A double machine learning model for measuring the impact of the Made in China 2025 strategy on green economic growth

Machine Learning


  • Cheng, K. & Liu, S. Does urbanization promote the urban–rural equalization of basic public services? Evidence from prefectural cities in China. Appl. Econ. 56(29), 3445–3459. https://doi.org/10.1080/00036846.2023.2206625 (2023).

    Article 

    Google Scholar 

  • Yin, X. & Xu, Z. An empirical analysis of the coupling and coordinative development of China’s green finance and economic growth. Resour. Policy 75, 102476. https://doi.org/10.1016/j.resourpol.2021.102476 (2022).

    Article 

    Google Scholar 

  • Fernandes, C. I., Veiga, P. M., Ferreira, J. J. M. & Hughes, M. Green growth versus economic growth: Do sustainable technology transfer and innovations lead to an imperfect choice?. Bus. Strateg. Environ. 30(4), 2021–2037. https://doi.org/10.1002/bse.2730 (2021).

    Article 

    Google Scholar 

  • Orsatti, G., Quatraro, F. & Pezzoni, M. The antecedents of green technologies: The role of team-level recombinant capabilities. Res. Policy 49(3), 103919. https://doi.org/10.1016/j.respol.2019.103919 (2020).

    Article 

    Google Scholar 

  • Lin, B. & Zhou, Y. Measuring the green economic growth in China: Influencing factors and policy perspectives. Energy 241(15), 122518. https://doi.org/10.1016/j.energy.2021.122518 (2022).

    Article 

    Google Scholar 

  • Fang, M. & Chang, C. L. Nexus between fiscal imbalances, green fiscal spending, and green economic growth: Empirical findings from E-7 economies. Econ. Change Restruct. 55, 2423–2443. https://doi.org/10.1007/s10644-022-09392-6 (2022).

    Article 

    Google Scholar 

  • Qian, Y., Liu, J. & Forrest, J. Y. L. Impact of financial agglomeration on regional green economic growth: Evidence from China. J. Environ. Plan. Manag. 65(9), 1611–1636. https://doi.org/10.1080/09640568.2021.1941811 (2022).

    Article 

    Google Scholar 

  • Awais, M., Afzal, A., Firdousi, S. & Hasnaoui, A. Is fintech the new path to sustainable resource utilisation and economic development?. Resour. Policy 81, 103309. https://doi.org/10.1016/j.resourpol.2023.103309 (2023).

    Article 

    Google Scholar 

  • Ahmed, E. M. & Elfaki, K. E. Green technological progress implications on long-run sustainable economic growth. J. Knowl. Econ. https://doi.org/10.1007/s13132-023-01268-y (2023).

    Article 

    Google Scholar 

  • Shen, F. et al. The effect of economic growth target constraints on green technology innovation. J. Environ. Manag. 292(15), 112765. https://doi.org/10.1016/j.jenvman.2021.112765 (2021).

    Article 

    Google Scholar 

  • Zhao, L. et al. Enhancing green economic recovery through green bonds financing and energy efficiency investments. Econ. Anal. Policy 76, 488–501. https://doi.org/10.1016/j.eap.2022.08.019 (2022).

    Article 

    Google Scholar 

  • Ferreira, J. J. et al. Diverging or converging to a green world? Impact of green growth measures on countries’ economic performance. Environ. Dev. Sustain. https://doi.org/10.1007/s10668-023-02991-x (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Song, X., Zhou, Y. & Jia, W. How do economic openness and R&D investment affect green economic growth?—Evidence from China. Resour. Conserv. Recycl. 149, 405–415. https://doi.org/10.1016/j.resconrec.2019.03.050 (2019).

    Article 

    Google Scholar 

  • Xu, J., She, S., Gao, P. & Sun, Y. Role of green finance in resource efficiency and green economic growth. Resour. Policy 81, 103349 (2023).

    Article 

    Google Scholar 

  • Zhou, Y., Tian, L. & Yang, X. Schumpeterian endogenous growth model under green innovation and its enculturation effect. Energy Econ. 127, 107109. https://doi.org/10.1016/j.eneco.2023.107109 (2023).

