Open Access Paper
26 September 2024 Impact of environmental regulation on the technological complexity of manufacturing export: empirical analysis using panel data of 30 provinces in China
Xiangxia Liu, Hui Lou
Author Affiliations +
Proceedings Volume 13279, Fifth International Conference on Green Energy, Environment, and Sustainable Development (GEESD 2024) ; 1327949 (2024) https://doi.org/10.1117/12.3044784
Event: Fifth International Conference on Green Energy, Environment, and Sustainable Development, 2024, Mianyang, China
Abstract
This study utilizes panel data spanning from 2004 to 2020 across 30 provinces in China to empirically examine how environmental regulations affect the technological complexity of provincial manufacturing exports. The results indicate that increasing the stringency of environmental regulation is detrimental to enhancing the technological complexity of provincial manufacturing exports. Specifically, enhancing the development level of technology markets helps mitigate the negative impact of environmental regulation on provincial manufacturing export technological complexity. Additionally, higher environmental regulatory stringency in the Central and Western regions tends to increase enterprise costs, thereby hindering the improvement of provincial manufacturing export technological complexity, whereas such effects are not significant in the Eastern region. Therefore, local governments should adopt moderate environmental regulation and create a favorable environment for technology market development, providing tailored policy support based on local conditions.

1.

INTRODUCTION

As global energy resources gradually deplete and ecological environments deteriorate, the manufacturing sector’s heavy reliance on energy and environmental resources becomes unsustainable. To maintain continuous growth in manufacturing exports, the traditional resource-intensive and environmentally damaging model must shift towards green growth, which has become an inevitable choice. Since the strategic conception of shaping a scientific development outlook and building a harmonious society was proposed by the central government in 2001, China has consistently intensified its environmental protection efforts. Successive development strategies have been formulated, including ecological civilization construction and the establishment of a resource-conserving and environmentally friendly society. Consequently, domestic environmental regulation has also become increasingly stringent.

Environmental regulation involves controlling activities that contaminate the public surroundings in order to safeguard the environment1.At present, there is no unanimous agreement among scholars regarding the effects of environmental regulations on exports. Some researchers argue that environmental regulation suppress exports by increasing enterprise costs2,3. Meanwhile, others suggest that under the combined influence of costs and innovation, the relationship between environmental regulation and exports follows a “U”-shaped curve4. This relationship exhibits two states: “U-shaped” and inverted “U-shaped”, depending on factors such as the industry and the type of environmental regulations5,6. In addition, some scholars, based on the “Porter hypothesis,” argue that moderate environmental regulations stimulate enterprises to upgrade their production technologies or optimize their product structures, thereby significantly promoting exports7,8.

Indeed, environmental regulations demonstrate notable regional variations in their impact on exports9. On one hand, while environmental standards are uniformly established nationwide, the specific enforcement intensity varies among provinces. On the other hand, different regions possess varying levels of economic development, resource endowments, and industrial structures, leading to differences in environmental pollution levels. Hence, this study seeks to empirically investigate how the intensity of environmental regulations influences the technological complexity of exports in the manufacturing industries across 30 provinces in China. Furthermore, it aims to analyze the regional disparities in how environmental regulation affects the technological complexity of manufacturing exports.

2.

MODEL SETTING AND VARIABLE EXPLANATION

2.1

Model setting

The basic model can be defined as follows:

00154_PSISDG13279_1327949_page_2_1.jpg

where j and t respectively denote province and year, ln Expyjt represents logarithm of technological complexity of manufacturing export in province j in yeart. SCjt denotes the environmental regulatory intensity in province j in year t, Controls represent control variables, μj represents province fixed effects, λt represents time fixed effects, and εjt represents the random disturbance term.

2.2

Variable explanation and data sources

This study utilizes data from 30 provinces (excluding Tibet) across China spanning the years 2004 to 2020. The export data of HS4 products in each province are sourced from the Foreign Trade Database of DRCNET, while other data are sourced from National Bureau of Statistics and provincial statistical yearbooks.

