Civil Engineering Reference
In-Depth Information
Tabl e 3
Nonparametric variable detection of national data
2 standard
deviations
Variable
Production
Region
Policy
Institution
Complex
kty
0.03144
0.02859
0.03611
0.03207
0.05408
0.60655
tech
0.32101
0.45622
4083172*
18840362*
5559999*
4.87432
year
0.53816
0.52963
0.51647
0.25312
0.75155
-
region
-
0.22078
0.50907
0.00744
0.51346
-
fdi
-
-
0.00066
-
4708.709*
0.00929
trd
-
-
0.01224
-
0.00844
0.10363
sir
-
-
0.01774
-
0.02719
0.15577
tir
-
-
0.00928
-
0.03471
0.13892
dev
-
-
-
1530.480
1250.829
24413.41
goi
-
-
-
0.00465
0.00880
0.07283
goe
-
-
-
0.12027
0.03076
0.12466
soe
-
-
-
0.03236
0.05394
0.18561
tax
-
-
-
0.00849
0.01076
0.06896
Tab le
3
is the bandwidths we calculate from LCLS. The last column of the table
gives a complex perspective which incorporates all of the variables.
The provincial complex perspective gives us a hint: the variables we consider
except technological progress and FDI are the determinant, which is in accordance
with the results achieve using the national data in some extent. From national
data, FDI is not the determinant; the ratio capital to yield, trade, tertiary industry,
and economic development are the determinants. But technological progress is not
the determinant using the provincial data, which is an exception, we consider the
difference in the next part.
While LLLS method, from provincial complex perspective, finds the ratio capital
to yield, government revenue and expenditure and secondary and tertiary industry
have an influence in a linear way, and trade, economic development, the scale of
state-owned enterprises, and tax burden are nonlinear.
3.3
Solution to Problems
Question 1: Our empirical analysis finds technological progress is not the deter-
minant using the provincial panel data. So we give a possible explanation:
Luo
and Zhang
(
2009
) find it is not significant, but
Xiao and Zhou
(
2010
) find it is
significant and linear; we find the difference stems from the different data they
adopt, using provincial data or national data may have different empirical results.
Question 2: Our empirical results find, when we consider FDI, trade, and sec-
ondary and tertiary industry as the policy factors, the influence of trade (import
and output) is nonlinear, but not linear. Referring to complex factors, the
influence of trade is linear, but not nonlinear. The contradictory results between
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