How Does AI Innovation Development Pilot Zones Improve Green Total Factor Productivity in China? Evidence From Chinese City Level Data

Avtorji

  • Wenqing Li Master's degree, School of Public Policy and Administration, Chongqing University, Chongqing 400044, China
  • Xiaobing Peng Doctor, School of Public Policy and Administration, Chongqing University, Chongqing 400044, China

DOI:

https://doi.org/10.52152/800189

Ključne besede:

Artificial intelligence implemental pilot zones; Green total factor productivity; DID method

Povzetek

With the growing utilization of artificial intelligence (AI) technologies, AI is starting to emerge as a major force behind green development, helping to reshape the economy in a sustainable and green way. This study takes China’s “National New Generation Artificial Intelligence Innovation and Development Pilot Zones” (AIIDPZ) as a quasi-natural experiment to evaluate their impact on green total factor productivity (GTFP). Using panel data from 280 prefecture-level cities between 2013 and 2023, a difference-in-differences (DID) model identifies a significant and robust policy effect on GTFP improvement. Mechanism analysis reveals that AIIDPZ enhances green innovation primarily through educational expenditure, while also contributing independently by improving electricity efficiency and reducing fixed asset investment. Further heterogeneity analysis shows that the policy’s positive effects are more pronounced in non-resource-based cities, cities with advanced industrial structures, small and medium-sized cities, flat-terrain regions, and locations with underdeveloped internet infrastructure. The findings offer empirical evidence and valuable policy implications for harnessing AI to advance green productivity and low-carbon growth.

Literatura

Lee C., Lee C. How does green finance affect green total factor productivity? Evidence from China. Energ. Econ. 2022, 107,105863.

Yang J., Li L., Liang Y., Wu J., Wang Z., Zhong Q., Liang S. Sustainability performance of global chemical industry based on green total factor productivity. Sci. Total Environ. 2022, 830,154787.

Cao X., Deng M., Li H. How does e-commerce city pilot improve green total factor productivity?Evidence from 230 cities in China. J. Environ. Manage. 2021, 289,112520.

Zhang Y., Peng Y., Ma C., Shen B. Can environmental innovation facilitate carbon emissions reduction? Evidence from China. Energ. Policy 2017, 100,18-28.

Jiang Y., Wang H., Liu Z. The impact of the free trade zone on green total factor productivity ——evidence from the shanghai pilot free trade zone. Energ. Policy 2021, 148,112000.

Yasmeen R., Zhaohui C., Hassan Shah W.U., Kamal M.A., Khan A. Exploring the role of biomass energy consumption, ecological footprint through FDI and technological innovation in B&R economies: A simultaneous equation approach. Energy 2022, 244,122703.

Allam Z., Dhunny Z.A. On big data, artificial intelligence and smart cities. Cities 2019, 89,80-91.

Shu H., Wang Y., Umar M., Zhong Y. Dynamics of renewable energy research, investment in EnvoTech and environmental quality in the context of G7 countries. Energ. Econ. 2023, 120,106582.

Zhang H., Ding Y., Niu J., Jung S. How artificial intelligence affects international industrial transfer - Evidence from industrial robot application. J. Asian Econ 2024, 95,13.

Fang W., Guo Y., Liao W., Ramani K., Huang S. Big data driven jobs remaining time prediction in discrete manufacturing system: a deep learning-based approach. Int. J. Prod. Res. 2020, 58,2751-2766.

Montobbio F., Staccioli J., Virgillito M.E., Vivarelli M. Robots and the origin of their labour-saving impact. Technol. Forecast. Soc. 2022, 174,19.

Feng L., Qi J., Zheng Y. How can AI reduce carbon emissions? Insights from a quasi-natural experiment using generalized random forest. Energ. Econ. 2025, 141,108040.

Dhar P. The carbon impact of artificial intelligence. Nat Mach Intell 2020, 2,423-425.

Xu S., Ge J. Sustainable shifting from coal to gas in North China: An analysis of resident satisfaction. Energ. Policy 2020, 138,10.

Zhang J., Zhang Y. Examining the effects of economic growth pressure on green total factor productivity: evidence from China. Econ Chang Restruct 2023, 56,4309-4337.

Liang T., Zhang Y., Qiang W. Does technological innovation benefit energy firms’ environmental performance? The moderating effect of government subsidies and media coverage. Technol. Forecast. Soc. 2022, 180,121728.

Zhang C., Zhu H., Li X. Which productivity can promote clean energy transition —total factor productivity or green total factor productivity? J. Environ. Manage. 2024, 366,121899.

Ge S., Luo X., Li Y., Zheng L. The impact of green credit policy on total factor productivity of enterprises. Int Rev Econ Financ 2024, 95,103480.

