In order to investigate the empirical importance of which industry offshores which
parts of production (what is of special interest in this contribution), the magnitude and
development of the VS index are also calculated on more disaggregated industry levels.
The numbers are presented in Table 1.
|
Table 1: Level and Development of Offshoring in Germany | ||
|
low skill int. industries |
high skill int. industries | |
|
low skill parts high skill parts |
low skill parts high skill parts | |
|
1991 |
6% 3% |
2% 8% |
|
1995 |
6% 3% |
2% 9% |
|
2000 |
6% 4% |
2% 12% |
|
1991 - |
2000 7% 38% |
0% 59% |
As the table shows, in relative low skill intensive industries, the average level of
offshoring high skill intensive parts reaches about one half (1991 and 1995) or two third
(2000) of the level of relocating low skill intensive production blocks. Considering the
offshoring dynamic, there is a much stronger increase in relocating high skill inten-
sive production parts (38 percent) compared to relocating low skill intensive parts (7
percent). In relative high skill intensive industries, by contrast, the average level of off-
shoring high skill intensive produciton parts is much higher then its low skill intensive
counterparts. Despite the relative high level, the increase of offshoring relative high
skill intensive production parts is much more pronounced as well.
Empirical Methodology and Results
In order to assess the implications of offshoring on the industries skill ratio, we estimate
(H/L)jt = β0 + β1ωjt(l) + β2Qjt(l) + β3VS jt(l) + t + jt (2)
for different levels of industry aggregation. The high skill labor ratio H/L of industry
j is regressed on a constant, relative high skill wages ωjt ≡ wwHj^, the industry’s output
Q, offshoring measured with the VS index, and the variable t capturing the time trend.
is a typical error term. Since there could be a possible endogeneity problem (not
only with respect to relative wages), we ran several Durbin - Wu - Hausman tests (as
suggested in Davidson and McKinnnon, 1993) to proof if possible endogeneity could
significantly bias the results. In order to secure pure exogenous variables on the right
hand side, we decided to perform an instrumental variable regression and instrument
all the exogenous variables with its lagged components (l).
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