Research Article How Does Environmental …downloads.hindawi.com/journals/mpe/2016/2405624.pdfintensive industries are likely to increase inputs to o set the cost of regulation when

Research ArticleHow Does Environmental Regulation AffectIndustrial Transformation A Study Based onthe Methodology of Policy Simulation

Wei Liu1 Jian Tong2 and Xiaohang Yue3

1School of Management Science and Engineering Dongbei University of Finance and Economics Dalian 116025 China2School of Economics and Management Tsinghua University Beijing 100084 China3Lubar School of Business University of WisconsinndashMilwaukee Milwaukee WI 53211 USA

Correspondence should be addressed to Wei Liu liuweidufe126com

Received 28 September 2015 Revised 30 January 2016 Accepted 14 February 2016

Academic Editor Fabio Tramontana

Copyright copy 2016 Wei Liu et al This is an open access article distributed under the Creative Commons Attribution License whichpermits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

The difference of factor input structure determines different response to environmental regulation This paper constructs atheoretical model including environmental regulation factor input structure and industrial transformation and conducts a policysimulation based on the difference of influencingmechanism of environmental regulation considering industrial heterogeneityThefindings show that the impact of environmental regulation on industrial transformation presents comparison of distortion effect ofresource allocation and technology effect Environmental regulationwill promote industrial transformationwhen technology effectof environmental regulation is stronger than distortion effect of resource allocation Particularly command-control environmentalregulation has a significant incentive effect and spillover effect of technological innovation on cleaning industries but these effectsdo not exist in pollution-intensive industries Command-control environmental regulation promotes industrial transformationThe result of simulation showed that environmental regulation of market incentives is similar to that of command-control

1 Introduction

Environmental regulation is one of the policies and mea-sures by which the government solves ldquomarket failurerdquo ofenvironmental issue which has become an important way topush industrial transformation The main cause of industrialtransformation is technological innovation According toPorter [1 2] the appropriate environmental regulation policyhelps to stimulate the enterprises to carry out technologicalinnovation which can be called the effect of technologicalinnovation incentive Jaffe and Palmer [3] present threedistinct variants of the so-called Porter Hypothesis namelythe ldquoweakrdquo version the ldquonarrowrdquo version and the ldquostrongrdquoversion Lanoie et al [4] tested the significance of thesedifferent variants of the Porter Hypothesis using data on thefourmain elements of the hypothesized causality chain (envi-ronmental policy research and development environmentalperformance and commercial performance) They found

strong support for the ldquoweakrdquo version and qualified supportfor the ldquonarrowrdquo version and the ldquostrongrdquo version Ambecet al [5] provided an overview of the key theoretical andempirical insights on the Porter Hypothesis to date Blind[6] differentiated between economic social and institu-tional regulations following the OECD taxonomy on regu-lations The results confirmed the hypotheses derived fromthe conceptual theoretical framework determining techni-cal progress and innovation endogenously and allowing adistinction between short-term and long-term effects Sothe influence of environmental regulation on technologicalinnovation is determined by many factors

In terms of industrial sector the adjustment of indus-trial production capacity is related to the proportion offixed capital in production factors input The fixed cost ishigher relatively in pollution-intensive industries due tothe large fixed capital input the complexity of technologyand the specificity of equipment It is difficult to update

Hindawi Publishing CorporationMathematical Problems in EngineeringVolume 2016 Article ID 2405624 10 pageshttpdxdoiorg10115520162405624

2 Mathematical Problems in Engineering

technology for pollution-intensive industries when envi-ronmental regulation intensity increases Pollution-intensiveindustries may augment production factors input to offsetenvironmental regulation cost which will cause a distortioneffect of resource allocation In contrast it is easier tochange technology for cleaning industries when environmen-tal regulation intensity increases Cleaning industries willincrease RampD investment to improve technology to avoidenvironmental regulation cost which will cause incentiveeffects and spillover effects of technological innovationTherefore the increase of environmental regulation inten-sity ultimately drives the adjustment of industrial structure[7]

Many literatures focused on the effect of environmen-tal regulation on industrial structure transformation fromproportion of the third industry and secondary industryperspective [8 9] Li [8] addressed environmental regulationswhich will improve the proportion of the service sectorrelative to the industrial sector and promote the adjustmentof industrial structure The previous literatures were moreconcerned with the incentive effect of environmental regula-tion on technological innovation within the industrial sectorFor instance Bai and Song [10] found that environmentalregulation can improve the efficiency of Chinese thermalpower as a whole and cause incentive effects of technologicalinnovation Zhang et al [11] conducted an empirical test onindustrial sectors of 30 provinces in China and found that theeffect of environmental regulation on technological progressrate is different among different regions In recent yearsmanyresearchers found that industrial heterogeneity plays a veryimportant role in the relationship between environmentalregulation and technological innovation but the conclusionis not consistent [12ndash15] Li and Tao [12] indicated environ-mental regulation intensity of heavy pollution industry canpromote the industrial green total factor productivity theenvironmental regulation intensity of the moderate pollutionindustry is weak and technological innovation can be earlybreakthrough ldquoUrdquo inflection point for light pollution indus-try Nie and Huang [15] found the current strength of envi-ronmental regulation hinders the improvement of moderateenergy-intensive industries in total factor energy productiv-ity technological innovation and efficiency improvementshighly energy-intensive industriesrsquo environmental regulatoryintensity does not significantly influence the total factorenergy productivity for themild energy-intensive industriesthe intensity of environmental regulation promotes techno-logical innovation

The existing literatures mostly focused on the effectof environmental regulation on industrial structure at thecountry or region level and paid little attention to theimpact of environmental regulation on industrial transfor-mation inside the industrial sector In the meantime thestructure of factors input may cause different response toenvironmental regulation in pollution-intensive industriesand cleaning industriesTherefore we construct a theoreticalmodel to analyze different effect of environmental regulationon heterogeneity industries in this paper Then we conduct asimulation to examine the effect of different environmentalregulation policy and put forward some suggestion

2 The Mathematical Model

Environmental regulation includes command-control andmarket incentive regulation In this paper we select environ-mental regulation intensity as a proxy of command-controlenvironmental regulation environment tax and environ-mental technology subsidies as a proxy of market incentiveenvironmental regulation Further we assume that tech-nology is relatively fixed for pollution-intensive industriesbut environmental technology will continue to change forcleaning industries in the process of production Pollution-intensive industries are likely to increase inputs to offset thecost of regulation when environmental regulation intensityincreases namely the distortion effect of resource allocationAnd cleaning industries will promote the environmentaltechnology namely the incentive effect of technologicalinnovation At the same time the technology change willmake organization structure and management mode changefurther eventually leading to improvements in total factorproductivity namely technology spillover effect In shortthe distortion effect of resources allocation represents thedistortion of environmental regulation moreover incentiveeffect and spillover effect of technological innovation reflectthe externality of environment regulation When distortioneffect of environmental regulation is bigger than the exter-nality (namely the benefit that pollution-intensive industriesaccept tax punishment and increase factors input is higher)environmental regulation will inhibit industrial transforma-tion When the externality of environmental regulation isgreater than distortion effect (namely incentive effect andspillover effect of technology innovation for cleaning industryis higher) environmental regulation will promote industrialtransformation In the following section the dynamic generalequilibrium model is selected to analyze the mechanism

21 The Effect of Environmental Regulation on Pollution-Intensive Industries The capital labor and environmentalresources are input in the process of production in pollution-intensive industry Because of consumption of environ-mental resources pollution emissions will be producedHere environmental resources include fossil energy andother natural resources for instance soil and water andair As mentioned above pollution-intensive industries arerestricted by replacement cost of machinery and equipmentso environmental technology is relatively fixed which canonly accept tax penalties Therefore the production functionin pollution-intensive industries is as follows

1198841119905= Φ011986011199051198701205721

11199051198711205731

11199051198641205741

1119905 (1)

where Φ0

denotes fixed environmental technology inpollution-intensive industries 119860

1119905represents total factor

productivity 1198701119905 1198711119905 and 119864

1119905denote capital labor and

environmental resource respectivelyThe function of pollution emission in pollution-intensive

industries is as follows

1198641198721119905= Ψ (Φ

0 1198641119905) =

12058811198641205882

1119905

Φ0

(2)