    Article 

    Google Scholar 

  • Luukkanen, J. et al. Resource efficiency and green economic sustainability transition evaluation of green growth productivity gap and governance challenges in Cambodia. Sustain. Dev. 27(3), 312–320. https://doi.org/10.1002/sd.1902 (2019).

    Article 

    Google Scholar 

  • Wang, K., Umar, M., Akram, R. & Caglar, E. Is technological innovation making world “Greener”? An evidence from changing growth story of China. Technol. Forecast. Soc. Change 165, 120516. https://doi.org/10.1016/j.techfore.2020.120516 (2021).

    Article 

    Google Scholar 

  • Talebzadehhosseini, S. & Garibay, I. The interaction effects of technological innovation and path-dependent economic growth on countries overall green growth performance. J. Clean. Prod. 333(20), 130134. https://doi.org/10.1016/j.jclepro.2021.130134 (2022).

    Article 

    Google Scholar 

  • Ge, T., Li, C., Li, J. & Hao, X. Does neighboring green development benefit or suffer from local economic growth targets? Evidence from China. Econ. Modell. 120, 106149. https://doi.org/10.1016/j.econmod.2022.106149 (2023).

    Article 

    Google Scholar 

  • Lin, B. & Zhu, J. Fiscal spending and green economic growth: Evidence from China. Energy Econ. 83, 264–271. https://doi.org/10.1016/j.eneco.2019.07.010 (2019).

    Article 

    Google Scholar 

  • Sohail, M. T., Ullah, S. & Majeed, M. T. Effect of policy uncertainty on green growth in high-polluting economies. J. Clean. Prod. 380(20), 135043. https://doi.org/10.1016/j.jclepro.2022.135043 (2022).

    Article 

    Google Scholar 

  • Sarwar, S. Impact of energy intensity, green economy and blue economy to achieve sustainable economic growth in GCC countries: Does Saudi Vision 2030 matters to GCC countries. Renew. Energy 191, 30–46. https://doi.org/10.1016/j.renene.2022.03.122 (2022).

    Article 

    Google Scholar 

  • Park, J. & Page, G. W. Innovative green economy, urban economic performance and urban environments: An empirical analysis of US cities. Eur. Plann. Stud. 25(5), 772–789. https://doi.org/10.1080/09654313.2017.1282078 (2017).

    Article 

    Google Scholar 

  • Feng, Y., Chen, Z. & Nie, C. The effect of broadband infrastructure construction on urban green innovation: Evidence from a quasi-natural experiment in China. Econ. Anal. Policy 77, 581–598. https://doi.org/10.1016/j.eap.2022.12.020 (2023).

    Article 

    Google Scholar 

  • Zhang, X. & Fan, D. Collaborative emission reduction research on dual-pilot policies of the low-carbon city and smart city from the perspective of multiple innovations. Urban Climate 47, 101364. https://doi.org/10.1016/j.uclim.2022.101364 (2023).

    Article 

    Google Scholar 

  • Cheng, J., Yi, J., Dai, S. & Xiong, Y. Can low-carbon city construction facilitate green growth? Evidence from China’s pilot low-carbon city initiative. J. Clean. Prod. 231(10), 1158–1170. https://doi.org/10.1016/j.jclepro.2019.05.327 (2019).

    Article 

    Google Scholar 

  • Li, L. China’s manufacturing locus in 2025: With a comparison of “Made-in-China 2025” and “Industry 4.0”. Technol. Forecast. Soc. Change 135, 66–74. https://doi.org/10.1016/j.techfore.2017.05.028 (2018).

    Article 

    Google Scholar 

  • Wang, J., Wu, H. & Chen, Y. Made in China 2025 and manufacturing strategy decisions with reverse QFD. Int. J. Prod. Econ. 224, 107539. https://doi.org/10.1016/j.ijpe.2019.107539 (2020).

    Article 

    Google Scholar 

  • Liu, X., Megginson, W. L. & Xia, J. Industrial policy and asset prices: Evidence from the Made in China 2025 policy. J. Bank. Finance 142, 106554. https://doi.org/10.1016/j.jbankfin.2022.106554 (2022).

