高铁开通对县级单元产业结构的影响————以长三角地区为例

doi:10.13249/j.cnki.sgs.2022.11.006

Abstract

Abstract:

Along with the rapid construction and extent of the high-speed railway network, almost all prefecture-level cities have enjoyed high-speed railway services, especially in the southeast coastal region. Therefore, the main body of high-speed railway construction has been transferred from connecting prefecture-level units to county-level units. However, current studies have rarely paid attention to the impact of the high-speed railway on county-level units. The purpose of this article is to explore what changes will take place in the industrial structure of county-level units after the opening of the high-speed railway and its mechanism. Taking the Yangtze River Delta as an example, it was evident that the sequence of high-speed rail opening and the evolution process of industrial structure in this region have significant synchronization. With the usage of socio-economic panel data of all county-level units in this region from 2000 to 2017, this article measured the impact of high-speed railways on the industrial structure through the time-varying difference-in-differences model and employed sub-grouping, threshold effect and mediation model to explore the mechanism of high-speed rail effect. The results of the study are listed as follows: 1) The opening of the high-speed railway will promote upgrading the industrial structure of county-level units, which is composed of the dispersion of the secondary industry and the aggregation of the tertiary industry. 2) Population size has partial mediating effect on the high-speed rail effect, but there is no threshold mutation within the population size range of the counties and county-level cities in the Yangtze River Delta. 3) The secondary and tertiary industries have different time-laggings in the effect of the opening of the high-speed railway, resulting in two window periods for the transformation of the county-level unit industrial structure. When the county-level units apply for the high-speed railway project, it is necessary to judge their industrial characteristics prudently. And they should follow the law of industrial evolution after opening the high-speed rail and formulate targeted policies to encourage or hedge.

Key words: high-speed railway, county-level units, industrial structure, time-varying difference-in-differences, the Yangtze River Delta

CLC Number:

F532.8

Shi Dehao, Yu Tao, Wang Lei. The Impact of High-speed Railway on the Industrial Structure of County-level Units: Taking the Yangtze River Delta as an Example[J].SCIENTIA GEOGRAPHICA SINICA, 2022, 42(11): 1912-1922.

Figures/Tables 8

Fig. 1

Table 1

Table 2

The impact of the opening of HSR on the industrial structure of county-level units

变量	因变量：产业结构
变量	1	2	3	4	5	6	7 大城市组	8 中等城市组	9 小城市组
注：列1~6是长三角地区所有县级单元逐步回归结果；列7~9分别是人口规模大、中等、小城市组县级单元的回归结果；^*、^、^* 分别表示在1%，5%和10%水平下显著；括号内数值为t值；变量解释见表1；空白项为无此项。
HSR	0.132^***	0.086^***	0.104^***	0.164^***	0.114^***	0.101^***	0.265^***	0.146^***	0.028
	(7.56)	(4.78)	(5.93)	(8.17)	(5.43)	(4.81)	(6.82)	(5.59)	(0.82)
Treat	−0.077	−0.039	0.027	0.018	0.154^**	0.159^**	2.721^***	0.782^***	0.342^***
	(−1.43)	(−0.69)	(0.48)	(0.30)	(2.25)	(2.43)	(10.14)	(7.77)	(2.91)
T	−0.025	−0.009	−0.025	0.080^***	0.053^***	−0.045^**	0.184^***	−0.069^**	−0.015
	(−1.36)	(−0.50)	(−1.38)	(−3.82)	(−2.68)	(−2.25)	(−4.85)	(−2.38)	(−0.58)
pGDP		0.309^***	0.380^***	0.519^***	0.497^***	0.440^***	0.302^***	−0.375^***	−0.657^***
		(−11.89)	(−12.29)	(−14.35)	(−13.79)	(−10.70)	(−3.69)	(−7.97)	(−5.06)
Pop			0.399^***	0.370^***	0.635^***	0.534^***	0.055	−0.443^*	−1.653^***
			(−5.46)	(−4.17)	(−5.84)	(−4.74)	(0.38)	(−1.84)	(−3.07)
Edu				−0.028^**	−0.023	0.038	0.101**	−0.049	0.100
				(−1.97)	(−0.89)	(1.25)	(2.03)	(−1.25)	(1.43)
FAI					0.148^***	0.130^***	0.117^***	−0.092^***	−0.129^***
					(−15.82)	(−11.21)	(−6.39)	(−7.68)	(−4.28)
PFE						0.199^***	0.271^***	−0.266^***	−0.064
						(−4.31)	(−4.70)	(−5.48)	(−0.43)
常数项	1.012^***	3.693^***	4.875^***	6.043^***	6.394^***	5.871^***	3.479^***	4.934^***	9.319^***
	(26.45)	(16.27)	(14.29)	(15.50)	(15.09)	(12.61)	(4.24)	(7.03)	(5.22)
个体固定	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
时间固定	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
样本量	3553	3553	3553	3553	3553	3553	1368	1242	972
R²	0.6082	0.6334	0.637	0.6652	0.7158	0.7191	0.7291	0.724	0.7809