Mathematical Problems in Engineering 3

where Ψ1015840Φ(Φ119905 1198641119905) lt 0 denotes that environmental technol-

ogy level is higher and environmental pollution emissions arelower Ψ1015840

119864(Φ119905 119864119905) gt 0 denotes that the more environmental

resource is consumed the more environmental pollutionemissions are produced

The government will levy a tax on pollution-intensiveindustry When environmental regulation intensity is highenterprises require burdening higher cost of tax There-fore there is a trade-off between increasing environmen-tal resources consumption and reducing the environmentresources consumption So the profit function in pollution-intensive industries is as follows

Π1119905= 11987511199051198841119905minus 11990311199051198701119905minus 1199081199051198711119905minus 119875119890

1199051198641119905minus 120591 (120601) 119864119872

1119905 (3)

where 120591(120601) = 120591 + 12058101206011205811 represents the tax rate of environ-

mental pollutionwhich is related to environmental regulationintensity Enterprises required undertaking the higher cost oftax when environmental regulation intensity is high

By solving the profit maximization problem we canobtain the first-order conditions

12057211198751119905Φ011986011199051198701205721minus1

11199051198711205731

11199051198641205741

1119905= 1199031119905

(4)

1205731119875111990511986011199051198701205721

11199051198711205731minus1

11199051198641205741

1119905= 120596119905

(5)

12057411198751119905Φ011986011199051198701205721

11199051198711205731

11199051198641205741minus1

1119905minus 119875119890

119905minus 120591 (120601)

120588112058821198641205882minus1

1119905

Φ0

= 0 (6)

Equations (4) and (5) denote the price of capital and laborequal to their marginal output respectively Equation (6)denotes the marginal output of environmental resources isequal to the sum of environmental resources price and taxcost which is caused by increasing environmental resourcesconsumption to produce environmental pollution increment

22The Effect of Environmental Regulation on Cleaning Indus-tries Cleaning industries generally include large enterpriseswith the stronger comprehensive technology research anddevelopment ability and small businesses with emergingtechnology The higher the intensity of environmental reg-ulation the stronger the motivation of green technologystrategy carried out by cleaning industries According toPorter [1 2] the appropriate environmental regulation policyhelps to stimulate the enterprises to carry out technologicalinnovation which can be called the effect of technologicalinnovation incentive The cleaning industries will increasegreen RampD investment improve the level of human capitaland develop perfect system environment which in turnimprove technological management level and change organi-zation structure and management mode eventually leadingto improvements in total factor productivity namely tech-nology spillover effect Cleaning industries alsowill dischargepollution in the process of production In order to expandtechnology innovation incentive effect the government will

impose subsidy to RampD investment of environmental tech-nology in cleaning industries Therefore the productionfunction in cleaning industries is as follows

1198842119905= Φ (120601

119905 119870119903119889119905

) 11986021199051198701205722

21199051198711205732

21199051198641205742

2119905

Φ(120601119905 119870119903119889119905

) = 12060111990512058831198701205884

119903119889119905+ Φ1

(7)

where 120601 is environmental regulation intensity Φ119905is initial

level of environmental technology in cleaning industriesΦ1015840

120601(120601 119870119903119889119905

) gt 0 and Φ1015840

119870(119889 119870119903119889119905

) gt 0 denote that the higherenvironmental regulation intensity and themoreRampD invest-ment of green technologies the greater spillover effect ofgreen technology and production technology respectively1198602119905denotes total factor productivity in cleaning industries

1198702119905 1198712119905 and 119864

2119905represent capital labor and environmental

resource respectivelyDifferent from pollution-intensive industries cleaning

industries not only can improve the level of environmentaltechnology to control pollution emissions but can reduceproduction to control pollution emissions So the function ofpollution emission in cleaning industries is as follows

1198641198722119905= Ψ (Φ

119905 1198642119905) =

12058851198641205886

2119905

Φ119905

(8)





The profit function in cleaning industries is as follows


1199051198642119905minus 120591 (120601) 119864119872

2119905

minus (119903119903119889119905

minus ]0)119870119903119889119905

(9)

where ]0denotes the subsidy that government imposes to

RampD investment of environmental technologyBy solving the profit maximization problem we can

obtain the first-order conditions

12057221198752119905Φ(120601119905 119870119903119889119905

) 11986021199051198701205722minus1

21199051198711205732

21199051198641205742

2119905= 1199032119905

(10)

12057321198752119905Φ(120601119905 119870119903119889119905

) 11986021199051198701205722

21199051198711205732minus1

21199051198641205742

2119905= 120596119905

(11)

12057421198752119905Φ(120601119905 119870119903119889119905

) 11986021199051198701205722

21199051198711205732minus1

21199051198641205742minus1

2119905minus 119875119890

119905

minus 120591 (120601)

120588512058861198641205886minus1

2119905

Φ119905

= 0

(12)

1198752119905120601119905120588312058841198701205884minus1

11990311988911990511986021199051198701205722

21199051198711205732

21199051198641205742

2119905

+ 120591 (120601)

12058851198641205886

2119905

Φ2

119905

120601119905120588312058841198701205884minus1

119903119889119905minus (119903119903119889119905

minus ]0) = 0

(13)

Equations (10) and (11) denote the price of capital and laborequals their marginal output Equation (12) denotes that themarginal output of environmental resources is equal to the


sum of environmental resources price and tax cost which iscaused by increasing environmental resources consumptionto produce environmental pollution increment Equation(13) denotes that the price of RampD capital of environmentaltechnology is equal to the sum of marginal output incrementand the reduction of tax cost caused by environmentaltechnology innovation and the governmental subsidy forRampD investment of environmental technology

23 The Production of Environmental Industries Environ-ment and resources also need to be produced by capitaland labor such as the extraction of fossil resource waterresource supply and coal mining Production function ofenvironmental industries is as follows

119864119905= 11986031199051198701205723

31199051198711minus1205723

3119905 (14)

The profit function of environmental industries is as follows

Π3119905= 119875119890

119905119864119905minus 11990331199051198703119905minus 1199081199051198713119905 (15)

By solving the profit maximization problem we can obtainthe first-order conditions

1205723119875119890

11990511986031199051198701205723minus1

31199051198711minus1205723

3119905= 1199033119905

(1 minus 1205723) 119875119890

11990511986031199051198701205723

3119905119871minus1205723

3119905= 120596119905

(16)

Equation (16) denotes that the price of capital and laborequals their marginal output in environmental industries

24TheConsumption of the Public Thepublic achieves a life-time utilitymaximization by choosing between clean productand the polluting products and between consumption andsaving Objective function of the public is as follows

maxinfin

sum

119905=0

(1198621minus1205901

1119905

1 minus 1205901

+ 1205771198621minus1205902

2119905

1 minus 1205902

) (17)

where 1205901and 120590

2denote the intertemporal substitution elas-

ticity of two kinds of products respectively 120577 depicts how thepublic pay close attention to the two kinds of products Thebudget constraint equations of the public are as follows

11987511199051198621119905+ 11987521199051198622119905+ 119876119905119878119905+ Π119905119866119905

le 11990311199051198701119905+ 11990321199051198702119905+ 119903119903119889119905

119870119903119889119905

+ 11990331199051198703119905+ 119908119905119871119905

119878119905= 1198781205791

11199051198781minus1205791

2119905

119876119905= (

1198751119905

1205791

)

1205791

(1198752119905

1 minus 1205791

)

1minus1205791

119866119905= 1198661205792

11199051198661minus1205792

2119905

Π119905= (

1198751119905

1205792

)

1205792

(1198752119905

1 minus 1205792

)

1minus1205792

(18)

where 1198781119905and 119878

2119905denote savings of the public for the two

kinds of products respectively 119878119905is the sum of 119878

1119905and 119878

2119905

1205791is substitution elasticity of the two kinds of savings 119876

119905is

the price of 119878119905 1198661119905and 119866

2119905denote the government purchase

of the two kinds of products respectively 119866119905is the sum of

1198661119905and 119866

2119905 1205792is substitution elasticity of the two kinds of

products which the government purchases Π119905is the price of

119866119905By solving the utilitymaximization problem of the public

we can obtain the first-order conditions

119862minus1205901

1119905= 1205821199051198751119905

(19)

120577119862minus1205902

2119905= 1205821199051198752119905

(20)

120573120582119905+1

1199031119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205751) = 0 (21)

120573120582119905+1

1199032119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205752) = 0 (22)

120573120582119905+1

119903119903119889119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 120575119903119889) = 0 (23)

120573120582119905+1

1199033119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205753) = 0 (24)

Equations (19) and (20) denote that the marginal utility ofconsumption of pollution product and clean product is equalto the marginal income of investment respectively namelyintertemporal substitution equation Equations (21)ndash(24) areEuler equations

