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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

Postal Subscription Code 80-973

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Front Envir Sci Eng    2012, Vol. 6 Issue (3) : 412-420    https://doi.org/10.1007/s11783-012-0392-0
RESEARCH ARTICLE
Spillover effect of environmental investment: evidence from panel data at provincial level in China
Qunhui LIN1(), Guanyi CHEN1, Wencui DU2, Haipeng NIU3
1. School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China; 2. School of Economics & Business Administration, Beijing Normal University, Beijing 100875, China; 3. School of Business, Renmin University of China, Beijing 100872, China
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Abstract

This paper considers pollution density as a function of environmental investment. The higher environmental investment, the lower pollution density. The lower the pollution density is the higher production technology becomes. This is called the spillover effect. We collected China’s panel data at the provincial level from 2005 to 2009, and tested the spillover effect of environmental investment. This paper finds that the environmental investment influenced production technology positively. There is a significant positive relation between government expenditure and spillover effect.
Keywords environmental investment      spillover effect      endogenous growth     
Corresponding Author(s): LIN Qunhui,Email:janetlqh@hotmail.com   
Issue Date: 01 June 2012
 Cite this article:   
Qunhui LIN,Guanyi CHEN,Wencui DU, et al. Spillover effect of environmental investment: evidence from panel data at provincial level in China[J]. Front Envir Sci Eng, 2012, 6(3): 412-420.
 URL:  
https://academic.hep.com.cn/fese/EN/10.1007/s11783-012-0392-0
https://academic.hep.com.cn/fese/EN/Y2012/V6/I3/412
Fig.1  Three effects of environmental investment
province20092008200720062005average
Beijing25026141228780258
Tianjin29616024779243205
Hebei764720615285210518.8
Shanxi554454187127112286.8
Inner Mongolia244313225296176250.8
Liaoning323280223165171232.4
Jilin1572401107134122.4
Heilongjiang138255928242121.8
Shanghai893719383378289532.4
Jiangsu1100170610359337341102
Zhejiang79639959045745611366
Anhui3515672569965267.6
Fujian429337240153203272.4
Jiangxi1801021906691125.8
Shandong11191240795379217750
Henan480354393230174326.2
Hubei51925673143112220.6
Hunan4272451678080199.8
Guangdong341373403664528261.8
Guangxi355317566969173.2
Hainan414755272138.2
Chongqing406241254237116250.8
Sichuan424403289193144290.6
Guizhou715197434160.6
Yunnan36625115995109196
Shaanxi37421624612452202.4
Gansu1354987303968
Qinghai5610951143352.6
Ningxia1448864383273.2
Xinjiang191118886374106.8
Tab.1  Environmental investment from 2005 to 2009 in China/(billion CNY)
variabledefinition
technologythe number of patents accepted
EInvestmentinvestment in Environment Components for New Construction Projects
initial technologythe technology last year
GDPthe natural logarithm of gross domestic product
industry structurethe proportion of tertiary industry in GDP
fixed assetsthe natural logarithm of local fixed assets
government expenditurethe proportion of government expenditure in GDP
Tab.2  Variable and definition
variablemeanmedianmaximizeminimizeStd. Dev.
technology/unit19157.847913.501743299728888.48
EInvestment/(￥billion CNY)300.4206.539950407.3
GDP/(billion CNY)90521.670210394825.62512.179458.9
industry structure/%403976280.08
fixed assets/(billion CNY)47175.136536.7190345.32703.437653
government expenditure/%20.0816.9996.417.9213.95
Tab.3  Descriptive statistics
variableADFvariableADF
Technology-8.9528a)industry structure-13.7872a)
EInvestment-7.8821a)fixed assets-7.7864a)
initial technology-7.5560a)government expenditure-6.4495a)
GDP-7.7824a)
Tab.4  Unit root test
variablemodel(1)model(2)model(3)model(4)model(5)model(6)
EInvestment0.1183a) (10.8118)0.0003 (0.7105)0.0006c) (1.7463)0.0009b) (2.3787)0.0008b) (2.2849)0.0008b) (2.2355)
initial technology1.0206a) (467.4646)0.9524a) (43.7598)0.9435a) (43.6656)0.9581a) (42.3160)1.0216a) (39.4188)
GDP0.0673a) (3.1502)0.0581a) (2.7357)-0.0759 (-1.0520)-0.0443 (-0.6525)
industry structure0.3795b) (2.4121)0.4592a) (2.9204)0.4566a) (2.9145)
fixed assets0.1245c) (1.9415)0.1699b) (2.3643)
government expenditure0.0070a) (4.2413)
adjusted R20.20120.98870.98960.99010.99040.9917
sample124124124124124124
Tab.5  Spillover effect in China
variablemodel(1)model(2)model(3)model(4)model(5)model(6)
EInvestment0.1183a) (10.8118)1.0617a) (10.6525)1.0256a) (12.2728)0.9160a) (10.6687)1.9464a) (8.1909)2.3894a) (13.2190)
initial technology × EInvestment-0.0889a) (-9.5739)-0.0722a) (-8.9065)-0.0772a) (-9.7965)-0.0242b) (-1.7733)0.0483a) (3.8899)
GDP × EInvestment-0.0822a) (-7.2029)-0.0844a) (-7.7252)-0.1036a) (-9.4872)-0.0802a) (-9.5604)
industry structure × EInvestment0.4160a) (3.4847)-0.1936 (-1.1123)-0.9332a) (-6.3350)
fixed assets × EInvestment-0.1443a) (-4.5999)-0.25573a) (-9.9477)
government expenditure × EInvestment0.0041a) (9.9245)
adjusted R20.68120.95660.73050.67170.55830.5767
sample124124124124124124
Tab.6  Influencing factors of spillover effect in China
variableeasternmiddlewestern
EInvestment0.0006b) (2.4181)0.0035c) (1.8044)-0.0002 (-0.0442)
initial technology0.9890a) (34.9261)0.8972a) (9.6071)1.0592a) (18.7899)
GDP0.0170 (0.2660)0.0425 (0.2570)-0.1706 (-0.7171)
industry structure0.1538 (0.7719)0.8648 (0.8983)-1.1724 (-1.3554)
fixed assets0.0064 (0.1072)0.0377 (0.1993)0.1657 (0.6352)
government expenditure-0.0019 (-0.4988)0.0017 (0.0947)0.0121a) (3.3700)
adjusted R20.99580.97690.9811
sample522448
Tab.7  Spillover effect in three regions
Variableeasternmiddlewestern
EInvestment2.1953a) (9.9826)3.5960a) (7.8108)3.0130a) (5.4405)
initial technology × EInvestment0.0525a) (3.6573)0.0552 (1.0578)0.0080 (0.2239)
GDP × EInvestment-0.0628a) (-7.4218)-0.1922a) (-4.1590)-0.2149a) (-3.8922)
industry structure × EInvestment-0.9462a) (-5.7571)-1.1418b) (-1.8609)0.0840 (0.0904)
fixed assets × EInvestment-0.2436a) (-8.2728)-0.3827a) (-5.1073)-0.3052a) (-5.5197)
government expenditure × EInvestment0.0051a) (9.9390)0.0070a) (4.8542)0.0023a) (3.4722)
adjusted R20.94360.61500.5088
sample522448
Tab.8  Influencing factors of spillover effect in three regions
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