(1) Technological complexity of manufacturing export (ln Expyjt)

This study utilizes provincial-level export data and provincial-level per capita GDP to calculate technological complexity of manufacturing export across provinces10.

Firstly, technological complexity of product i is calculated using the following formula:

00154_PSISDG13279_1327949_page_2_2.jpg

In equation (2), PRODYi represents technological complexity of product i, xij is export value of product i in province j, xj. is export value of manufacturing in province j, and Yj. represents per capita GDP of province j.

Next, technological complexity of manufacturing export for each province is calculated using the following formula:

00154_PSISDG13279_1327949_page_2_3.jpg

In equation (3), Expyj represents technological complexity of manufacturing export in province j.

(2) Environmental regulatory intensity (SCjt). This paper measures the environmental regulation intensity of each province by using the ratio of industrial pollution control investment to industrial added value. (3) Control variables: Infrastructure level (FRA), measured by the logarithm of total road mileage of each province; Industrialization level (IDL), measured by the ratio of industrial added value to regional GDP; Opening level (lnFDI), measured by the logarithm of actual utilization of regional foreign investment; Fiscal support intensity (GOV), calculated as the ratio of local government fiscal expenditure to regional GDP.

3.

ANALYSIS OF EMPIRICAL RESULTS

3.1

Benchmark regression

This study first regresses the direct effects of environmental regulation on technological sophistication of manufacturing export. As indicated in Table 1, the estimated coefficient of environmental regulation is negative and statistically significant, suggesting a notable inverse relationship between environmental regulation across provinces and technological sophistication of manufacturing export. This is because the rising cost of pollution control has led companies to reduce their investments in research and development and technological innovation to control costs, thus generating a strong “offsetting effect”.

Table 1.

Baseline regression results.

 (1)lnExpy(2)lnExpy(3)lnExpy(4)lnExpy
SC-67.507***-3.885**-14.583**-3.800***
 (9.723)(1.499)(6.230)(1.408)
FRA  0.110***0.116***
   (0.016)(0.035)
IDL  -0.914***0.101
   (0.172)(0.078)
lnFDI  0.247***0.011*
   (0.012)(0.006)
GOV  0.041***0.004***
   (0.003)(0.001)
_cons10.72410.497***5.609***8.892***
 (0.037)(0.006)(0.267)(0.394)
Fixed effects by regionNOYESNOYES
Fixed effects by yearNOYESNOYES
Number510510510510
Coefficient of determination(R2)0.1610.9870.6500.989

Note: Numbers in parentheses within Table 1 denote robust standard errors of the coefficient estimates. Symbols *, **, and *** denote statistical significance at 10%, 5%, and 1% thresholds,

3.2

Further analysis

(1) Introducing interaction terms between environmental regulation and technological market development (SC*Treat). A value of 1 is assigned to provinces with high levels of technological market development, while a value of 0 is assigned to those with low levels. Regions with a proportion of technological market transactions to GDP higher than the average are categorized as areas with a higher level of technological market development, while those below the average are categorized as areas with a lower level. As indicated in Table 2, environmental regulation continues to exert a notably adverse influence on technological complexity of manufacturing export. However, the regression coefficient for the interaction term is significantly positive, indicating that the higher level of technological market development alleviates the adverse effects of environmental regulation on technological sophistication of manufacturing export.

Table 2.

Interaction terms test.

 (1)lnExpy(2)lnExpy(3)lnExpy
SC-3.800***-3.812***-5.228***
 (1.408)(1.418)(1.561)
Treat -0.010-0.039***
  (0.010)(0.014)
SC*Treat  11.530***
   (3.245)
_cons8.892***8.891***9.079***
 (0.394)(0.394)(0.399)
Control VariablesControlControlControl
Fixed effects by regionYESYESYES
Fixed effects by yearYESYESYES
Number510510510
Coefficient of determination R-squared(R2)0.9890.9890.990

Notes: Numbers in parentheses within Table 2 denote robust standard errors of the coefficient estimates. Symbol *** denote statistical significance at 10% thresholds.