Wei R., Xia Y. Digital transformation and corporate green total factor productivity: Based on double/debiased machine learning robustness estimation. Econ Anal Policy 2024, 84,808-827.

Zhang S., Zhang M., Meng S. Corporate transaction costs and corporate green total factor productivity. Financ Res Lett 2024, 61,105041.

Jiang T., Cao C., Lei L., Hou J., Yu Y., Jahanger A. Temporal and spatial patterns, efficiency losses and impact factors of energy mismatch in China under environmental constraints. Energy 2023, 282,128875.

Li Y., Chen Y. Development of an SBM-ML model for the measurement of green total factor productivity: The case of pearl river delta urban agglomeration. Renewable and Sustainable Energy Reviews 2021, 145,111131.

Mo R., Huang H., Zhang J., Liu Y., Zhao X. Green economic efficiency and productivity for sustainable development in China: A ray epsilon-based measure model analysis. Environ. Sci. Policy 2024, 160,103860.

Hossain M.R., Rao A., Sharma G.D., Dev D., Kharbanda A. Empowering energy transition: Green innovation, digital finance, and the path to sustainable prosperity through green finance initiatives. Energ. Econ. 2024, 136,107736.

Yu L., Liu Y., Niu Y., Xiao Z. Greener together: The impact of China's mixed-ownership reform on firm carbon emissions. Energ. Policy 2023, 180,113689.

Chen S., Yang Q. Renewable energy technology innovation and urban green economy efficiency. J. Environ. Manage. 2024, 353,120130.

Sun Y., Razzaq A., Kizys R., Bao Q. High-speed rail and urban green productivity: The mediating role of climatic conditions in China. Technol. Forecast. Soc. 2022, 185,122055.

Song Y., Du C., Du P., Liu R., Lu Z. Digital transformation and corporate environmental performance: Evidence from Chinese listed companies. Technol. Forecast. Soc. 2024, 201,123159.

Xu S., Zhong M., Wang Y. Can innovative industrial clusters enhance urban economic resilience? A quasi-natural experiment based on an innovative pilot policy. Energ. Econ. 2024, 134,107544.

Zhao P., Gao Y., Sun X. How does artificial intelligence affect green economic growth?—Evidence from China. Sci. Total Environ. 2022, 834,155306.

Acemoglu D., Restrepo P. The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment. Am. Econ. Rev. 2018, 108,1488-1542.

Lin B., Zhu Y. Does AI elevate corporate ESG performance? A supply chain perspective. Bus Strateg Environ 2025, 34,586-597.

Stefan A., Paul L. Does It Pay to Be Green? A Systematic Overview. Acad Manage Perspect 2008, 22,45-62.

Jang S., Kim J., von Zedtwitz M. The importance of spatial agglomeration in product innovation: A microgeography perspective. J. Bus. Res. 2017, 78,143-154.

Duch-Brown N., Gomez-Herrera E., Mueller-Langer F., Tolan S. Market power and artificial intelligence work on online labour markets. Res. Policy 2022, 51,19.

Zhang D. The pathway to curb greenwashing in sustainable growth: The role of artificial intelligence. Energ. Econ. 2024, 133,10.

Huang Y., Liu S., Gan J., Liu B., Wu Y. How does the construction of new generation of national AI innovative development pilot zones drive enterprise ESG development? Empirical evidence from China. Energ. Econ. 2024, 140,108011.

Yang W., Wang D. Can industrial robot applications help cross the middle-income trap ?-Empirical evidence based on crossed-country panel data. Technol. Forecast. Soc. 2023, 192,16.

Yang C., Huang C. Quantitative mapping of the evolution of AI policy distribution, targets and focuses over three decades in China. Technol. Forecast. Soc. 2022, 174,121188.

Cao Q., Chi C., Shan J. Can artificial intelligence technology reduce carbon emissions? A global perspective. Energ. Econ. 2025, 143,108285.

Lin B., Yang Y. Building efficiency: How the national AI innovation pilot zones enhance green energy utilization? Evidence from China. J. Environ. Manage. 2025, 387,125945.

Xu Y., Li A. The relationship between innovative human capital and interprovincial economic growth based on panel data model and spatial econometrics. J. Comput. Appl. Math. 2020, 365,112381.

Wang B., Wang J., Dong K., Dong X. Is the digital economy conducive to the development of renewable energy in Asia? Energ. Policy 2023, 173,113381.

Ahmed Z., Asghar M.M., Malik M.N., Nawaz K. Moving towards a sustainable environment: The dynamic linkage between natural resources, human capital, urbanization, economic growth, and ecological footprint in China. Resour. Policy 2020, 67,101677.

López-Peña Á., Pérez-Arriaga I., Linares P. Renewables vs. energy efficiency: The cost of carbon emissions reduction in Spain. Energ. Policy 2012, 50,659-668.

