertler (1986, 1990) also argue that the strength of balance sheets determines the quality of investment projects undertaken.

In 2001, the recovery rate fell to a 20-year low of 21 percent. See Moody’s (2002).

See Anderson and Sundaresan (1996) and Anderson, Sundaresan, and Tychon (1996) who derive the default barrier in a game-theoretic framework of a bankruptcy process; or Mella-Barral and Perraudin (1997), who derive the default barrier along the lines of the real options theory of investment that treats the liquidation process as an option.

For a more detailed discussion, see Ivaschenko (2002).

This approach to predicting the probability of recession follows Estrella and Hardovelis (1991), Stock and Watson (1993), Estrella and Mishkin (1997), Dueker (1997), and Dotsey (1998). The recession index equals one if the economy is in a recession– as defined by the NBER—during the given quarter, and zero otherwise.

The choice of variables was guided by their proven ability to predict U.S. business cycles.

The estimation results are uniformly insignificant and are not reported here for the sake of brevity, but are available from the author.

The choice of the model was guided by the following considerations. First, modeling aggregate corporate debt as a perpetuity with time-varying coupon payments seems to be the most natural as individual firms continuously roll over their existing debts or issue new ones. Second, the AST model better reflects bond market realities in that it allows for costly bankruptcy, deviations from absolute claim priority, strategic debt service, and less-than-complete recovery of liability claims. The point at which a firm defaults—the default barrier—is not given exogenously but is derived as a result of the strategic interaction between creditors and shareholders. Finally, the theoretical bond prices produced by the model fit actual bond price data better than those of other structural models. See Anderson and Sundaresan (2000) for details.

PDt=(1/(LEVtγtθt(11/γt)+BCOSTtθt(11/γt)))γt When PDt is the probability of the firm’s defaulting on its debt obligations, LEVt is total leverage, rt is a risk-free interest rate, BCOST, is bankruptcy costs, θ is a recovery rate, and yt is a nonlinear function of the risk-free interest rate, rt dividend payout rate, BBETA, and volatility of the firm value, σt.

The choice of the bond index is guided by the fact that an average rating of a company listed in S&P 500 composite index is Baa. Leverage is approximated by total leverage, described above. The risk-free interest rate is approximated by the yield on the long maturity composite Treasury bond index, and volatility of the firm value is approximated by equity volatility multiplied by a constant scaling factor. The bankruptcy costs, the recovery value, and the dividend payout rate are expressed as a percentage of the firm’s value and are treated as constant model parameters. Together with the equity-scaling factor, they are inferred from the estimation.

The model is estimated in real terms as a robustness check, since in periods of high inflation firms tend to switch to different accounting methods. Moreover, fixed assets tend to be understated and long-term debt levels overstated. Since all balance sheet and flow data are estimated as ratios, only interest rates are adjusted for inflation. Inflation was proxied by the chain-type GDP deflator. Expected inflation rates are estimated by fitting an ARIMA (7,1,3) model to quarterly inflation data over 1947Q2 to 2001Q4.

Sec Estrella and Mishkin (1997), Dotsey (1998), and Stock and Watson (2000) for a detailed discussion.

The evidence of improved corporate sector health is reflected in a decline in the corporate default rate (to 3.9 percent) in December 2001—the first decline since 1999. See Moody’s (2002).

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