The interaction of clusters between manufacturing and producer services in China

Figures & data

Table 1. Definition of Types of Manufacturing and Regions.

Content	Type	Definition
Manufacturing	Labour-intensive	Clothing, shoes, hat manufacturing, textile manufacturing, the agricultural and sideline food processing industry, food manufacturing, the beverage processing industry
	Resource-intensive	The non-mental mineral product industry, the ferrous metal smelting and rolling processing industry, the metal product industry, the tobacco product industry, the papermaking and paper product industry, the petroleum processing, coking and nuclear fuel processing industry, the non-ferrous metal smelting and rolling processing industry
	Capital-intensive	The electrical machinery and equipment industry, the transportation equipment industry, the chemical fibre industry, the general equipment industry, the specific equipment industry
	Technology-intensive	The pharmaceutical industry, the instrument and culture, office machinery industry, the chemical raw materials and chemical products industry, the communications equipment, computers and other electronic equipment industry
Regions	Eastern region	Beijing, Tianjin, Liaoning, Hebei, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Hainan
	Middle region	Shanxi, Neimenggu, Jilin, Heilongjiang, Anhui, Jiangxi, Henan, Hubei, Hunan, Guangxi
	Western region	Chongqing, Sichuan, Guizhou, Yunnan, Tibet, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang

Source: The data is from China’s Industrial Economy Statistical Yearbook.

Table 2. β Value of Various Types of Manufacturing in 2006–2011.

β	Time						β	Time
	2006	2007	2008	2009	2010	2011		2006	2007	2008	2009	2010	2011
LDn	1.06	1.07	1.04	1.08	1.10	1.09	LDe	0.96	0.91	0.89	0.91	0.90	0.90
ZYn	1.30	1.28	1.27	1.30	1.29	1.26	ZYe	0.95	0.98	0.99	1.00	1.00	1.00
ZBn	0.80	0.79	0.78	0.79	0.78	0.77	ZBe	0.98	0.97	0.99	0.99	0.99	1.02
JSn	0.97	0.96	0.96	0.93	0.91	0.89	JSe	1.04	1.03	1.05	1.03	1.05	1.04
LDm	1.18	1.17	1.11	1.14	1.16	1.16	LDw	1.04	1.14	1.14	1.19	1.24	1.23
ZYm	1.26	1.24	1.19	1.21	1.18	1.15	ZYw	1.73	1.67	1.66	1.71	1.71	1.66
ZBm	0.85	0.84	0.78	0.80	0.78	0.77	ZBw	0.54	0.53	0.54	0.56	0.54	0.49
JSm	0.76	0.74	0.73	0.74	0.74	0.73	JSw	1.10	1.11	1.10	1.00	0.93	0.89

Note: subscript _n represents the whole country, _m for the middle region, _e for the eastern region and _w for the western region.

Source: The data is from China’s Industrial Economy Statistical Yearbook.

Table 3. β Value of Various Types of Producer Services in 2006–2011.

β	Time						β	Time
	2006	2007	2008	2009	2010	2011		2006	2007	2008	2009	2010	2011
JYn	1.10	1.15	1.11	1.12	1.12	1.12	JYe	0.94	1.03	0.95	0.95	0.96	0.95
PLn	0.96	0.99	1.00	0.96	0.96	0.95	PLe	1.01	0.99	1.00	1.00	1.00	1.00
JRn	0.93	0.86	0.87	0.95	0.96	0.98	JRe	1.08	1.06	1.07	1.05	1.04	1.04
JYm	1.24	1.26	1.27	1.22	1.22	1.23	JYw	1.12	1.16	1.13	1.20	1.20	1.18
PLm	0.99	1.03	1.04	1.01	1.00	1.00	PLw	0.89	0.94	0.95	0.86	0.86	0.85
JRm	0.61	0.61	0.60	0.75	0.77	0.79	JRw	1.08	0.90	0.93	1.04	1.06	1.10

Note: subscript _n represents ‘the whole country’; _m for middle region; _e for eastern region and _w for western region.

Source: The data is from China’s Industrial Economy Statistical Yearbook.