Garrone P., Grilli L. Is there a relationship between public expenditures in energy R&D and carbon emissions per GDP? An empirical investigation. Energ. Policy 2010, 38,5600-5613.

Jaumandreu J., Mairesse J. Disentangling the effects of process and product innovation on cost and demand. Econ Innov New Tech 2017, 26,150-167.

Wang R., Mirza N., Vasbieva D.G., Abbas Q., Xiong D. The nexus of carbon emissions, financial development, renewable energy consumption, and technological innovation: What should be the priorities in light of COP 21 Agreements ? J. Environ. Manage. 2020, 271,7.

Khan Z., Ali S., Dong K., Li R.Y.M. How does fiscal decentralization affect CO 2 emissions? The roles of institutions and human capital. Energ. Econ. 2021, 94,10.

Wang M., Zhu C., Wang X., Ntim V.S., Liu X. Effect of information and communication technology and electricity consumption on green total factor productivity. Appl. Energ. 2023, 347,12.

Apergis N., Payne J.E. A dynamic panel study of economic development and the electricity consumption-growth nexus. Energ. Econ. 2011, 33,770-781.

Goldfarb A., Tucker C. Digital Economics. J. Econ. Lit. 2019, 57,3-43.

Srivastava P.R., Mangla S.K., Eachempati P., Tiwari A.K. An explainable artificial intelligence approach to understanding drivers of economic energy consumption and sustainability. Energ. Econ. 2023, 125,21.

Liang C., Chen X., Di Q. Path to pollution and carbon reduction synergy from the perspective of the digital economy : Fresh evidence from 292 prefecture-level cities in China. Environ. Res. 2024, 252,13.

Salahuddin M., Alam K. Information and Communication Technology , electricity consumption and economic growth in OECD countries : A panel data analysis. Int. J. Elec. Power 2016, 76,185-193.

Ai H., Xiong S., Li K., Jia P. Electricity price and industrial green productivity : Does the "low- electricity price trap" exist? Energy 2020, 207,11.

Lin B., Wang M. Dynamic analysis of carbon dioxide emissions in China's petroleum refining and coking industry. Sci. Total Environ. 2019, 671,937-947.

Wang H., Ye S., Chen H., Yin J. The impact of carbon emission trading policy on overcapacity of companies: Evidence from China. Energ. Econ. 2023, 126,106929.

Chen H., Li S.C., Zhang Y.L. IMPACT OF ROAD CONSTRUCTION ON VEGETATION ALONGSIDE QINGHAI-XIZANG HIGHWAY AND RAILWAY. Chinese Geogr Sci 2003, 13,340-346.

Wang R., Qi Z., Shu Y. Multiple relationships between fixed-asset investment and industrial structure evolution in China-Based on Directed Acyclic Graph (DAG) analysis and VAR model. Struct Change Econ D. 2020, 55,222-231.

Liu W., Li P., Huang X. Does the green financial policy promote growth quality ? Evidence from China. Appl. Econ. 2025,16.

Du J., Zhong Z., Shi Q., Wang L., Liu Y., Ying N. Does government environmental attention drive green total factor productivity ? Evidence from China. J. Environ. Manage. 2024, 366,10.

Yang J., Shi D., Yang W. Stringent environmental regulation and capital structure : The effect of NEPL on deleveraging the high polluting firms. Int Rev Econ Financ 2022, 79,643-656.

Xie H., Zhai Q., Wang W., Yu J., Lu F., Chen Q. Does intensive land use promote a reduction in carbon emissions ? Evidence from the Chinese industrial sector. Resour. Conserv. Recy. 2018, 137,167-176.

Cheng Z., Jin W. Agglomeration economy and the growth of green total-factor productivity in Chinese Industry. Socio-Econ. Plan. Sci. 2022, 83,12.

Wang H., Chen Z., Wu X., Niea X. Can a carbon trading system promote the transformation of a low-carbon economy under the framework of the porter hypothesis ? -Empirical analysis based on the PSM-DID method. Energ. Policy 2019, 129,930-938.

Kuosmanen N., Maczulskij T. Going green while getting lean: Decomposing carbon and green total factor productivity. J. Environ. Manage. 2024, 352,120046.

Zhu B., Nakaishi T., Kagawa S. Neighbor's profit or Neighbor's beggar? Evidence from China's low carbon cities pilot scheme on green development. Energ. Policy 2024, 195,114318.

Zhao L., Liu G., Jiao H., Hu S., Feng Y. China's endeavor to reduce energy intensity: Does the green financial reform and innovation pilot zones policy matter ? J. Environ. Manage. 2024, 370,16.

KRUGMAN P. INCREASING RETURNS AND ECONOMIC-GEOGRAPHY. J. Polit. Econ. 1991, 99,483-499.