Table 2

Table 3

The impact of the opening of HSR on the secondary industry of county-level units

变量	因变量：第二产业产值(Ind2)
变量	1	2	3	4	5	6	7 大城市组	8 中等城市组	9 小城市组
注：列1~9解释见表2；^*、^、^* 分别表示在1%，5%和10%水平下显著；括号内数值为t值；变量解释见表1；空白项为无此项。
HSR	−0.181^***	0.215^***	−0.100^***	−0.100^***	−0.067^***	−0.105^***	−0.215^***	−0.105^***	−0.004
	(−8.80)	(−9.43)	(−8.94)	(−8.94)	(−5.88)	(−8.72)	(−7.01)	(−5.90)	(−0.20)
Treat	0.514^***	0.459^***	−0.006	−0.085^*	−0.320^***	−0.387^***	0.425^***	0.413^***	−1.000^***
	(11.6)	(10.28)	(−0.18)	(−1.81)	(−6.33)	(−7.2)	(4.44)	(3.78)	(−5.04)
T	0.021	0.044^**	0.040^***	0.040^***	0.020^*	0.052^***	0.165^***	0.063^***	−0.003
	(1.09)	(2.15)	(3.50)	(3.50)	(1.84)	(4.54)	(5.87)	(3.08)	(−0.19)
Pop		0.401^***	2.334^***	2.334^***	2.434^***	2.502^***	2.047^***	2.704^***	3.439^***
		(3.50)	(49.81)	(49.81)	(48.15)	(37.11)	(19.61)	(13.81)	(12.60)
pGDP			1.332^***	1.332^***	1.292^***	1.398^***	1.301^***	1.444^***	1.619^***
			(64.35)	(64.35)	(63.26)	(57.12)	(24.92)	(42.80)	(28.39)
Admin				0.079^*	0.241^***	0.301^***	0.545^***	0.36^***	0.721^***
				(1.87)	(5.17)	(6.19)	(5.74)	(5.56)	(4.89)
FAI					0.091^***	0.104^***	0.128^***	0.088^***	0.092^***
					(18.04)	(20.98)	(11.7)	(10.88)	(11.82)
Edu						−0.012	−0.014	0.069^**	−0.059^**
						(−0.69)	(−0.46)	(2.28)	(−2.03)
常数项	1.704^***	1.133^***	13.136^***	13.453^***	14.000^***	15.302^***	14.897^***	16.422^***	20.251^***
	(39.05)	(6.69)	(−58.76)	(−38.39)	(−38.5)	(−37.81)	(−16.79)	(−21.54)	(−14.34)
个体固定	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
时间固定	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
样本量	3553	3553	3553	3553	3553	3553	1368	1242	972
R²	0.9737	0.9847	0.9920	0.9920	0.9925	0.9929	0.9912	0.9903	0.9926

Table 3

Table 4

Table 5

Table 6

Table 7

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变量种类	变量	符号	定义	均值	标准差	最小值	最大值
因变量	第二产业	Ind2/100万元	第二产业的产值	218.09	580.86	0.52	9251.40
	第三产业	Ind3/100万元	第三产业的产值	208.16	884.67	0.85	20783.47
	产业结构	IndR	以第三产业和第二产业的产值之比来度量产业结构	0.84	0.35	0.36	4.49
虚拟变量	县级单元是否开通高铁	Treat	有无差异：开通高铁的单元为1，否则为0	0.41	0.49	0.00	1.00
	具体年份是否开通高铁	T	前后差异：开通高铁之后为1，开通高铁之前为0	2008.50	5.19	2000.00	2017.00
	某个县级单元在具体年份内是否开通高铁	HSR	由Treat乘以T获得	0.13	0.34	0.00	1.00
控制变量	县级单元的具体行政类型（城市等级）	Admin	根据县级单元的行政等级划分为5档	4.30	0.91	1.00	5.00
	常住人口	Pop/万人	常住人口数	101.72	162.68	7.24	2421.47
	人均生产总值	pGDP/元	人均生产总值	33848.01	33128.08	1681.00	218984.10
	固定资产投资	FAI/100万元	固定资产投资	184.95	474.55	0.13	7246.60
	房地产投资	REI/100万元	房地产投资	57.03	210.44	0.00	3856.53
	公共财政支出	PFE/100万元	公共财政支出	59.07	283.64	0.48	7547.62
	教育支出	Edu/100万元	教育支出	10.02	39.49	0.06	874.10
	专利数	Patent/项	专利数	5682.75	31313.68	1.00	954400.00
	城镇化率	Nag/%	非农人口占总人口的比例	83.70	12.26	37.02	99.00