In particular the equation of industry transformation isas follows

STR =1198842

1198841

(25)

25 Model Solutions The first-order conditions combinedwith capital formation equation the government budgetconstraint equation andmarket clearing condition constituteour theoretical model We can solve the theoretical modelThe optimization problem that theoretical model solves isto configure the limited resource among 119870

1119905 1198711119905 1198641119905 1198702119905

1198712119905 1198642119905 1198703119905 and 119871

3119905 so as to maximize profits and the

lifetime utility of the typical families By solving theoreticalmodel we cannot get analytical solutions of 119875

2 119875119890 120596 119870

119903119889

1198641 and 119864

2 because there is a complex nonlinear relationship

among them Equations (26) are steady state equations ofthe equilibrium solution Industrial structure is the optimalstructure under the steady state of model because it achievesprofitsmaximization and lifetimeutilitymaximization of rep-resentative families simultaneously which is to maximize thesocial welfareThe optimal industrial structure is determinedby the parameters of the model at the same time based onthe steady state equations (26) namely the optimal industrialstructure is a function of environmental regulation policyIndustrial structure transition is decided by the governmentrsquosenvironmental regulation policy Pollution-intensive indus-tries will gradually reduce the scale of production to dropcost and cleaning industries will improve the environmen-tal technology which is affected by technology innovationincentive effect when the government makes a tougherenvironmental regulation policy Technology spillover effectleads to the improvement of total factor productivity whichwill promote the cleaning production scale to achieve the aim


Table 1 The division of cleaning industries and pollution-intensive industries

Cleaning industries Pollution-intensive industries1 Manufacture of electrical machinery and equipment 1 Manufacture of foods2 Manufacture of articles for culture education and sport activity 2 Processing of food from agricultural products3 Printing and reproduction of recording media 3 Manufacture of textile

4 Manufacture of communication equipment computer andother electronic equipment 4 Production and distribution of gas

5 Manufacture of furniture 5 Manufacture of beverage6 Manufacture of textile wearing apparel Footwear and caps 6 Extraction of petroleum and natural gas7 Manufacture of general purpose machinery 7 Production and distribution of water8 Manufacture of tobacco 8 Manufacture and processing of nonferrous metals9 Manufacture of transport equipment 9 Manufacture of chemical raw material and chemical products

10 Manufacture of measuring instrument machinery for culturaland office work 10 Manufacture of chemical fiber

11 Manufacture of special purpose machinery 11 Manufacture of nonmetallic mineral products12 Manufacture of metal products 12 Manufacture and processing of ferrous metals13 Manufacture of leather fur feather and their products 13 Mining and washing of coal14 Extraction of petroleum and natural gas 14 Mining and processing of nonmetal ores

15 Processing of timbers and manufacture of wood bamboorattan palm and straw 15 Manufacture of paper and paper products

16 Manufacture of rubber and plastic 16 Production and supply of electric power and heat power17 Manufacture of medicines 17 Mining of ferrous metal ores

18 Mining of nonferrous metal oresSource of date China Industry Economy Statistical Yearbook

of industrial transformation There are more than a dozenexogenous parameters in steady state equations which havecomplex nonlinear relationship Therefore we analyze theexistence of the technological innovation incentive effectand the technology spillover effect and the mechanism ofenvironmental regulation on industrial transformation bysimulation computation method with MATLAB software

1198841= Φ011986011198701205721

11198711205731

11198641205741

1

11988421198752120601120588312058841198701205884minus1

119903119889

12060112058831198701205884

119903119889+ 1

= minus120591 (120601)12058851198641205886

2

(12060112058831198701205884

119903119889+ 1)2120601120588312058841198701205884minus1

119903119889

+ 119903119903119889

minus ]0

1198842= (120601120588

31198701205884

119903119889+ 1)119860

21198701205722

21198711205732

21198641205742

2

119862minus1205902

2=

119862minus1205901

1

1198751

1198752

119864 = 11986031198701205723

31198711minus1205723

3

1198711+ 1198712+ 1198713= 1

(26)

26 Calibration of Parameters

(1)The Division of Cleaning Industries and Pollution-IntensiveIndustries The division standard of industrial sectors isin accordance with ldquoChina Industry Economy StatisticalYearbookrdquo To be sure because the data is missing partly inManufacture of Artwork and Other Manufacture recycling

and processing of waste resource and old materials andMining of Other Ores we remove these subindustries Inaddition we incorporate manufacture of plastic and manu-facture of rubber to maintain consistent statistical standarddue to industrial classification standard changed in differentyears After the adjustment we get 35 subindustries Furtherall the industries are divided into cleaning industries andpollution-intensive industries based on the median of thepollution emission intensity The calculation of the pollutionemission intensity (EMI) is as follows

A To calculate pollutant emissions per unit of outputin each sector namely 119880119864

119894119895= 119864119894119895119884119894 where 119864

119894119895is

pollutant emission 119895 of sector 119894 119884119894is gross value of

industrial output in each sectorB To standardize pollutant emissions per unit of output

in each industry

1198801198641015840

119894119895=

119880119864119894119895minusmin (119880119864

119895)

max (119880119864119895) minusmin (119880119864

119895)

(27)

where 119880119864119894119895

denotes pollutant emissions per unitof output in each sector max(119880119864

119895) and min(119880119864

119895)

denote the maximum and minimum of pollutantemission 119895 across all industries respectively 1198801198641015840

119894119895is

standardized value of pollutant emission per unit ofoutput in each industry

C To calculate weighted average of standardized value ofpollutant emission we can obtain industry pollutionemission intensityThe division of cleaning industriesand pollution-intensive industries is shown in Table 1


Table 2 The estimated results of the production function and technological progress rate

Parameters

(1) (2) (3) (4)Pollution-intensity

industries Cleaning industries Energy industries Technological progress rate incleaning industries

ln1198841119905

ln1198842119905

ln1198643119905

lnΦ119905

ln119870119895119905

05269lowastlowastlowast(01029)




ln 119871119895119905

00636lowast(00365)

01898lowastlowast(00754)


ln119864119895119905



119862minus27246lowastlowast(10437)

minus15689lowastlowast(06292)



Note standard errors in parentheses lowastlowastlowast119901 lt 001 lowastlowast119901 lt 005 lowast119901 lt 01

(2) Environmental Regulation Intensity Environmental reg-ulation is measured from 6 dimensions in the previousliterature [11] First is the type of environmental regulationpolicy Second is the proportion of investment of pollutiontreatment in total cost or output value Third is running costof pollution control facilities Fourth is the per capita incomeFifth is the number of governmentsrsquo inspection Sixth is thevolume of pollution emissions Considering the availabilityof industry data we select running cost of pollution controlfacilities as the measurement of environmental regulationintensity According to Shen [13] we choose the proportion ofrunning cost of pollution control that accounts for industrialoutput as a proxy The total running cost of pollution controlis the sumof running cost of wastewater andwaste gas controlin each sector The data source of environmental variablesis ldquoChina Environment Statistical Yearbookrdquo and the datasource of industrial output is ldquoChina Industrial EconomicStatistical Yearbookrdquo

(3) The Estimation of Production Function in Pollution-Intensity Industries and Cleaning Industries We estimatethe production functions of cleaning industries pollution-intensity industries and energy industries (here we usemining and washing of coal to substitute energy industries)based on panel data in 30 provinces (excluding Tibet) from2002 to 2012 And we decompose total factor productivityto get technological progress rate and do regression analysisbetween technological progress rate and RampD investment incleaning industries

The regression results are shown in Table 2

(4) The Estimation of the Function of Pollution EmissionsSince the data of waste water and solid waste are missingpartly we select the volume of SO

2emissions as a proxy

in pollution-intensity industries and cleaning industries Weconstruct the regression equation in which energy consump-tion is independent variable and the volume of pollutionemissions is dependent variable

The results are shown in Table 3

(5)TheOther Parameters in theModel Because it is difficult tocollect the data of government green purchase and consump-tion we set up the other parameters based onDong et al [16]

Table 3The estimated results of the function of pollution emissions

Parameters

(1) (2)Pollution-intensity

industries Cleaning industries

ln1198641198721119905

ln1198641198722119905

lnΦ119895119905

minus00102(01160)

minus00156lowast(00087)

ln119864119895119905





Note standard errors in parentheses lowastlowastlowast119901 lt 001 lowast119901 lt 01

Acemoglu et al [17] and Huang and Lin [18] The settings ofparameters are as follows 120573 = 099 120579

