A Structural Model of Human Capital and Leverage - Duke ...

of displaced workers, with the consensus being that they are significant and long-lasting. Figure 1 is taken
from Couch and Placzek (2010), which contains an excellent summary of the studies in this area, and shows
earnings losses of a sample of employees in Connecticut who were separated in mass layoffs starting in 1999.
The magnitude and duration of the losses in this study are consistent with the findings of similar studies
using different data sets, sample periods, and geographic regions. The average quarterly earnings in their
sample is $13,288. The figure shows a spike at the time of separation which is driven by lump-sum severance
payments to a subset of the displaced workers. Following separation, workers suffer an immediate loss of
around 35%. Two years later earnings remain 15% below pre-separation levels, and they remain depressed
through six years, when the sample ends.
Figure 1 presents evidence that workers who are laid off experience significant economic consequences.
This constitutes a significant cost of financial distress. Firms whose production technology is relatively labor
intensive are more heavily exposed to this cost of financial distress, and will therefore respond by using less
leverage. Figure 2 plots the mean market leverage of Compustat firms sorted into deciles of labor intensity.
Labor intensity is measured as the ratio of total wage bill to total assets. 2 The figure shows a striking
univariate relationship between leverage and labor intensity. Firms in the lowest decile of labor intensity
have an average of 42% market leverage versus 16% for firms in the highest decile, a difference of a factor of
2.6, and leverage is monotonically decreasing in labor intensity. Figure 3 performs the same exercise using
book leverage in place of market leverage. The pattern for book leverage is nearly identical to that for market
leverage.
Figures 2 and 3 show that the univariate relationship between leverage and labor intensity is significant.
However, labor intensity is likely to be correlated with a number of other determinants of capital structure.
Table 1 reports multivariate results for regressions of market leverage on deciles of labor intensity and other
well-known predictors of capital structure (Rajan and Zingales 1995). All regressions include year fixed effects
and cluster standard errors at the firm level. Each dependent variable is measured in deciles to account for
nonlinearities in the relationships and to facilitate the comparison of coefficients. Table 1 shows that labor
intensity is a significant predictor of leverage, on par with previously recognized predictors in terms of both
the magnitude of its coefficient and its explanatory power. Moving up one decile of labor intensity results in
a drop in market leverage of 2.8 percentage points. For comparison, the largest coefficient in the regression
2 Measuring labor intensity using the wage bill puts severe restrictions on the data. Reporting labor expenses is voluntary,
and is reported consistently by roughly 10% of Compustat firms. Ballester, Livnat, and Sinha (2001) find that disclosure is
more common for large firms, labor-intensive firms, and firms in regulated industries. I also find that firms who report labor
expenses have slightly higher leverage on average.
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