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Can technology R&D continuously improve green development level in the open economy? Empirical evidence from China’s industrial sector

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Abstract

Applying a global DEA model based on non-radial directional distance function, this paper constructs a comprehensive efficiency index to estimate green development level and further identifies the influencing mechanism of technology R&D on green development in China’s industrial sector. The results demonstrate that the level of green development in China’s industrial sector declined year by year and the average was 0.27, and it also shows significant regional characteristics within the sample period. Besides, the environment pollution transferred from the east to the central and the west. In addition, the results also indicate that there is a threshold effect for the impact of technology R&D on China’s industrial green development. Based on the volume of the trade openness, this effect presents a “N”-type characteristic that tilts to the right. According to the research results, the corresponding policy recommendations are put forward, which may be of great importance to improve the green development level in China’s industrial sector.

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Abbreviations

GDI:

Green Development index

Technology R&D:

Technology research and development

DEA:

Data envelopment analysis

SDF:

Shephard distance function

DDF:

Directional distance function

NDDF:

Non-radial distance function

EC:

Change in efficiency

TPC:

Change in technology progress

CEC:

Change in the catch-up effect

TE:

Green technology efficiency

GPR:

Green technology process gap ratio

TCR:

Green technology catch–effect gap ratio

MGD:

Malmquist GD index

FDI:

foreign direct investment

References

  • Ai H, Deng Z, Yang X (2015) The effect estimation and channel testing of the technological progress on China’s regional environmental performance. Ecol Indic 51:67–78

    Google Scholar 

  • Aller C, Ductor L, Herrerias MJ (2015) The world trade network and the environment. Energy Econ 52:55–68

    Google Scholar 

  • Ang JB (2007) CO2 emissions, energy consumption, and output in France. Energy Policy 35(10):4772–4778

    Google Scholar 

  • Arrow KJ (1962) The economic implications of learning by doing. Rev Econ Stud 29(3):155–173

    Google Scholar 

  • Baek J (2016) A new look at the FDI–income–energy–environment nexus: dynamic panel data analysis of ASEAN. Energy Policy 91:22–27

    Google Scholar 

  • Barros CP, Managi S, Matousek R (2012) The technical efficiency of the Japanese banks: non-radial directional performance measurement with undesirable output. Omega 40(1):1–8

    Google Scholar 

  • Bin S, Yue L (2012) Impact of foreign direct investment on China’s environment: an empirical study based on industrial panel data. Social Sciences in China 33(04):89–107

    Google Scholar 

  • Birdsall, N. and D. Wheeler (2017). Trade policy and industrial pollution in Latin America: where are the pollution havens? International Trade and the Environment: 355-368.

  • Bosetti V, Carraro C, Galeotti M, Massetti E, Tavoni M (2006) WITCH: a world induced technical change hybrid model. Energy J SI2006

  • Cherniwchan J (2017) Trade liberalization and the environment: evidence from NAFTA and U.S. manufacturing. J Int Econ 105:130–149

    Google Scholar 

  • Chung YH, Färe R, Grosskopf S (1997) Productivity and undesirable outputs: a directional distance function approach. J Environ Manag 51(3):229–240

    Google Scholar 

  • Dalvi-Esfahani M, Alaedini Z, Nilashi M, Samad S, Asadi S, Mohammadi M (2020) Students' green information technology behavior: beliefs and personality traits. J Clean Prod 257:120406

    Google Scholar 

  • Danish and R. Ulucak (2020). How do environmental technologies affect green growth? Evidence from BRICS economies. Science of the Total Environment 712.

  • Du K, Li J (2019) Towards a green world: how do green technology innovations affect total-factor carbon productivity. Energy Policy 131:240–250

    CAS  Google Scholar 

  • Du KR, Li PZ, Yan ZM (2019a) Do green technology innovations contribute to carbon dioxide emission reduction? Empirical evidence from patent data. Technol Forecast Soc Chang 146:297–303

    Google Scholar 

  • Du ZL, Lin BQ, Guan CX (2019b) Development path of electric vehicles in China under environmental and energy security constraints. Resour Conserv Recycl 143:17–26

    Google Scholar 

  • Eskeland GS, Harrison AE (2003) Moving to greener pastures? Multinationals and the pollution haven hypothesis. J Dev Econ 70(1):1–23

    Google Scholar 

  • Fukuyama H, Yoshida Y, Managi S (2011) Modal choice between air and rail: a social efficiency benchmarking analysis that considers CO2 emissions. Environ Econ Policy Stud 13(2):89–102

