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顧客與供應商關係與成本結構
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Due to lack of authoritative guidance for preparing income statements, the
component of SG&A in one company could be assigned to cost of goods sold or other
expenses in another company (Subramanian and Weidenmier, 2003), thus we also
investigate the stickiness of cost of goods sold (COGS) and total operating cost (OC) and
report the results in Table 4 and Table 5 respectively.
Column (1) of Table 4 reports the baseline results of Anderson et al. (2003) model
with the extension of our variable of interest (
CC
). The coefficient on ∆
ln(Sale)
is 1.01948
(
t-
statistic = 219.16), positively significant at the 0.1% level. COGS by a manufacturing
firm includes direct material, direct labor, and allocated overhead that needed to produce
goods for sale. As expected, change in cost of goods sold (COGS) are highly correlated to
change in sales revenue.
The estimated coefficient, 1.01948 indicates that COGS increase almost 1 % per 1%
increase in sales revenue. The coefficient on ∆
ln(Sale)*Dec
is -0.04348 (
t
-statistic =
-4.52), significantly negative at the 0.1% level, which is consistent with the notion that
COGS is sticky. The combine value of these two coefficients on ∆ln
(Sale)
and
∆ln
(Sale)
*Dec is 0.976, indicating that COGS decreases only 0.976% per 1% decrease in
sales revenue. When customer concentration (
CC
) is included in the model, the coefficient
on our variable of interest,
CC*∆ln(Sale)*Dec
, is 0.29744 (
t
-statistic = 9.43), significantly
positive at the 0.1% level. The result suggests that for companies with more concentrated
customers, COGS is less sticky when sales decrease. Column (3) of Table 4 reports the
results with full control variables and indicator variables for industry fixed effects. The
result reflects a similar pattern: Specifically, the coefficient on
∆ln(Sale)*Dec
is -0.25001
(
t
-statistic = -17.41), significantly negative at the 0.1% level, which is consistent with the
presence of cost stickiness. The coefficient on our variable of interest,
CC*∆ln(Sale)*Dec
,
is 0.61429 (
t
-statistic = 6.87), significantly positive at the 0.1% level. The result indicates
that COGS cost stickiness decrease with the level of customer concentration even after
controlling industry effects.