1= 68 120579

2= 0015

1205751= 02 120575

2= 015 120575

119903119889= 02 120575

3= 02 120590

1= 5 and 120590

2= 4

3 The Policy Simulation

31 The Impact of Command-Control Environmental Regula-tion on the Industrial Transformation

(1) Incentive Effects of Technological Innovation Figure 1 is acomparison of the existence situation related to technologicalinnovation incentive effects of the environmental regulationintensity in different types of the industry As shown inFigure 1 the enhancement of the environmental regulationintensity does not affect the level of environmental technol-ogy as for pollution-intensive industries but promotes thecleaning industries to enhance their level of the environ-mental technology It means that technological innovationincentive effects of the environmental regulation intensitydo not exist in terms of pollution-intensive industries whilethey exist in the cleansing industries The cause of this phe-nomenon is the difference of the cost input model betweenthese two types of industry

(2) Technology Spillover Effect Figure 2 is a comparison ofthe existence situation related to technology spillover effectsof the environmental regulation intensity in different types


098

100

102

104

106

108

110

112

Tech

nica

l pro

cess

of p

ollu

tion-

inte

nsiv

e ind

ustr

y

Environmental regulation intensity

118360

118365

118370

118375

118380

118385

118390

118395

Tech

nica

l pro

cess

of c

lean

ing

indu

stry

Environmental regulation intensity014 016 018 020 022 024 026 028 030012014 016 018 020 022 024 026 028 030012

Figure 1 The existence analysis of technological innovation incentive effects of command-control environmental regulation

164

168

172

176

180

184

188

192

TFP

of p

ollu

tion-

inte

nsiv

e ind

ustr

y

Environmental regulation intensity Environmental regulation intensity

119540

119545

119550

119555

119560

119565

119570

119575TF

P of

clea

ning

indu

stry

014 016 018 020 022 024 026 028 030012014 016 018 020 022 024 026 028 030012

Figure 2 The existence analysis of technology spillover effects of command-control environmental regulation

of the industry As shown in Figure 2 the enhancement ofthe environmental regulation intensity does not affect thetotal factor productivity as for pollution-intensive industriesbut leads to the increase of the total factor productivity incleaning industries It means that technology spillover effectsof the environmental regulation intensity do not exist inthe pollution-intensive industries while they exist in thecleansing industries

(3) The Impact of Command-Control Environmental Reg-ulation on the Industrial Transformation Figure 3 is theimpact of the command-control environmental regulationon the industrial transformation As shown in Figure 3when the environmental regulation intensity is enhancedthose enterprises will afford heavier tax if they increasepollution emissions Since the environmental technologyof contaminative enterprises is relatively fixed without anyother responses except reducing the yield the pollution-intensive industries still carry out the original mode ofproduction but the equilibrium will be moved down alongthe original production function However the cleansingindustries have the subjective initiative in the process of tax

014 016 018 020 022 024 026 028 030012Environmental regulation intensity

0972

0976

0980

0984

0988

0992

0996

Indu

stry

tran

sform

atio

n

Figure 3 The impact of command-control environmental regula-tion on the industrial transformation

cost raise Reduction of yield cannot bring the marketingcompetitive edge for cleansing industries under the conditionof environmental tax Thus the cleansing industries need toincrease the research input of environmental technology to


Technical progress of cleaning industryTechnical progress of pollution-intensive industry


13 14 15 16 17 18 1912RampD subsidies of environmental technology

013 014008 009 010 011 012006 007005Environmental tax

104

108

112

116

120

124

104

106

108

110

112

114

116

118

120

Figure 4 The existence analysis of technological innovation incentive effects of market incentives environmental regulation

TFP of cleaning industry TFP of pollution-intensive industry


11

12

13

14

15

16

17

18

11

12

13

14

15

16

17

18



Figure 5 The existence analysis of technology spillover effects of market incentives environmental regulation

decrease the tax burden of environmental tax Meanwhilewhen the environmental regulation intensity is enhanced thecleansing industries will accelerate the RampD and innovationof technology enhance the productivity increase the outputand upgrade the industrial structural transformation forobtaining the competitive edge

32 The Impact of Market Incentives Environmental Regula-tion on the Industrial Transformation

(1) Incentive Effects of Technological Innovation Figure 4 is acomparison of the existence situation related to technologicalinnovation incentive effects of themarket incentives environ-mental regulation in different types of the industry As shownin Figure 4 the enhancement of the environmental tax andsubsidies of environmental technology RampD do not affect thelevel of environmental technology as for pollution-intensive

industries but promote the cleaning industries to enhancetheir level of the environmental technology It means thattechnological innovation incentive effects of the marketincentives environmental regulation do not exist in termsof pollution-intensive industries while they exist in thecleansing industries In addition technological innovationincentive effects of subsidies of environmental technologyRampD should be higher than that of the environmental tax

(2) Technology Spillover Effect Figure 5 is a comparison ofthe existence situation related to technology spillover effectsof market incentives environmental regulation in differenttypes of the industry As shown in Figure 5 the enhancementof the environmental tax and subsidies of environmentaltechnology RampD do not affect the total factor productivity asfor pollution-intensive industries but lead to the increase ofthe total factor productivity in cleaning industries It means


0975

0980

0985

0990

0995

1000

1005

Indu

stria

l tra

nsfo

rmat

ion

09864

09868

09872

09876

09880

09884In

dustr

ial t

rans

form

atio

n



Figure 6 The impact of market incentives environmental regulation on the industrial transformation

that technology spillover effects of the market incentivesenvironmental regulation do not exist in terms of pollution-intensive industries while they exist in the cleansing indus-tries In addition technology spillover effects of subsidies ofenvironmental technology RampD should be higher than thatof the environmental tax

(3)The Impact of Market Incentives Environmental Regulationon the Industrial Transformation Figure 6 is the impactof the market incentives environmental regulation on theindustrial transformation As shown in Figure 6 the riseof environmental tax will increase the environmental costof enterprises Since the environmental technology of con-taminative enterprises is relatively fixed without any otherresponses except reducing the yield the pollution-intensiveindustries still carry out the original mode of productionbut the equilibrium will be moved down along the originalproduction function However the cleaning industries havesubjective initiative to deal with environmental tax Reduc-tion of yield cannot bring the marketing competitive edge forcleaning industries under the condition of environmental taxThus the cleansing industries need to increase the researchinput of environmental technology to decrease the tax bur-den of environmental tax Nevertheless the motivation ofenvironmental technology innovation is dependent on therelationship between the cost of environmental tax and thecost of environmental technology innovation In the longrun the cost of environmental tax cleansing industries thatthe cleansing industries required to pay is inevitably higherthan the cost of environmental technology innovation Thetechnology innovation of cleansing industries will bring thequality improvement of cleaning products and upgradingof the industry Overall the real GDP is decreased thecleansing industries have been developing gradually whereasthe pollution-intensive industries have been shrinking Thetransformation of industrial structure has been accelerated

The subsidies of environmental technology RampD rise andthe cost of environmental technology RampD for cleansingindustries reduced so that cleansing industries aspire toincrease the input of environmental technology RampD topromote its improvement The environmental technology

spillover effects of cleansing industries can improve theenterprisesrsquo productivity and extend the yield scale since thehuman resources are trained and the level of management isdevelopedThe increase of capital accumulation portion of allthe output in terms of cleansing industries causes the increaseof the real GDP Correspondingly the part of capital accu-mulation for pollution-intensive industries will be increasedtoo due to the wealth effect that leads to the output increaseHowever the growth of cleansing products output brought bythe improvement of environmental technology of cleansingindustries exceeds that of pollution-intensive industries sothe industrial structure transformation is upgraded

Generally speaking both incentive effects of technolog-ical innovation and technology spillover effect exist in thecleansing industries while both of them do not exist in thepollution-intensive industries Meanwhile the environmen-tal regulation policies assist in improving the transformationof industrial structure There are two influent channelsFirst the enhancement of environmental regulation intensityresults in the cost increase of pollution emission as forpollution-intensive industries In the short term pollution-intensive industries may increase factor input to make up forthe loss of pollution emission but in the long term theseindustries can onlymaximize the operating profit by reducingthe production scale Second under the enhancement ofenvironmental regulation intensity the cleansing industrieswill improve its level of environmental technology Technol-ogy spillover effects will extend the production scale for thecleansing industries which promote the transformation ofindustrial structure