    Google Scholar 

  • Gong X, Mi JN, Wei CY, Yang RT (2019) Measuring environmental and economic performance of air pollution control for province-level areas in China. Int J Environ Res Public Health 16(8)

  • Goulder LH, Schneider SH (1999) Induced technological change and the attractiveness of CO2 abatement policies. Resour Energy Econ 21(3):211–253

    Google Scholar 

  • Hirukawa M, Sakudo M (2018) Functional-coefficient cointegration models in the presence of deterministic trends. Econ Rev 37(5):507–533

    Google Scholar 

  • Huang J, Cai X, Huang S, Tian S, Lei H (2019) Technological factors and total factor productivity in China: evidence based on a panel threshold model. China Econ Rev 54:271–285

    Google Scholar 

  • Kolcava D, Nguyen Q, Bernauer T (2019) Does trade liberalization lead to environmental burden shifting in the global economy? Ecol Econ 163:98–112

    Google Scholar 

  • Lee SK, Mogi G (2018) Relative efficiency of energy technologies in the Korean mid-term strategic energy technology development plan. Renew Sust Energ Rev 91:472–482

    Google Scholar 

  • Li K, Lin B (2018) How to promote energy efficiency through technological progress in China? Energy 143:812–821

    Google Scholar 

  • Li A, Zhang A, Huang H, Yao X (2018) Measuring unified efficiency of fossil fuel power plants across provinces in China: an analysis based on non-radial directional distance functions. Energy 152:549–561

    Google Scholar 

  • Li J, Xie C, Long H (2019a) The roles of inter-fuel substitution and inter-market contagion in driving energy prices: evidences from China’s coal market. Energy Econ 84:104525

    Google Scholar 

  • Li, J. L., H. X. Liu and K. R. Du (2019b). Does market-oriented reform increase energy rebound effect? Evidence from China's regional development. China Economic Review 56.

  • Lin B, Du K (2015) Energy and CO2 emissions performance in China's regional economies: do market-oriented reforms matter? Energy Policy 78:113–124

    Google Scholar 

  • Lin BQ, Xu B (2020) How does fossil energy abundance affect China's economic growth and CO2 emissions? Sci Total Environ 719:137503

    CAS  Google Scholar 

  • Love, I., B. Javorcik and A. Brucal (2017). Pollution haven or halo? Evidence from foreign acquisitions in Indonesia. Meeting Papers. Society for Economic Dynamics.

  • Lovely M, Popp D (2011) Trade, technology, and the environment: does access to technology promote environmental regulation? J Environ Econ Manag 61(1):16–35

    Google Scholar 

  • Managi S, Hibiki A, Tsurumi T (2009) Does trade openness improve environmental quality? J Environ Econ Manag 58(3):346–363

    Google Scholar 

  • Mirza FM, Ansar S, Ullah K, Maqsood F (2020) The impact of information and communication technologies, CO2 emissions, and energy consumption on inclusive development in developing countries. Environ Sci Pollut Res 27(3):3143–3155

    CAS  Google Scholar 

  • Oh DH, Lee J-d (2010) A metafrontier approach for measuring Malmquist productivity index. Empir Econ 38(1):47–64

    Google Scholar 

  • Peng DM, Yang Q, Yang HJ, Liu HH, Zhu YG, Mu YT (2020) Analysis on the relationship between fisheries economic growth and marine environmental pollution in China's coastal regions. Sci Total Environ 713:136641

    CAS  Google Scholar 

  • Romer PM (1986) Increasing returns and long-run growth. J Polit Econ 94(5):1002–1037

    Google Scholar 

  • Romer PM (1990) Endogenous technological change. J Polit Econ 98(5):S71–S102

    Google Scholar 

  • Roy J (2017) On the environmental consequences of intra-industry trade. J Environ Econ Manag 83:50–67

    Google Scholar 

  • Shahbaz M, Nasir MA, Roubaud D (2018) Environmental degradation in France: the effects of FDI, financial development, and energy innovations. Energy Econ 74:843–857

    Google Scholar 

  • Shi X, Sun S (2017) Energy price, regulatory price distortion and economic growth: a case study of China. Energy Econ 63:261–271

    Google Scholar 

  • Son H, Chung Y, Hwang H (2019) Do technology entrepreneurship and external relationships always promote technology transfer? Evidence from Korean public research organizations. Technovation 82-83:1–15

    Google Scholar 

  • Song M-L, Cao S-P, Wang S-H (2019a) The impact of knowledge trade on sustainable development and environment-biased technical progress. Technol Forecast Soc Chang 144:512–523