变量	因变量：第三产业产值(Ind3)
变量	1	2	3	4	5	6	7 大城市组	8 中等城市组	9 小城市组
注：列1~9解释见表2；^*、^、^* 分别表示在1%，5%和10%水平下显著；括号内数值为t值；变量解释见表1；空白项为无此项。
HSR	0.001	0.086^***	0.020^**	0.033^***	0.033^***	0.028^***	0.059^***	0.050^***	−0.003
	(0.10)	(6.29)	(2.30)	(3.86)	(3.90)	(3.38)	(3.48)	(3.28)	(−0.22)
Treat	0.399^***	0.336^***	0.001	0.050	0.050	0.056	0.285^***	0.475^***	0.113^**
	(10.30)	(9.82)	(0.02)	(1.39)	(1.40)	(1.57)	(7.24)	(4.09)	(1.91)
T	−0.001	−0.031^**	0.027^**	0.013	0.012	0.014^*	0.009	−0.027^*	0.035^**
	(−0.08)	(−2.07)	(2.47)	(1.50)	(1.47)	(1.68)	(0.58)	(−1.79)	(2.15)
pGDP		0.430^***	0.811^***	0.697^***	0.695^***	0.701^***	0.699^***	0.766^***	0.575^***
		(21.18)	(54.72)	(27.78)	(26.02)	(26.52)	(17.44)	(12.39)	(9.11)
Pop			1.970^***	1.779^***	1.778^***	1.795^***	1.847^***	1.744^***	1.664^***
			(53.19)	(26.76)	(26.76)	(27.94)	(26.50)	(10.31)	(6.64)
Patent				0.021^***	0.021^***	0.020***	0.018^***	−0.026^***	−0.040^***
				(−6.98)	(−6.78)	(−6.43)	(−4.18)	(−4.03)	(−6.44)
Nag					0.013^***	0.033	0.333^**	−0.121	0.019
					(0.17)	(0.43)	(2.49)	(−0.81)	(0.14)
REI						−0.012^***	0.026^***	−0.010	−0.006
						(−2.91)	(−3.28)	(−1.07)	(−0.70)
常数项	1.722^***	2.003^***	8.097^***	7.042^***	7.079^***	−7.273^***	7.712^***	−6.719^***	−5.904^***
	(77.84)	(−11.36)	(−49.57)	(−24.45)	(−19.43)	(−19.53)	(−13.23)	(−9.68)	(−6.40)
个体固定	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
时间固定	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes	Yes
样本量	3553	3553	3553	3553	3553	3553	1368	1242	972
R²	0.9858	0.9888	0.9944	0.9965	0.9965	0.9966	0.9968	0.9934	0.9948

变量	产业结构	第二产业	第三产业
注：^*、^、^* 分别表示在1%，5%和10%水平下显著；括号内数值为t值；HSR-treat为高铁开通当年对因变量的影响系数；HSR-1st、HSR-2nd、HSR-3rd分别为HSR-n之后的第1、2、3年影响系数。
HSR-treat	0.045^***	0.077	0.041^*
	(2.62)	(1.31)	(1.94)
HSR-1st	−0.011	−0.119^**	0.026^**
	(−0.51)	(−2.01)	(2.17)
HSR-2nd	−0.005	−0.092^**	−0.014
	(−0.19)	(−2.04)	(−0.53)
HSR-3rd	0.036^**	−0.122^***	−0.024
	(1.98)	(−2.94)	(−1.33)
个体固定	Yes	Yes	Yes
时间固定	Yes	Yes	Yes

变量	产业结构	第二产业	第三产业
注：HSR-Bn代表高铁开通前第n年交互项的回归系数；括号内数值为t值。
HSR-B4	0.003	−0.025	0.005
	(0.13)	(−0.76)	(0.15)
HSR-B3	0.012	−0.042	0.040
	(0.60)	(−1.05)	(0.93)
-HSR-B2	0.025	−0.023	0.045
	(1.31)	(−0.61)	(0.99)
HSR-B1	0.023	−0.047	−0.014
	(1.07)	(−1.40)	(−0.29)
个体固定	Yes	Yes	Yes
时间固定	Yes	Yes	Yes

组别	门槛模型	门槛值/万人	F值	P值	不同显著性水平临界值			95%置信区间
组别	门槛模型	门槛值/万人	F值	P值	1%	5%	10%	95%置信区间
注：^*、^表示在1%，5%水平下显著。
全样本	单门槛	362.107	32.637^***	0.007	28.879	19.111	14.394	[119,538]
大城市组	单门槛	359.864	42.016^***	0.003	38.588	28.091	21.861	[322,722]
中等城市组	单门槛	55.149	21.556^**	0.030	37.250	17.309	12.577	[52,112]
小城市组	单门槛	45.955	3.396	0.230	27.394	16.167	9.129	[8,71]

The Impact of High-speed Railway on the Industrial Structure of County-level Units: Taking the Yangtze River Delta as an Example

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