with the corresponding growth rate for the Compustat’s entire nonfarm nonfinancial
sector. The two series are highly correlated and exhibit virtually identical business
cycle dynamics. The lower panel compares the sales-weighted median leverage of firms
in our sample with the corresponding statistic for all nonfinancial firms in Compustat
as well as with a measure of long-term leverage in the nonfinancial sector obtained
from the Flow of Funds accounts.17 The three measures paint a very similar picture
of the state of corporate balance sheets over time. Clearly evident is the sharp run-up
in corporate leverage during the late 1980s, followed by a steady decline over most
of the past decade. Leverage in the nonfinancial corporate sector bottomed out at
a very low level in the late 1990s and then rose noticeably after the bursting of the
stock market bubble in the spring of 2000.
Credit spreads in our sample are also representative of the spreads in the corporate
bond market as a whole, when controlling for the maturity of bonds outstanding and
the credit quality of issuers. As shown in the upper panel of Figure 5, the (weighted)
median credit spread for BBB-rated debt with maturity of 7 to 10 years obtained
from our sample provides a very close match to the (weighted) median spread of
all nonfinancial bond issues in the Merrill lynch database. (This result holds for
other rating categories and maturity buckets.) Finally, the lower panel shows that
the evolution of the (weighted) median expected one-year-ahead default frequency
for the firms in our sample tracks very closely the (weighted) median EDF of all
nonfinancial firms in the MKMV database.
For our purposes, the two key relationships implied by the BGG framework are
the leverage-spread and the leverage-default-probability schedules. These two un-
conditional relationships are plotted in Figure 6 using the firm-level data.18 Despite
enormous variation, there is a clearly discernable pattern between leverage and credit
spreads (top panel) and leverage and expected probabilities of default (bottom panel).
Moreover, the contours of these relationships are broadly similar to those implied by
the BGG model in Figures 2-3, in that a higher leverage is associated with a wider
credit spread and a higher expected probability of defaults.
17The sales-weighted median leverage in period t identifies a firm in the distribution of leverage
such that firms with higher (or lower) leverage in period t account for one-half of sample liabilities.
18 To minimize the visual effect of outliers, we drop in each quarter firms with leverage ratios
above the 97.5th percentile and below the 97.5th percentile, firms with credit spreads ab ove the
97.5th percentile, and firms with EDFs at exactly 20%.
18