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Kim and Sherman
(1998) indicate that firms increase investment in liquid assets in response to increase in the
cost of external financing, the variance of future cash flows or the return on future investment opportunities.4
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Harford (1999)
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argues that corporations with excessive cash holdings
are less likely to be takeover targets. Almeida, Campello and Weisbach (2004) develop a
liquidity demand model where firms have access to investment opportunities but cannot
finance them.
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homogeneously in response to increases in macroeconomic uncertainty.6However, their model implies predictable variations in thecrosssectional distributionof corporate cash holdings and does not make predictions about the individual firm’s optimallevel
of liquidity. Furthermore, they do not consider the impact of idiosyncratic uncertainty on
the firm’s cash holdings.
In this paper, we complement
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Baum et al. (2006)
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by investigating the impact of macroeconomic uncertainty as well as idiosyncratic uncertainty on the cash holding behavior of
nonfinancial firms. We provide a theoretical and empirical investigation of the firm’s deci4See also Opler, Pinkowitz, Stulz and Williamson (1999), Mills, Morling and Tease (1994) and Bruinshoofd
(2003).
5See also Gertler and Gilchrist (1994) on the effects of monetary pol
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In this paper, we complement Baum et al. (2006) by investigating the impact of macroeconomic uncertainty as well as idiosyncratic uncertainty on the cash holding behavior of
nonfinancial firms. We provide a theoretical and empirical investigation of the firm’s deci4See also Opler, Pinkowitz, Stulz and Williamson (1999), Mills, Morling and Tease (1994) and
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Bruinshoofd (2003).
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5See also Gertler and Gilchrist (1994) on the effects of monetary policy on financial policies regarding
the use of debt.
6In a recent paper Bo and Lensink (2005) suggests that presence of uncertainty factors changes the
structural parameters of the Qmodel of investment.
sion to hold liquid assets.
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ˆst=γ1LIt+γ2E[ˆR]t+1(13)
14We proxy the firm’s capital stockKwith total assets,TA.
14
whereLItis the index of leading indicators: a measure of overall economic health.E[R]t+1
is the firm’s expected return on investment. Both a stronger economic environment and a
higher expected return on investment increase the firm’s probability of acquiring sufficient
credit if threatened with bankruptcy (see
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Altman (1968), Liu (2004)).
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Substituting the parameterized expressions into equation (6) yields
Cˆ=α1ζ1ˆCt−1+α1ζ2ˆIt−1+ζ3ˆψt−1+ (α2+α5γ2)θ
(̂S
TA
)
t+1
+α3β21ˆτ2t
+α3β22ˆ2t+α4δTBt+α5γ1LIt+ (α2+α5γ2)(κ+ω+ν).
After normalization of cash holdings, debt and investment by total assets we derive our
econometric model specification for firmiat timet:
(̂Cit
TAit
)
=φ0+φ1
(̂Cit−1
TAit−1
)
+φ2
(̂Iit−1
TAit−1
)
+φ3
(̂Sit+1
TAit+1
)
+(
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For instance, Bo and Lensink
(2005) use three measures: stock price volatility, estimated as the difference between the
highest and the lowest stock price normalized by the lowest price; volatility of sales measured by the coefficient of variation of sales over a seven–year window; and the volatility of
number of employees estimated similarly to volatility of sales.
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Bo (2002)
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employs a slightly
different approach, setting up the forecasting AR(1) equation for the underlying uncertainty
variable driven by sales and interest rates. The unpredictable part of the fluctuations, the
estimated residuals, are obtained from that equation and their threeyear moving average
standard deviation is computed.
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Bo (2002) employs a slightly
different approach, setting up the forecasting AR(1) equation for the underlying uncertainty
variable driven by sales and interest rates. The unpredictable part of the fluctuations, the
estimated residuals, are obtained from that equation and their threeyear moving average
standard deviation is computed.
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Kalckreuth (2000)
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uses cost and sales uncertainty measures, regressing operating costs on sales. The threemonth aggregated orthogonal residuals
from that regression are used as uncertainty measures.
In contrast to the studies cited above, we proxy the idiosyncratic uncertainty by computing the the standard deviation of the closing price for the firm’s shares over the last nine
months.
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only
manufacturing sector firms we obtain on average 700 firms’ quarterly characteristics.15
Descriptive statistics for the quarterly means of cashtoasset ratios along with investment and sales to asset ratios andψare presented in Table 3. From the means of the sample
we see that firms hold about 10 percent of their total assets in cash. This amount is sizable
and similar to that reported in
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Baum et al. (2006).
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The empirical literature investigating firms’ cashholding behavior has identified that
firmspecific characteristics play an important role.16We might expect that a group of
firms with similar characteristics (e.g., those firms with high levels of leverage) might behave
similarly, and quite differently from those with differing characteristics.
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Small firms also have a
much larger coefficient for idiosyncratic uncertainty. The greater sensitivity of small firms
could be explained by the fact that smaller firms are more likely to be financially constrained.
As
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Almeida et al. (2004)
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indicate, financially unconstrained firms have no precautionary
motive to hold cash; their cash holding policies are indeterminate. In contrast, for financially
constrained firms, any change in the level of uncertainty that affects managers’ ability to
predict cash flows should cause them to alter their demand for liquidity.
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When the macroeconomic environment is less predictable, or when idiosyncratic risk is higher, companies become more
cautious and increase their liquidity ratio.
Our results should be considered in conjunction with those of
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Baum et al. (2006)
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who
predict that during periods of higher uncertainty firms behave more similarly in terms of
their cashtoasset ratios. Taken together, these studies allow us to conjecture that as
either macroeconomic or idiosyncratic uncertainty increases the total amount of cash held
by nonfinancial firms will increase significantly, with negative effects on the economy.
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