Table 2 Estimated model: generalized regression for industrial distribution across Chinese regions from 1995 to 2014

MSz

2.140947 (.287356)^*

2.765489 (.1024622)^*

2.368863 (.1770392)^*

1.454354 (.0839593)^*

1.34885 (.1577469)^*

.4577651 (.1161277)^*

.4369391 (.214675)^*

CAd

- 1.435096 (.8828371)^**

.0039425 (.1123031)^**

-.7632607 (.1699287)^*

.9912443 (.4243256)^*

.9714682 (.2596577)^*

.2322001 (.0663806)^*

-.1224958 (.4769336)^***

InterTC

.7003798 (.174558)^*

.002214 (.0209503)^***

-.0093017 (.0277309)^***

.0883141 (.0210309)^*

.1850768 (.0388763)^*

.0075077 (.0158179)^***

.0313649 (.0704416)^***

IntraTC

.1799575 (.1157521)^**

.1672521 (.0511079)^*

-.3021995 (.0924854)^*

.1003722 (.0383487)^*

.089857 (.0492795)^*

.6906011 (.0447454)^*

.7657295 (.0867046)^*

Constant

.0172112 (.0219723)^***

-.0213503 (.0042008)^*

.0337041 (.0059889)^*

-.0314977 (.0106556)^-

-.0306712 (.0073523)^*

-.008505 (.0022426)^*

.0045645 (.010956)^***

Number of provinces

4

6

5

3

4

5

3

Number of observations

80

120

100

60

80

100

60

Wald chi-square (4)

220.85

1766.83

382.81

13980.19

692.28

2835.86

598.30

Log likelihood

284.5811

416.0149

368.3247

261.9177

342.9367

523.2777

249.453