Table 4. Description of the Influencing Factors.

Symbol	Factor	Measurement
RD	Technical level	R&D of the above scaled enterprise (with unit being ten thousand Yuan) divided by the certain region’s GDP (with unit being 0.1 billion Yuan)
NH	Energy consumption	Per unit GDP energy consumption coefficient multiplied by 100
FDI	Multinational corporation	Foreign direct investment (with unit being 0.1million US$) divided by the Certain region’s GDP (with unit being 0.1billion Yuan)
JZ	Cooperation & competition degree	Ten times of the quantity of private enterprises divided the quantity of state and state-owned enterprises
SO	Policy influence	The quantity of sulphur dioxide emissions (with unit being ton) divided the certain region’s GDP (with unit being 0.1billion Yuan)

Source: The data is from China’s Industrial Economy Statistical Yearbook.

Table 5. Empirical Result of Factors Influencing Manufacturing Cluster and Producer Services Cluster.

Econometric result	Manufacturing				Producer services
	LD	ZY	ZB	JS	JY	PL	JR
c	7.170	5.243	5.659	4.778	4.102	5.462	3.572
α	−0.042**	−0.044	−1.193	0.133	0.150	−0.193	0.149
η	−0.364	−0.110	0.215	−0.020	−0.029	−0.047	0.137
δ	−0.208	0.176	0.519	−0.257	0.060	0.023	−0.102
ϕ	0.210	−0.093	0.197	−0.027	0.005*	0.015	−0.024
γ	−0.260	−0.056	0.132	0.079	−0.083	0.018	0.042
A-R^2	0.434	0.384	0.734	0.316	0.413	0.244	0.087

Note:

^* indicated not passing 10 percent significance test

^** indicated passing 10 percent significance test but not 5 percent significance test, the other indicated passing 5 percent significance test, p-value of each model was 0.000. The following carried the same treatment.

Source: The data is from China’s Industrial Economy Statistical Yearbook.

Table 6. Empirical Result of Producer Services Cluster’s Influence on Various Types of Manufacturing Cluster.

Econometric result	LD	ZY		ZB		JS
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
c	2.821	3.485	3.129	2.803	3.133	10.422
χ	0.264	0.477	0.500	−0.606	−0.627	−0.883
λ	0.282	−0.189	−0.155	0.901	0.869	−0.299
σ	−0.178	−0.020*		0.019*		−0.107
A-R^2	0.072	0.130	0.130	0.110	0.110	0.221

Note:

^* indicated not passing 10 percent significance test

^** indicated passing 10 percent significance test but not 5 percent significance test, the other indicated passing 5 percent significance test, p-value of each model was 0.000. The following carried the same treatment.

Source: The data is from China’s Industrial Economy Statistical Yearbook.

Table 7. Empirical Result of Producer Services Cluster’s Influence on Various Types of Manufacturing Cluster in Various Regions.

Region		LD	ZY	ZB	JS
The eastern region	c	1.214	9.964	−1.331	1.214
	χ	0.322	−0.079*	−0.058*	0.322
	λ	0.450	−0.411	0.739	0.450
	σ	−0.064*	−0.692	0.594	−0.064*
	A-R^2	0.127	0.582	0.366	0.127
The middle region	c	−8.224	0.408	22.25	0.705
	χ	0.754	1.022	−2.643	−0.149*
	λ	2.073	−0.324*	−0.775	1.014
	σ	−0.067*	0.219	−0.390	−0.090**
	A-R^2	0.246	0.330	0.542	0.446
The western region	c	7.737	33.58	−46.16	13.52
	χ	−0.045*	−2.156	3.319	−0.756
	λ	−0.531*	−2.618	4.724	−0.645*
	σ	−0.132*	−1.443	2.805	−0.565
	A-R^2	0.010	0.122	0.066	0.018

Note:

^* indicated not passing 10 percent significance test

^** indicated passing 10 percent significance test but not 5 percent significance test, the other indicated passing 5 percent significance test, p-value of each model was 0.000. The following carried the same treatment.

Source: The data is from China’s Industrial Economy Statistical Yearbook.