4 Conclusion

In this paper the entire industries are divided into two partscleaning industries and pollution-intensive industries Weconstructed a mathematical model and conducted numer-ical simulation the results indicated that the impact thatenvironmental regulation has on industrial transformationpresents comparison of distortion effect of resource alloca-tion and technology effect Environmental regulation will


promote industrial transformation when technology effectof environmental regulation is stronger than the distortioneffect of resources allocation Particularly command-controlenvironmental regulation has a significant incentive effectand spillover effect of technological innovation on cleaningindustries but these effects do not exist in pollution-intensiveindustries Command-control environmental regulation pro-motes industrial transformation The results of simulationto market incentives environmental regulation are similar tocommand-control environmental regulation

According to the conclusion we suggest that the gov-ernment should improve the mechanism of investment andfinancing gradually widen the ways of financing acceleratethe process of financial reform and attract private capitalinto cleaning industries to support the development ofcleaning industries to produce technology spillover effectThe government should set up the appropriate environmentaccess standards to guide the environment control and realizethe pollution source management for pollution-intensiveindustryThe government should combine market incentivesenvironmental regulation and command-control environ-mental regulation effectively to guide cleaning industries toenvironment governance and improve the effectiveness ofenvironmental regulation

Competing Interests

The authors declare that they have no competing interests

References

[1] M E Porter ldquoAmericarsquos green strategyrdquo Scientific American vol264 no 4 p 168 1991

[2] M E Porter and C Van Der Linde ldquoToward a new conceptionof the environment-competitiveness relationshiprdquo Journal ofEconomic Perspectives vol 9 no 4 pp 97ndash118 1995

[3] A B Jaffe and K Palmer ldquoEnvironmental regulation andinnovation a panel data studyrdquo Review of Economics andStatistics vol 79 no 4 pp 610ndash619 1997

[4] P Lanoie J Laurent-Lucchetti N Johnstone and S AmbecldquoEnvironmental policy innovation and performance newinsights on the porter hypothesisrdquo Journal of Economics andManagement Strategy vol 20 no 3 pp 803ndash842 2011

[5] S Ambec M A Cohen S Elgie and P Lanoie ldquoThe PorterHypothesis at 20 can environmental regulation enhance inno-vation and competitivenessrdquo Review of Environmental Eco-nomics and Policy vol 7 no 1 pp 2ndash22 2013

[6] K Blind ldquoThe influence of regulations on innovation a quanti-tative assessment for OECD countriesrdquo Research Policy vol 41no 2 pp 391ndash400 2012

[7] Y J Yuan and R H Xie ldquoResearch on the effect of environmen-tal regulation to industrial restructuring empirical test based onprovincial panel data of ChinardquoChina Industrial Economics no8 pp 57ndash69 2014

[8] Q Li ldquoEnvironmental regulation and industrial structureadjustment the theoretical analysis and empirical study basedon Baumol modelrdquo Economics Review no 5 pp 100ndash107 2013

[9] T Li ldquoEnvironmental regulation service industry developmentand industrial restructuringrdquo Economic Management no 8 pp1ndash10 2013

[10] X J Bai and Y Song ldquoEnvironment regulation technologyinnovation and efficiency improvement of Chinese thermalpower industryrdquo China Industrial Economics no 8 pp 68ndash772009

[11] C Zhang Y Lu L Guo and T S Yu ldquoThe intensity of environ-mental regulation and technological progress of productionrdquoEconomic Research Journal no 2 pp 113ndash124 2011

[12] L Li and F Tao ldquoSelection of optimal environmental regulationintensity for Chinese manufacturing industrymdashbased on thegreen TFP perspectiverdquo China Industrial Economics no 5 pp70ndash82 2012

[13] N Shen ldquoEnvironmental efficiency industrial heterogeneityand intensity of optimal regulationmdashnonlinear test based onindustrial panel-datardquo China Industrial Economics no 3 pp56ndash68 2012

[14] M Y Xu and H P Zuo ldquoStudy on the relationship betweenenvironmental regulation and industrial competitiveness underagglomeration effect porterHypothesis re-examinationrdquoChinaIndustrial Economics no 3 pp 72ndash84 2013

[15] P Y Nie and L Huang ldquoAn empirical study of environmentalregulationrsquos different impact on industrial total factor energyproductivityrdquo Industrial Economics Research no 4 pp 50ndash582013

[16] Z Q Dong X Cai and L H Wang ldquoThe direction of technicalchange urban land size and environment qualityrdquo EconomicResearch Journal no 10 pp 111ndash124 2014

[17] D Acemoglu P Aghion L Bursztyn and D Hemous ldquoTheenvironment and directed technical changerdquo American Eco-nomic Review vol 102 no 1 pp 131ndash166 2012

[18] M X Huang and S F Lin ldquoPollution damage environmentalmanagement and sustainable economic growthmdashbased on theanalysis of five-department endogenous growth modelrdquo Eco-nomics Research no 12 pp 30ndash41 2013

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

MathematicsJournal of


Mathematical Problems in Engineering

Hindawi Publishing Corporationhttpwwwhindawicom

Differential EquationsInternational Journal of

Volume 2014

Applied MathematicsJournal of


Probability and StatisticsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of


Mathematical PhysicsAdvances in

Complex AnalysisJournal of


OptimizationJournal of


CombinatoricsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of


Operations ResearchAdvances in

Journal of


Function Spaces

Abstract and Applied AnalysisHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of Mathematics and Mathematical Sciences


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014


Algebra

Discrete Dynamics in Nature and Society



Decision SciencesAdvances in

Discrete MathematicsJournal of


Volume 2014 Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Stochastic AnalysisInternational Journal of


technology for pollution-intensive industries when envi-ronmental regulation intensity increases Pollution-intensiveindustries may augment production factors input to offsetenvironmental regulation cost which will cause a distortioneffect of resource allocation In contrast it is easier tochange technology for cleaning industries when environmen-tal regulation intensity increases Cleaning industries willincrease RampD investment to improve technology to avoidenvironmental regulation cost which will cause incentiveeffects and spillover effects of technological innovationTherefore the increase of environmental regulation inten-sity ultimately drives the adjustment of industrial structure[7]

Many literatures focused on the effect of environmen-tal regulation on industrial structure transformation fromproportion of the third industry and secondary industryperspective [8 9] Li [8] addressed environmental regulationswhich will improve the proportion of the service sectorrelative to the industrial sector and promote the adjustmentof industrial structure The previous literatures were moreconcerned with the incentive effect of environmental regula-tion on technological innovation within the industrial sectorFor instance Bai and Song [10] found that environmentalregulation can improve the efficiency of Chinese thermalpower as a whole and cause incentive effects of technologicalinnovation Zhang et al [11] conducted an empirical test onindustrial sectors of 30 provinces in China and found that theeffect of environmental regulation on technological progressrate is different among different regions In recent yearsmanyresearchers found that industrial heterogeneity plays a veryimportant role in the relationship between environmentalregulation and technological innovation but the conclusionis not consistent [12ndash15] Li and Tao [12] indicated environ-mental regulation intensity of heavy pollution industry canpromote the industrial green total factor productivity theenvironmental regulation intensity of the moderate pollutionindustry is weak and technological innovation can be earlybreakthrough ldquoUrdquo inflection point for light pollution indus-try Nie and Huang [15] found the current strength of envi-ronmental regulation hinders the improvement of moderateenergy-intensive industries in total factor energy productiv-ity technological innovation and efficiency improvementshighly energy-intensive industriesrsquo environmental regulatoryintensity does not significantly influence the total factorenergy productivity for themild energy-intensive industriesthe intensity of environmental regulation promotes techno-logical innovation

The existing literatures mostly focused on the effectof environmental regulation on industrial structure at thecountry or region level and paid little attention to theimpact of environmental regulation on industrial transfor-mation inside the industrial sector In the meantime thestructure of factors input may cause different response toenvironmental regulation in pollution-intensive industriesand cleaning industriesTherefore we construct a theoreticalmodel to analyze different effect of environmental regulationon heterogeneity industries in this paper Then we conduct asimulation to examine the effect of different environmentalregulation policy and put forward some suggestion

2 The Mathematical Model

Environmental regulation includes command-control andmarket incentive regulation In this paper we select environ-mental regulation intensity as a proxy of command-controlenvironmental regulation environment tax and environ-mental technology subsidies as a proxy of market incentiveenvironmental regulation Further we assume that tech-nology is relatively fixed for pollution-intensive industriesbut environmental technology will continue to change forcleaning industries in the process of production Pollution-intensive industries are likely to increase inputs to offset thecost of regulation when environmental regulation intensityincreases namely the distortion effect of resource allocationAnd cleaning industries will promote the environmentaltechnology namely the incentive effect of technologicalinnovation At the same time the technology change willmake organization structure and management mode changefurther eventually leading to improvements in total factorproductivity namely technology spillover effect In shortthe distortion effect of resources allocation represents thedistortion of environmental regulation moreover incentiveeffect and spillover effect of technological innovation reflectthe externality of environment regulation When distortioneffect of environmental regulation is bigger than the exter-nality (namely the benefit that pollution-intensive industriesaccept tax punishment and increase factors input is higher)environmental regulation will inhibit industrial transforma-tion When the externality of environmental regulation isgreater than distortion effect (namely incentive effect andspillover effect of technology innovation for cleaning industryis higher) environmental regulation will promote industrialtransformation In the following section the dynamic generalequilibrium model is selected to analyze the mechanism

