Exploring the Node Importance and Its Influencing Factors in the Railway Freight Transportation Network in China
Table 6
Results of the determinants of Hub and PageRank using the PCSE and SCCSE estimators.
Dependent variable
Hub
PageRank
Explanatory variable
PCSE
SCCSE
PCSE
SCCSE
PopDen
0.0201∗∗∗
0.0201∗∗
0.0027∗∗
0.0027∗
(0.0074)
(0.0088)
(0.0015)
(0.0021)
GDP
-0.0631∗∗∗
-0.0631∗∗
-0.0011
-0.0011
(0.0188)
(0.0201)
(0.0024)
(0.0046)
HighwayDen
-0.0127
-0.0127
-0.0066∗∗∗
-0.0066∗∗
(0.0094)
(0.0096)
(0.0024)
(0.0028)
Fixedasset
0.0551∗∗
0.0551∗
0.0120∗∗∗
0.0120∗
(0.0221)
(0.0249)
(0.003)
(0.0055)
RFC
-0.2917∗∗∗
-0.2917∗∗∗
-0.0713∗∗∗
-0.0713∗∗∗
(0.0288)
(0.0244)
(0.0039)
(0.0041)
Longitude
-0.0040∗∗∗
-0.0040∗∗∗
-0.0002∗∗∗
-0.0002∗∗∗
(0.0001)
(0.0002)
(0.0000)
(0.0000)
Latitude
-0.0009∗∗∗
-0.0009∗∗∗
-0.0006∗∗∗
-0.0006∗∗∗
(0.0003)
(0.0003)
(0.0001)
(0.0001)
Coastalregion
-0.0410∗∗∗
-0.0410∗∗∗
-0.0038∗∗∗
-0.0038∗∗
(0.003)
(0.0023)
(0.001)
(0.0013)
YEZ
-0.0510∗∗∗
-0.0510∗∗∗
-0.0007
-0.0007
(0.003)
(0.0022)
(0.0011)
(0.0012)
SREB
-0.0579∗∗∗
-0.0579∗∗∗
0.0015
0.0015
(0.0021)
(0.0021)
(0.0018)
(0.0028)
Resource
0.1129
0.1129∗∗∗
-0.0028∗∗∗
-0.0028∗∗
(0.0019)
(0.0032)
(0.0011)
(0.0012)
Crisis
0.0042
0.0042
0.0039∗∗
0.0039∗
(0.0056)
(0.0058)
(0.0028)
(0.0031)
Newnormal
-0.006
-0.006
-0.0088∗∗∗
-0.0088∗∗∗
(0.0063)
(0.0042)
(0.0028)
(0.0022)
Constant
0.0788
0.0788
-0.1776∗∗∗
-0.1776∗∗∗
(0.0554)
(0.0957)
(0.0089)
(0.0114)
Wald test
44430.65
44330.61
50333.31
74668.83
(0.0000)
(0.0000)
(0.0000)
(0.0000)
N
341
341
341
341
Note: (1) The standard errors in parentheses (except Wald test) are statistically significant at the 1% (∗∗∗), 5% (∗∗), and 10% (∗) levels. (2) In all cases, the Wald test (the value in parentheses is the p value) rejects the null hypothesis that the explanatory variables as well as the dummy variables are jointly equal to zero.