    Article 

    Google Scholar 

  • Chen, K. et al. How does industrial policy experimentation influence innovation performance? A case of Made in China 2025. Humanit. Soc. Sci. Commun. 11, 40. https://doi.org/10.1057/s41599-023-02497-x (2024).

    Article 
    CAS 

    Google Scholar 

  • Xu, L. Towards green innovation by China’s industrial policy: Evidence from Made in China 2025. Front. Environ. Sci. 10, 924250. https://doi.org/10.3389/fenvs.2022.924250 (2022).

    Article 

    Google Scholar 

  • Li, X., Han, H. & He, H. Advanced manufacturing firms’ digital transformation and exploratory innovation. Appl. Econ. Lett. https://doi.org/10.1080/13504851.2024.2305665 (2024).

    Article 

    Google Scholar 

  • Liu, G. & Liu, B. How digital technology improves the high-quality development of enterprises and capital markets: A liquidity perspective. Finance Res. Lett. 53, 103683 (2023).

    Article 

    Google Scholar 

  • Chernozhukov, V. et al. Double/debiased machine learning for treatment and structural parameters. Econom. J. 21(1), C1–C68. https://doi.org/10.1111/ectj.12097 (2018).

    Article 
    MathSciNet 

    Google Scholar 

  • Athey, S., Tibshirani, J. & Wager, S. Generalized random forests. Ann. Stat. 47(2), 1148–1178. https://doi.org/10.1214/18-AOS1709 (2019).

    Article 
    MathSciNet 

    Google Scholar 

  • Knittel, C. R. & Stolper, S. Machine learning about treatment effect heterogeneity: The case of household energy use. AEA Pap. Proc. 111, 440–444 (2021).

    Article 

    Google Scholar 

  • Yang, J., Chuang, H. & Kuan, C. Double machine learning with gradient boosting and its application to the Big N audit quality effect. J. Econom. 216(1), 268–283. https://doi.org/10.1016/j.jeconom.2020.01.018 (2020).

    Article 
    MathSciNet 

    Google Scholar 

  • Zhang, Y., Li, H. & Ren, G. Quantifying the social impacts of the London Night Tube with a double/debiased machine learning based difference-in-differences approach. Transp. Res. Part A Policy Pract. 163, 288–303. https://doi.org/10.1016/j.tra.2022.07.015 (2022).

    Article 

    Google Scholar 

  • Farbmacher, H., Huber, M., Lafférs, L., Langen, H. & Spindler, M. Causal mediation analysis with double machine learning. Econom. J. 25(2), 277–300. https://doi.org/10.1093/ectj/utac003 (2022).

    Article 
    MathSciNet 

    Google Scholar 

  • Chiang, H., Kato, K., Ma, Y. & Sasaki, Y. Multiway cluster robust double/debiased machine learning. J. Bus. Econ. Stat. 40(3), 1046–1056. https://doi.org/10.1080/07350015.2021.1895815 (2022).

    Article 
    MathSciNet 

    Google Scholar 

  • Bodory, H., Huber, M. & Lafférs, L. Evaluating (weighted) dynamic treatment effects by double machine learning. Econom. J. 25(3), 628–648. https://doi.org/10.1093/ectj/utac018 (2022).

    Article 
    MathSciNet 

    Google Scholar 

  • Waheed, R., Sarwar, S. & Alsaggaf, M. I. Relevance of energy, green and blue factors to achieve sustainable economic growth: Empirical study of Saudi Arabia. Technol. Forecast. Soc. Change 187, 122184. https://doi.org/10.1016/j.techfore.2022.122184 (2023).

    Article 

    Google Scholar 

  • Taskin, D., Vardar, G. & Okan, B. Does renewable energy promote green economic growth in OECD countries?. Sustain. Account. Manag. Policy J. 11(4), 771–798. https://doi.org/10.1108/SAMPJ-04-2019-0192 (2020).