(2) To further explore the regional heterogeneity, this study divides the research sample into Eastern regions and CentralWestern regions. As indicated in Table 3, environmental regulation in the Central-Western regions significantly inhibit the enhancement of manufacturing export technological sophistication, whereas their impact in the Eastern regions is not significant.

Table 3.

Regional heterogeneity analysis.

 Eastern regionsCentral-western regions
 (1) lnExpy(2) lnExpy
SC0.837-4.038**
 (0.701)(1.725)
_cons8.360***10.573***
 (0.666)(0.479)
Control VariablesControlControl
Fixed effects by regionYESYES
Fixed effects by yearYearYESYES
Number510510
Coefficient of determinationR-squared(R2)0.9930.991

Notes: Numbers in parentheses within Table 3 denote robust standard errors of the coefficient estimates. Symbols** and *** denote statistical significance at 5%, and 1% thresholds, respectively.

3.3

Robustness test

This paper uses the following methods: (1) The explanatory variable is replaced. A composite index is constructed using provincial emissions of industrial SO2, industrial wastewater, and industrial soot as a substitute variable for environmental regulation. (2) The sample underwent a 1% winsorization. (3) The impact of the financial crisis was excluded. To mitigate the influence of the financial crisis on regression outcomes, data from 2009 were excluded and reestimated. The findings from these robustness tests are presented in Table 4, indicating that none of the tests conducted altered the observed significantly negative effect of environmental regulation on technological sophistication of manufacturing exports. These estimates confirm the robustness of the results.

Table 4.

Robustness testing.

 Replace explanatory variablesWinsorizeExcluding financial crises
 (1) lnExpy(2) lnExpy(3) lnExpy
SC-0.023*-4.428***-3.739**
 (0.012)(1.457)(1.475)
_cons8.866***8.891***8.926***
 (0.388)(0.370)(0.398)
Control VariablesControlControlControl
Fixed effects by regionYESYESYES
Fixed effects by yearYESYESYES
Number510510480
Coefficient of determination R- squared(R2)0.9890.9900.989

Notes: Numbers in parentheses within Table 4 denote robust standard errors of the coefficient estimates. Symbols *, **, and *** denote statistical significance at 10%, 5%, and 1% thresholds, respectively.

4.

CONCLUSIONS AND IMPLICATIONS

This study empirically investigates how environmental regulation affects technological complexity of China’s manufacturing export, utilizing panel data covering 30 provinces from 2004 to 2020. The following conclusions and insights can be drawn:

  • (1) Environmental regulations adversely affect technological sophistication of manufacturing export. In terms of promoting technological progress and enhancing export technological complexity, stricter environmental regulation does not necessarily lead to better outcomes. Strengthened environmental protection measures can hinder technological innovation and the improvement of export technology levels. Therefore, appropriate environmental regulatory approaches need to be adopted.

  • (2) Promoting the growth of technology markets can help alleviate the adverse effects of environmental regulation on the increase in technological content of manufacturing exports. Environmental regulatory policies should be aligned with the level of technological market development to promote technological progress and enhance export technological complexity. Thus, efforts should be made to vigorously promote the construction of technology markets.

  • (3) Due to differences in resource endowment, economic development levels, and technological market maturity among provinces, there are significant regional heterogeneities in the export effects of environmental regulations. The Eastern region, benefiting from ample human capital accumulation, can overcome environmental resource constraints. In contrast, the Central and Western regions exhibit higher dependence on population and resources, necessitating tailored policy support strategies based on local conditions.

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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xiangxia Liu and Hui Lou "Impact of environmental regulation on the technological complexity of manufacturing export: empirical analysis using panel data of 30 provinces in China", Proc. SPIE 13279, Fifth International Conference on Green Energy, Environment, and Sustainable Development (GEESD 2024) , 1327949 (26 September 2024); https://doi.org/10.1117/12.3044784
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KEYWORDS
Manufacturing

Control systems

Error analysis

Industry

Pollution control

Standards development

Analytical research

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