21 The Effect of Environmental Regulation on Pollution-Intensive Industries The capital labor and environmentalresources are input in the process of production in pollution-intensive industry Because of consumption of environ-mental resources pollution emissions will be producedHere environmental resources include fossil energy andother natural resources for instance soil and water andair As mentioned above pollution-intensive industries arerestricted by replacement cost of machinery and equipmentso environmental technology is relatively fixed which canonly accept tax penalties Therefore the production functionin pollution-intensive industries is as follows

1198841119905= Φ011986011199051198701205721

11199051198711205731

11199051198641205741

1119905 (1)

where Φ0

denotes fixed environmental technology inpollution-intensive industries 119860

1119905represents total factor

productivity 1198701119905 1198711119905 and 119864

1119905denote capital labor and

environmental resource respectivelyThe function of pollution emission in pollution-intensive

industries is as follows

1198641198721119905= Ψ (Φ

0 1198641119905) =

12058811198641205882

1119905

Φ0

(2)








1199051198641119905minus 120591 (120601) 119864119872

1119905 (3)




12057211198751119905Φ011986011199051198701205721minus1

11199051198711205731

11199051198641205741

1119905= 1199031119905

(4)

1205731119875111990511986011199051198701205721

11199051198711205731minus1

11199051198641205741

1119905= 120596119905

(5)

12057411198751119905Φ011986011199051198701205721

11199051198711205731

11199051198641205741minus1

1119905minus 119875119890

119905minus 120591 (120601)

120588112058821198641205882minus1

1119905

Φ0

= 0 (6)




1198842119905= Φ (120601

119905 119870119903119889119905

) 11986021199051198701205722

21199051198711205732

21199051198641205742

2119905

Φ(120601119905 119870119903119889119905

) = 12060111990512058831198701205884

119903119889119905+ Φ1

(7)



120601(120601 119870119903119889119905

) gt 0 and Φ1015840

119870(119889 119870119903119889119905


1198702119905 1198712119905 and 119864




1198641198722119905= Ψ (Φ

119905 1198642119905) =

12058851198641205886

2119905

Φ119905

(8)







1199051198642119905minus 120591 (120601) 119864119872

2119905

minus (119903119903119889119905

minus ]0)119870119903119889119905

(9)




12057221198752119905Φ(120601119905 119870119903119889119905

) 11986021199051198701205722minus1

21199051198711205732

21199051198641205742

2119905= 1199032119905

(10)

12057321198752119905Φ(120601119905 119870119903119889119905

) 11986021199051198701205722

21199051198711205732minus1

21199051198641205742

2119905= 120596119905

(11)

12057421198752119905Φ(120601119905 119870119903119889119905

) 11986021199051198701205722

21199051198711205732minus1

21199051198641205742minus1

2119905minus 119875119890

119905

minus 120591 (120601)

120588512058861198641205886minus1

2119905

Φ119905

= 0

(12)

1198752119905120601119905120588312058841198701205884minus1

11990311988911990511986021199051198701205722

21199051198711205732

21199051198641205742

2119905

+ 120591 (120601)

12058851198641205886

2119905

Φ2

119905

120601119905120588312058841198701205884minus1

119903119889119905minus (119903119903119889119905

minus ]0) = 0

(13)





119864119905= 11986031199051198701205723

31199051198711minus1205723

3119905 (14)


Π3119905= 119875119890

119905119864119905minus 11990331199051198703119905minus 1199081199051198713119905 (15)


1205723119875119890

11990511986031199051198701205723minus1

31199051198711minus1205723

3119905= 1199033119905

(1 minus 1205723) 119875119890

11990511986031199051198701205723

3119905119871minus1205723

3119905= 120596119905

(16)



maxinfin

sum

119905=0

(1198621minus1205901

1119905

1 minus 1205901

+ 1205771198621minus1205902

2119905

1 minus 1205902

) (17)

where 1205901and 120590



11987511199051198621119905+ 11987521199051198622119905+ 119876119905119878119905+ Π119905119866119905

le 11990311199051198701119905+ 11990321199051198702119905+ 119903119903119889119905

119870119903119889119905

+ 11990331199051198703119905+ 119908119905119871119905

119878119905= 1198781205791

11199051198781minus1205791

2119905

119876119905= (

1198751119905

1205791

)

1205791

(1198752119905

1 minus 1205791

)

1minus1205791

119866119905= 1198661205792

11199051198661minus1205792

2119905

Π119905= (

1198751119905

1205792

)

1205792

(1198752119905

1 minus 1205792

)

1minus1205792

(18)

where 1198781119905and 119878



1119905and 119878

2119905


119905is

the price of 119878119905 1198661119905and 119866



1198661119905and 119866





119862minus1205901

1119905= 1205821199051198751119905

(19)

120577119862minus1205902

2119905= 1205821199051198752119905

(20)

120573120582119905+1

1199031119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205751) = 0 (21)

120573120582119905+1

1199032119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205752) = 0 (22)

120573120582119905+1

119903119903119889119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 120575119903119889) = 0 (23)

120573120582119905+1

1199033119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205753) = 0 (24)



STR =1198842

1198841

(25)


1119905 1198711119905 1198641119905 1198702119905

1198712119905 1198642119905 1198703119905 and 119871



2 119875119890 120596 119870

119903119889

1198641 and 119864














1198841= Φ011986011198701205721

11198711205731

11198641205741

1

11988421198752120601120588312058841198701205884minus1

119903119889

12060112058831198701205884

119903119889+ 1

= minus120591 (120601)12058851198641205886

2

(12060112058831198701205884

119903119889+ 1)2120601120588312058841198701205884minus1

119903119889

+ 119903119903119889

minus ]0

1198842= (120601120588

31198701205884

119903119889+ 1)119860

21198701205722

21198711205732

21198641205742

2

119862minus1205902

2=

119862minus1205901

1

1198751

1198752

119864 = 11986031198701205723

31198711minus1205723

3

1198711+ 1198712+ 1198713= 1

(26)





119894119895= 119864119894119895119884119894 where 119864

119894119895is



in each industry

1198801198641015840

119894119895=

119880119864119894119895minusmin (119880119864

119895)

max (119880119864119895) minusmin (119880119864

119895)

(27)

where 119880119864119894119895


119895) and min(119880119864

119895)


119894119895is





Parameters



ln1198841119905

ln1198842119905

ln1198643119905

lnΦ119905

ln119870119895119905





ln 119871119895119905

00636lowast(00365)



ln119864119895119905

















Parameters



ln1198641198721119905

ln1198641198722119905

lnΦ119895119905

minus00102(01160)


ln119864119895119905







1= 68 120579

2= 0015

1205751= 02 120575

2= 015 120575

119903119889= 02 120575

3= 02 120590

1= 5 and 120590

2= 4






098

100

102

104

106

108

110

112

Tech

nica

l pro

cess

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


118360

118365

118370

118375

118380

118385

118390

118395

Tech

nica

l pro

cess

of c

lean

ing

indu

stry



164

168

172

176

180

184

188

192

TFP

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


119540

119545

119550

119555

119560

119565

119570

119575TF

P of

clea

ning

indu

stry

014 016 018 020 022 024 026 028 030012014 016 018 020 022 024 026 028 030012





0972

0976

0980

0984

0988

0992

0996

Indu

stry

tran

sform

atio

n








104

108

112

116

120

124

104

106

108

110

112

114

116

118

120




11

12

13

14

15

16

17

18

11

12

13

14

15

16

17

18










0975

0980

0985

0990

0995

1000

1005

Indu

stria

l tra

nsfo

rmat

ion

09864

09868

09872

09876

09880

09884In

dustr

ial t

rans

form

atio

n









4 Conclusion





Competing Interests


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra
















1199051198641119905minus 120591 (120601) 119864119872

1119905 (3)




12057211198751119905Φ011986011199051198701205721minus1

11199051198711205731

11199051198641205741

1119905= 1199031119905

(4)