    Article 

    Google Scholar 

  • Ding, X. & Liu, X. Renewable energy development and transportation infrastructure matters for green economic growth? Empirical evidence from China. Econ. Anal. Policy 79, 634–646. https://doi.org/10.1016/j.eap.2023.06.042 (2023).

    Article 

    Google Scholar 

  • Ferguson, P. The green economy agenda: Business as usual or transformational discourse?. Environ. Polit. 24(1), 17–37. https://doi.org/10.1080/09644016.2014.919748 (2015).

    Article 

    Google Scholar 

  • Pan, D., Yu, Y., Hong, W. & Chen, S. Does campaign-style environmental regulation induce green economic growth? Evidence from China’s central environmental protection inspection policy. Energy Environ. https://doi.org/10.1177/0958305X231152483 (2023).

    Article 

    Google Scholar 

  • Zhang, Q., Qu, Y. & Zhan, L. Great transition and new pattern: Agriculture and rural area green development and its coordinated relationship with economic growth in China. J. Environ. Manag. 344, 118563. https://doi.org/10.1016/j.jenvman.2023.118563 (2023).

    Article 

    Google Scholar 

  • Li, J., Dong, K. & Dong, X. Green energy as a new determinant of green growth in China: The role of green technological innovation. Energy Econ. 114, 106260. https://doi.org/10.1016/j.eneco.2022.106260 (2022).

    Article 

    Google Scholar 

  • Herman, K. S. et al. A critical review of green growth indicators in G7 economies from 1990 to 2019. Sustain. Sci. 18, 2589–2604. https://doi.org/10.1007/s11625-023-01397-y (2023).

    Article 

    Google Scholar 

  • Mura, M., Longo, M., Zanni, S. & Toschi, L. Exploring socio-economic externalities of development scenarios. An analysis of EU regions from 2008 to 2016. J. Environ. Manag. 332, 117327. https://doi.org/10.1016/j.jenvman.2023.117327 (2023).

    Article 

    Google Scholar 

  • Huang, S. Do green financing and industrial structure matter for green economic recovery? Fresh empirical insights from Vietnam. Econ. Anal. Policy 75, 61–73. https://doi.org/10.1016/j.eap.2022.04.010 (2022).

    Article 

    Google Scholar 

  • Li, J., Dong, X. & Dong, K. Is China’s green growth possible? The roles of green trade and green energy. Econ. Res.-Ekonomska Istraživanja 35(1), 7084–7108. https://doi.org/10.1080/1331677X.2022.2058978 (2022).

    Article 

    Google Scholar 

  • Zhang, H. et al. Promoting eco-tourism for the green economic recovery in ASEAN. Econ. Change Restruct. 56, 2021–2036. https://doi.org/10.1007/s10644-023-09492-x (2023).

    Article 
    ADS 

    Google Scholar 

  • Ahmed, F., Kousar, S., Pervaiz, A. & Shabbir, A. Do institutional quality and financial development affect sustainable economic growth? Evidence from South Asian countries. Borsa Istanbul Rev. 22(1), 189–196. https://doi.org/10.1016/j.bir.2021.03.005 (2022).

    Article 

    Google Scholar 

  • Yuan, S., Li, C., Wang, M., Wu, H. & Chang, L. A way toward green economic growth: Role of energy efficiency and fiscal incentive in China. Econ. Anal. Policy 79, 599–609. https://doi.org/10.1016/j.eap.2023.06.004 (2023).

    Article 

    Google Scholar 

  • Capasso, M., Hansen, T., Heiberg, J., Klitkou, A. & Steen, M. Green growth – A synthesis of scientific findings. Technol. Forecast. Soc. Change 146, 390–402. https://doi.org/10.1016/j.techfore.2019.06.013 (2019).

    Article 

    Google Scholar 

  • Wei, X., Ren, H., Ullah, S. & Bozkurt, C. Does environmental entrepreneurship play a role in sustainable green development? Evidence from emerging Asian economies. Econ. Res. Ekonomska Istraživanja 36(1), 73–85. https://doi.org/10.1080/1331677X.2022.2067887 (2023).