    Google Scholar 

  • Song Y, Yang TT, Zhang M (2019b) Research on the impact of environmental regulation on enterprise technology innovation—an empirical analysis based on Chinese provincial panel data. Environ Sci Pollut Res 26(21):21835–21848

    Google Scholar 

  • Stern DI (2012) Modeling international trends in energy efficiency. Energy Econ 34(6):2200–2208

    Google Scholar 

  • Sueyoshi T, Goto M (2011) DEA approach for unified efficiency measurement: assessment of Japanese fossil fuel power generation. Energy Econ 33(2):292–303

    Google Scholar 

  • Sueyoshi T, Li AJ, Liu XH (2019) Exploring sources of China's CO2 emission: decomposition analysis under different technology changes. Eur J Oper Res 279(3):984–995

    Google Scholar 

  • Sun YG, Malikov E (2018) Estimation and inference in functional-coefficient spatial autoregressive panel data models with fixed effects. J Econ 203(2):359–378

    Google Scholar 

  • Tran NV, Tran QV, Do LTT, Dinh LH, Do HTT (2019) Trade off between environment, energy consumption and human development: do levels of economic development matter? Energy 173:483–493

    Google Scholar 

  • Tulkens H, Eeckaut PV (1995) Non-frontier measures of efficiency, progress and regress for time series data. Int J Prod Econ 39(1-2):83–97

    Google Scholar 

  • Walter I, Ugelow JL (1979) Environmental policies in developing countries. Ambio 8(2):102–109

    Google Scholar 

  • Wang H, Zhou P, Zhou DQ (2013) Scenario-based energy efficiency and productivity in China: a non-radial directional distance function analysis. Energy Econ 40:795–803

    Google Scholar 

  • Weixian W, Fang Y (2010) Impact of technology advance on carbon dioxide emission in China. Statistical Research 27(07):36–44

    Google Scholar 

  • Xiaoping L, Xianxian L (2010) International trade, pollution industry transfer and Chinese industries' CO2 emissions. Econ Res J 45(01):15–26

    Google Scholar 

  • Yang YC, Nie PY, Huang JB (2020) The optimal strategies for clean technology to advance green transition. Sci Total Environ 716:134439

    CAS  Google Scholar 

  • Yao X, Zhou H, Zhang A, Li A (2015) Regional energy efficiency, carbon emission performance and technology gaps in China: a meta-frontier non-radial directional distance function analysis. Energy Policy 84:142–154

    CAS  Google Scholar 

  • Zafar MW, Mirza FM, Zaidi SAH, Hou FJ (2019) The nexus of renewable and nonrenewable energy consumption, trade openness, and CO2 emissions in the framework of EKC: evidence from emerging economies. Environ Sci Pollut Res 26(15):15162–15173

    CAS  Google Scholar 

  • Zhang S, Liu X, Bae J (2017) Does trade openness affect CO2 emissions: evidence from ten newly industrialized countries? Environ Sci Pollut Res 24(21):17616–17625

    CAS  Google Scholar 

  • Zhang N, Zhao KK, Yu YT (2020) The effect of environmental regulation on air pollution, productivity, and factor structure: a quasi-natural experiment evidence from China. Environ Sci Pollut Res

  • Zhou, P., B. W. Ang and H. Wang (2012). Energy and CO2 emission performance in electricity generation: a non-radial directional distance function approach. Eur J Oper Res 221(3): 0-0, 625, 635.

  • Zhou D, Lin ZL, Lim SH (2019) Spatial characteristics and risk factor identification for land use spatial conflicts in a rapid urbanization region in China. Environ Monit Assess 191(11):677

    Google Scholar 

  • Zihui Y, Lei T (2017) A panel co-integration analysis of the pollution haven hypothesis and its determinants in China. The Journal of World Economy 40(05):148–172

    Google Scholar 

  • Zugravu-Soilita N (2017) How does foreign direct investment affect pollution? Toward a better understanding of the direct and conditional effects. Environmental &amp. Res Econ 66(2):293–338

    Google Scholar 

Download references

Acknowledgments

The research was supported by the Fundamental Research Funds for the Central Universities, China (2019VI020).

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Authors and Affiliations

  1. School of Economics, Wuhan University of Technology, Wuhan, Hubei, 430070, PR China

    Rilong Fei, Aixue Cui & Keyu Qin

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  1. Rilong Fei
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  2. Aixue Cui
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Correspondence to Keyu Qin.

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Fei, R., Cui, A. & Qin, K. Can technology R&D continuously improve green development level in the open economy? Empirical evidence from China’s industrial sector. Environ Sci Pollut Res 27, 34052–34066 (2020). https://doi.org/10.1007/s11356-020-09357-0

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