1205731119875111990511986011199051198701205721

11199051198711205731minus1

11199051198641205741

1119905= 120596119905

(5)

12057411198751119905Φ011986011199051198701205721

11199051198711205731

11199051198641205741minus1

1119905minus 119875119890

119905minus 120591 (120601)

120588112058821198641205882minus1

1119905

Φ0

= 0 (6)




1198842119905= Φ (120601

119905 119870119903119889119905

) 11986021199051198701205722

21199051198711205732

21199051198641205742

2119905

Φ(120601119905 119870119903119889119905

) = 12060111990512058831198701205884

119903119889119905+ Φ1

(7)



120601(120601 119870119903119889119905

) gt 0 and Φ1015840

119870(119889 119870119903119889119905


1198702119905 1198712119905 and 119864




1198641198722119905= Ψ (Φ

119905 1198642119905) =

12058851198641205886

2119905

Φ119905

(8)







1199051198642119905minus 120591 (120601) 119864119872

2119905

minus (119903119903119889119905

minus ]0)119870119903119889119905

(9)




12057221198752119905Φ(120601119905 119870119903119889119905

) 11986021199051198701205722minus1

21199051198711205732

21199051198641205742

2119905= 1199032119905

(10)

12057321198752119905Φ(120601119905 119870119903119889119905

) 11986021199051198701205722

21199051198711205732minus1

21199051198641205742

2119905= 120596119905

(11)

12057421198752119905Φ(120601119905 119870119903119889119905

) 11986021199051198701205722

21199051198711205732minus1

21199051198641205742minus1

2119905minus 119875119890

119905

minus 120591 (120601)

120588512058861198641205886minus1

2119905

Φ119905

= 0

(12)

1198752119905120601119905120588312058841198701205884minus1

11990311988911990511986021199051198701205722

21199051198711205732

21199051198641205742

2119905

+ 120591 (120601)

12058851198641205886

2119905

Φ2

119905

120601119905120588312058841198701205884minus1

119903119889119905minus (119903119903119889119905

minus ]0) = 0

(13)





119864119905= 11986031199051198701205723

31199051198711minus1205723

3119905 (14)


Π3119905= 119875119890

119905119864119905minus 11990331199051198703119905minus 1199081199051198713119905 (15)


1205723119875119890

11990511986031199051198701205723minus1

31199051198711minus1205723

3119905= 1199033119905

(1 minus 1205723) 119875119890

11990511986031199051198701205723

3119905119871minus1205723

3119905= 120596119905

(16)



maxinfin

sum

119905=0

(1198621minus1205901

1119905

1 minus 1205901

+ 1205771198621minus1205902

2119905

1 minus 1205902

) (17)

where 1205901and 120590



11987511199051198621119905+ 11987521199051198622119905+ 119876119905119878119905+ Π119905119866119905

le 11990311199051198701119905+ 11990321199051198702119905+ 119903119903119889119905

119870119903119889119905

+ 11990331199051198703119905+ 119908119905119871119905

119878119905= 1198781205791

11199051198781minus1205791

2119905

119876119905= (

1198751119905

1205791

)

1205791

(1198752119905

1 minus 1205791

)

1minus1205791

119866119905= 1198661205792

11199051198661minus1205792

2119905

Π119905= (

1198751119905

1205792

)

1205792

(1198752119905

1 minus 1205792

)

1minus1205792

(18)

where 1198781119905and 119878



1119905and 119878

2119905


119905is

the price of 119878119905 1198661119905and 119866



1198661119905and 119866





119862minus1205901

1119905= 1205821199051198751119905

(19)

120577119862minus1205902

2119905= 1205821199051198752119905

(20)

120573120582119905+1

1199031119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205751) = 0 (21)

120573120582119905+1

1199032119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205752) = 0 (22)

120573120582119905+1

119903119903119889119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 120575119903119889) = 0 (23)

120573120582119905+1

1199033119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205753) = 0 (24)



STR =1198842

1198841

(25)


1119905 1198711119905 1198641119905 1198702119905

1198712119905 1198642119905 1198703119905 and 119871



2 119875119890 120596 119870

119903119889

1198641 and 119864














1198841= Φ011986011198701205721

11198711205731

11198641205741

1

11988421198752120601120588312058841198701205884minus1

119903119889

12060112058831198701205884

119903119889+ 1

= minus120591 (120601)12058851198641205886

2

(12060112058831198701205884

119903119889+ 1)2120601120588312058841198701205884minus1

119903119889

+ 119903119903119889

minus ]0

1198842= (120601120588

31198701205884

119903119889+ 1)119860

21198701205722

21198711205732

21198641205742

2

119862minus1205902

2=

119862minus1205901

1

1198751

1198752

119864 = 11986031198701205723

31198711minus1205723

3

1198711+ 1198712+ 1198713= 1

(26)





119894119895= 119864119894119895119884119894 where 119864

119894119895is



in each industry

1198801198641015840

119894119895=

119880119864119894119895minusmin (119880119864

119895)

max (119880119864119895) minusmin (119880119864

119895)

(27)

where 119880119864119894119895


119895) and min(119880119864

119895)


119894119895is





Parameters



ln1198841119905

ln1198842119905

ln1198643119905

lnΦ119905

ln119870119895119905





ln 119871119895119905

00636lowast(00365)



ln119864119895119905

















Parameters



ln1198641198721119905

ln1198641198722119905

lnΦ119895119905

minus00102(01160)


ln119864119895119905







1= 68 120579

2= 0015

1205751= 02 120575

2= 015 120575

119903119889= 02 120575

3= 02 120590

1= 5 and 120590

2= 4






098

100

102

104

106

108

110

112

Tech

nica

l pro

cess

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


118360

118365

118370

118375

118380

118385

118390

118395

Tech

nica

l pro

cess

of c

lean

ing

indu

stry



164

168

172

176

180

184

188

192

TFP

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


119540

119545

119550

119555

119560

119565

119570

119575TF

P of

clea

ning

indu

stry

014 016 018 020 022 024 026 028 030012014 016 018 020 022 024 026 028 030012





0972

0976

0980

0984

0988

0992

0996

Indu

stry

tran

sform

atio

n








104

108

112

116

120

124

104

106

108

110

112

114

116

118

120




11

12

13

14

15

16

17

18

11

12

13

14

15

16

17

18










0975

0980

0985

0990

0995

1000

1005

Indu

stria

l tra

nsfo

rmat

ion

09864

09868

09872

09876

09880

09884In

dustr

ial t

rans

form

atio

n









4 Conclusion





Competing Interests


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra












119864119905= 11986031199051198701205723

31199051198711minus1205723

3119905 (14)


Π3119905= 119875119890

119905119864119905minus 11990331199051198703119905minus 1199081199051198713119905 (15)


1205723119875119890

11990511986031199051198701205723minus1

31199051198711minus1205723

3119905= 1199033119905

(1 minus 1205723) 119875119890

11990511986031199051198701205723

3119905119871minus1205723

3119905= 120596119905

(16)



maxinfin

sum

119905=0

(1198621minus1205901

1119905

1 minus 1205901

+ 1205771198621minus1205902

2119905

1 minus 1205902

) (17)

where 1205901and 120590



11987511199051198621119905+ 11987521199051198622119905+ 119876119905119878119905+ Π119905119866119905

le 11990311199051198701119905+ 11990321199051198702119905+ 119903119903119889119905

119870119903119889119905

+ 11990331199051198703119905+ 119908119905119871119905

119878119905= 1198781205791

11199051198781minus1205791

2119905

119876119905= (

1198751119905

1205791

)

1205791

(1198752119905

1 minus 1205791

)

1minus1205791

119866119905= 1198661205792

11199051198661minus1205792

2119905

Π119905= (

1198751119905

1205792

)

1205792

(1198752119905

1 minus 1205792

)

1minus1205792

(18)

where 1198781119905and 119878



1119905and 119878

2119905


119905is

the price of 119878119905 1198661119905and 119866



1198661119905and 119866





119862minus1205901

1119905= 1205821199051198751119905

(19)

120577119862minus1205902

2119905= 1205821199051198752119905

(20)

120573120582119905+1

1199031119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205751) = 0 (21)

120573120582119905+1

1199032119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205752) = 0 (22)

120573120582119905+1

119903119903119889119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 120575119903119889) = 0 (23)

120573120582119905+1

1199033119905+1

minus 120582119905119876119905+ 120573120582119905+1

119876119905+1

(1 minus 1205753) = 0 (24)



STR =1198842

1198841

(25)