    Article 

    Google Scholar 

  • Iqbal, K., Sarfraz, M. & Khurshid,. Exploring the role of information communication technology, trade, and foreign direct investment to promote sustainable economic growth: Evidence from Belt and Road Initiative economies. Sustain. Dev. 31(3), 1526–1535. https://doi.org/10.1002/sd.2464 (2023).

    Article 

    Google Scholar 

  • Li, Y., Zhang, J. & Lyu, Y. Toward inclusive green growth for sustainable development: A new perspective of labor market distortion. Bus. Strategy Environ. 32(6), 3927–3950. https://doi.org/10.1002/bse.3346 (2023).

    Article 

    Google Scholar 

  • Chernozhukov, V. et al. Double/Debiased/Neyman machine learning of treatment effects. Am. Econ. Rev. 107(5), 261–265. https://doi.org/10.1257/aer.p20171038 (2017).

    Article 

    Google Scholar 

  • Chen, C. Super efficiencies or super inefficiencies? Insights from a joint computation model for slacks-based measures in DEA. Eur. J. Op. Res. 226(2), 258–267. https://doi.org/10.1016/j.ejor.2012.10.031 (2013).

    Article 
    ADS 
    MathSciNet 

    Google Scholar 

  • Tone, K., Chang, T. & Wu, C. Handling negative data in slacks-based measure data envelopment analysis models. Eur. J. Op. Res. 282(3), 926–935 (2020).

    Article 
    MathSciNet 

    Google Scholar 

  • Sarkodie, S. A., Owusu, P. A. & Taden, J. Comprehensive green growth indicators across countries and territories. Sci. Data 10, 413. https://doi.org/10.1038/s41597-023-02319-4 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Jiang, Z., Wang, Z. & Lan, X. How environmental regulations affect corporate innovation? The coupling mechanism of mandatory rules and voluntary management. Technol. Soc. 65, 101575 (2021).

    Article 

    Google Scholar 

  • Oh, D. H. & Heshmati, A. A sequential Malmquist-Luenberger productivity index: Environmentally sensitive productivity growth considering the progressive nature of technology. Energy Econ. 32(6), 1345–1355. https://doi.org/10.1016/j.eneco.2010.09.003 (2010).

    Article 

    Google Scholar 

  • Tone, K. & Tsutsui, M. An epsilon-based measure of efficiency in DEA – A third pole of technical efficiency. Eur. J. Op. Res. 207(3), 1554–1563. https://doi.org/10.1016/j.ejor.2010.07.014 (2010).

    Article 
    MathSciNet 

    Google Scholar 

  • Lv, C., Song, J. & Lee, C. Can digital finance narrow the regional disparities in the quality of economic growth? Evidence from China. Econ. Anal. Policy 76, 502–521. https://doi.org/10.1016/j.eap.2022.08.022 (2022).

    Article 

    Google Scholar 

  • Arkhangelsky, D., Athey, S., Hirshberg, D. A., Imbens, G. W. & Wager, S. Synthetic difference-in-differences. Am. Econ. Rev. 111(12), 4088–4118 (2021).

    Article 

    Google Scholar 

  • Abadie, A., Diamond, A. & Hainmueller, J. Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program. J. Am. Stat. Assoc. 105(490), 493–505 (2010).

    Article 
    MathSciNet 
    CAS 

    Google Scholar 

  • Fang, J., Tang, X., Xie, R. & Han, F. The effect of manufacturing agglomerations on smog pollution. Struct. Change Econ. Dyn. 54, 92–101. https://doi.org/10.1016/j.strueco.2020.04.003 (2020).

    Article 

    Google Scholar 

  • Yang, S. & Liu, F. Impact of industrial intelligence on green total factor productivity: The indispensability of the environmental system. Ecol. Econ. 216, 108021. https://doi.org/10.1016/j.ecolecon.2023.108021 (2024).

    Article 

    Google Scholar 

  • Zhang, P., Wang, Y., Wang, R. & Wang, T. Digital finance and corporate innovation: Evidence from China. Appl. Econ. 56(5), 615–638. https://doi.org/10.1080/00036846.2023.2169242 (2024).

    Article 

    Google Scholar 



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