1119905 1198711119905 1198641119905 1198702119905

1198712119905 1198642119905 1198703119905 and 119871



2 119875119890 120596 119870

119903119889

1198641 and 119864














1198841= Φ011986011198701205721

11198711205731

11198641205741

1

11988421198752120601120588312058841198701205884minus1

119903119889

12060112058831198701205884

119903119889+ 1

= minus120591 (120601)12058851198641205886

2

(12060112058831198701205884

119903119889+ 1)2120601120588312058841198701205884minus1

119903119889

+ 119903119903119889

minus ]0

1198842= (120601120588

31198701205884

119903119889+ 1)119860

21198701205722

21198711205732

21198641205742

2

119862minus1205902

2=

119862minus1205901

1

1198751

1198752

119864 = 11986031198701205723

31198711minus1205723

3

1198711+ 1198712+ 1198713= 1

(26)





119894119895= 119864119894119895119884119894 where 119864

119894119895is



in each industry

1198801198641015840

119894119895=

119880119864119894119895minusmin (119880119864

119895)

max (119880119864119895) minusmin (119880119864

119895)

(27)

where 119880119864119894119895


119895) and min(119880119864

119895)


119894119895is





Parameters



ln1198841119905

ln1198842119905

ln1198643119905

lnΦ119905

ln119870119895119905





ln 119871119895119905

00636lowast(00365)



ln119864119895119905

















Parameters



ln1198641198721119905

ln1198641198722119905

lnΦ119895119905

minus00102(01160)


ln119864119895119905







1= 68 120579

2= 0015

1205751= 02 120575

2= 015 120575

119903119889= 02 120575

3= 02 120590

1= 5 and 120590

2= 4






098

100

102

104

106

108

110

112

Tech

nica

l pro

cess

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


118360

118365

118370

118375

118380

118385

118390

118395

Tech

nica

l pro

cess

of c

lean

ing

indu

stry



164

168

172

176

180

184

188

192

TFP

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


119540

119545

119550

119555

119560

119565

119570

119575TF

P of

clea

ning

indu

stry

014 016 018 020 022 024 026 028 030012014 016 018 020 022 024 026 028 030012





0972

0976

0980

0984

0988

0992

0996

Indu

stry

tran

sform

atio

n








104

108

112

116

120

124

104

106

108

110

112

114

116

118

120




11

12

13

14

15

16

17

18

11

12

13

14

15

16

17

18










0975

0980

0985

0990

0995

1000

1005

Indu

stria

l tra

nsfo

rmat

ion

09864

09868

09872

09876

09880

09884In

dustr

ial t

rans

form

atio

n









4 Conclusion





Competing Interests


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra




















1198841= Φ011986011198701205721

11198711205731

11198641205741

1

11988421198752120601120588312058841198701205884minus1

119903119889

12060112058831198701205884

119903119889+ 1

= minus120591 (120601)12058851198641205886

2

(12060112058831198701205884

119903119889+ 1)2120601120588312058841198701205884minus1

119903119889

+ 119903119903119889

minus ]0

1198842= (120601120588

31198701205884

119903119889+ 1)119860

21198701205722

21198711205732

21198641205742

2

119862minus1205902

2=

119862minus1205901

1

1198751

1198752

119864 = 11986031198701205723

31198711minus1205723

3

1198711+ 1198712+ 1198713= 1

(26)





119894119895= 119864119894119895119884119894 where 119864

119894119895is



in each industry

1198801198641015840

119894119895=

119880119864119894119895minusmin (119880119864

119895)

max (119880119864119895) minusmin (119880119864

119895)

(27)

where 119880119864119894119895


119895) and min(119880119864

119895)


119894119895is





Parameters



ln1198841119905

ln1198842119905

ln1198643119905

lnΦ119905

ln119870119895119905





ln 119871119895119905

00636lowast(00365)



ln119864119895119905

















Parameters



ln1198641198721119905

ln1198641198722119905

lnΦ119895119905

minus00102(01160)


ln119864119895119905







1= 68 120579

2= 0015

1205751= 02 120575

2= 015 120575

119903119889= 02 120575

3= 02 120590

1= 5 and 120590

2= 4






098

100

102

104

106

108

110

112

Tech

nica

l pro

cess

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


118360

118365

118370

118375

118380

118385

118390

118395

Tech

nica

l pro

cess

of c

lean

ing

indu

stry



164

168

172

176

180

184

188

192

TFP

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


119540

119545

119550

119555

119560

119565

119570

119575TF

P of

clea

ning

indu

stry

014 016 018 020 022 024 026 028 030012014 016 018 020 022 024 026 028 030012





0972

0976

0980

0984

0988

0992

0996

Indu

stry

tran

sform

atio

n








104

108

112

116

120

124

104

106

108

110

112

114

116

118

120




11

12

13

14

15

16

17

18

11

12

13

14

15

16

17

18










0975

0980

0985

0990

0995

1000

1005

Indu

stria

l tra

nsfo

rmat

ion

09864

09868

09872

09876

09880

09884In

dustr

ial t

rans

form

atio

n









4 Conclusion





Competing Interests


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra











Parameters



ln1198841119905

ln1198842119905

ln1198643119905

lnΦ119905

ln119870119895119905





ln 119871119895119905

00636lowast(00365)



ln119864119895119905

















Parameters



ln1198641198721119905

ln1198641198722119905

lnΦ119895119905

minus00102(01160)


ln119864119895119905







1= 68 120579

2= 0015

1205751= 02 120575

2= 015 120575

119903119889= 02 120575

3= 02 120590

1= 5 and 120590

2= 4






098

100

102

104

106

108

110

112

Tech

nica

l pro

cess

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


118360

118365

118370

118375

118380

118385

118390

118395

Tech

nica

l pro

cess

of c

lean

ing

indu

stry



164

168

172

176

180

184

188

192

TFP

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


119540

119545

119550

119555

119560

119565

119570

119575TF

P of

clea

ning

indu

stry

014 016 018 020 022 024 026 028 030012014 016 018 020 022 024 026 028 030012





0972

0976

0980

0984

0988

0992

0996

Indu

stry

tran

sform

atio

n








104

108

112

116

120

124

104

106

108

110

112

114

116

118

120




11

12

13

14

15

16

17

18

11

12

13

14

15

16

17

18










0975

0980

0985

0990

0995

1000

1005

Indu

stria

l tra

nsfo

rmat

ion

09864

09868

09872

09876

09880

09884In

dustr

ial t

rans

form

atio

n









4 Conclusion





Competing Interests


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra










098

100

102

104

106

108

110

112

Tech

nica

l pro

cess

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


118360

118365

118370

118375

118380

118385

118390

118395

Tech

nica

l pro

cess

of c

lean

ing

indu

stry



164

168

172

176

180

184

188

192

TFP

of p

ollu

tion-

inte

nsiv

e ind

ustr

y


119540

119545

119550

119555

119560

119565

119570

119575TF

P of

clea

ning

indu

stry

014 016 018 020 022 024 026 028 030012014 016 018 020 022 024 026 028 030012





0972

0976

0980

0984

0988

0992

0996

Indu

stry

tran

sform

atio

n








104

108

112

116

120

124

104

106

108

110

112

114

116

118

120




11

12

13

14

15

16

17

18

11

12

13

14

15

16

17

18










0975

0980

0985

0990

0995

1000

1005

Indu

stria

l tra

nsfo

rmat

ion

09864

09868

09872

09876

09880

09884In

dustr

ial t

rans

form

atio

n









4 Conclusion





Competing Interests


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra














104

108

112

116

120

124

104

106

108

110

112

114

116

118

120




11

12

13

14

15

16

17

18

11

12

13

14

15

16

17

18










0975

0980

0985

0990

0995

1000

1005

Indu

stria

l tra

nsfo

rmat

ion

09864

09868

09872

09876

09880

09884In

dustr

ial t

rans

form

atio

n









4 Conclusion





Competing Interests


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra










0975

0980

0985

0990

0995

1000

1005

Indu

stria

l tra

nsfo

rmat

ion

09864

09868

09872

09876

09880

09884In

dustr

ial t

rans

form

atio

n









4 Conclusion





Competing Interests


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra












Competing Interests


References


























Volume 2014




Journal of











Journal of


Function Spaces






Algebra
















Volume 2014




Journal of











Journal of


Function Spaces






Algebra









Documents

Research Article How Does Environmental …downloads.hindawi.com/journals/mpe/2016/2405624.pdfintensive industries are likely to increase inputs to o set the cost of regulation when