Yang J., Liu P., Zhong F., Han N. Subway opening enables urban green development: Evidence from difference-in-differences and double dual machine learning methods. J. Environ. Manage. 2025, 375,14.

Tian Y., Feng C. How does internet development drive the sustainable economic growth of China ? Evidence from internal-structural perspective of green total-factor productivity. Sci. Total Environ. 2023, 887,11.

Yu B. The Impact of the Internet on Industrial Green Productivity: Evidence from China. Technol. Forecast. Soc. 2022, 177,10.

Wang C., Liao H., Zhu L., He L. The haze reduction effect in china under the digital economy. J. Asian Econ 2024, 95,101819.

BARON R.M., KENNY D.A. THE MODERATOR MEDIATOR VARIABLE DISTINCTION IN SOCIAL PSYCHOLOGICAL-RESEARCH - CONCEPTUAL, STRATEGIC, AND STATISTICAL CONSIDERATIONS. J. Pers. Soc. Psychol. 1986, 51,1173-1182.

Li L., Zheng Y., Ma S., Ma X., Zuo J., Goodsite M. Unfavorable weather, favorable insights: Exploring the impact of extreme climate on green total factor productivity. Econ Anal Policy 2025, 85,626-640.

Jing Z., Liu Z., Wang T., Zhang X. The impact of environmental regulation on green TFP :A quasi-natural experiment based on China's carbon emissions trading pilot policy. Energy 2024, 306,20.

HUANG J.P. ELECTRICITY CONSUMPTION AND ECONOMIC-GROWTH - A CASE-STUDY OF CHINA. Energ. Policy 1993, 21,717-720.

Jiang L., Chen Y., Jiang Y., Zhang B. Does Fiscal Efficiency Affect Green Total Factor Productivity: Evidence Based on Spatial Panel Data Models. Rev Dev Econ 2025,16.

Du K., Cheng Y., Yao X. Environmental regulation, green technology innovation, and industrial structure upgrading: The road to the green transformation of Chinese cities. Energ. Econ. 2021, 98,105247.

Zhou M., Shao W., Jiang K., Huang L. How does economic agglomeration affect carbon emissions at the county level in Liaoning China? Ecol. Indic. 2024, 158,111507.

Wang K., Pang S., Zhang F., Miao Z., Sun H. The impact assessment of smart city policy on urban green total-factor productivity: Evidence from China. Environ. Impact Asses. 2022, 94,106756.

Shahbaz M., Hoang T., Mahalik M.K., Roubaud D. Energy consumption, financial development and economic growth in India: New evidence from a nonlinear and asymmetric analysis. Energ. Econ. 2017, 63,199-212.

Zhang S., Wang Y., Hao Y., Liu Z. Shooting two hawks with one arrow : Could China's emission trading scheme promote green development efficiency and regional carbon equality? Energ. Econ. 2021, 101,14.

Zhao X., Nakonieczny J., Jabeen F., Shahzad U., Jia W. Does green innovation induce green total factor productivity? Novel findings from Chinese city level data. Technol. Forecast. Soc. 2022, 185,122021.

Xu L., Fan M., Yang L., Shao S. Heterogeneous green innovations and carbon emission performance: Evidence at China's city level. Energ. Econ. 2021, 99,105269.

Xie F., Zhang B., Wang N. Non-linear relationship between energy consumption transition and green total factor productivity: A perspective on different technology paths. Sustain Prod Consump 2021, 28,91-104.

Cheng Y., Lv K., Zhu S. How does digital financial inclusion promote green total factor productivity in China? An empirical analysis from the perspectives of innovation and entrepreneurship. Process Saf. Environ. 2023, 174,403-413.

Xie R., Fu W., Yao S., Zhang Q. Effects of financial agglomeration on green total factor productivity in Chinese cities: Insights from an empirical spatial Durbin model. Energ. Econ. 2021, 101,105449.

Acemoglu D., Angrist J.D. Consequences of employment protection ? The case of the Americans with Disabilities Act. J. Polit. Econ. 2001, 109,915-957.

Cengiz D., Dube A., Lindner A., Zipperer B. THE EFFECT OF MINIMUM WAGES ON LOW-WAGE JOBS. Q. J. Econ. 2019, 134,1405-1454.

Lv L., Chen Y. The Collision of digital and green: Digital transformation and green economic efficiency. J. Environ. Manage. 2024, 351,14.

Xia F., Xu J. Green total factor productivity: A re-examination of quality of growth for provinces in China. China Econ. Rev. 2020, 62,30.

Gao H., Xue X., Zhu H. Developing digital dividends: digital-economy-oriented industrial policy, digital technology innovation, and firms' productivity. Appl. Econ. Lett. 2024,8.

Lv J., Zhao Z., Ji Y. Can big data aggregation help businesses save energy and reduce emissions ? Quasi-natural experiment in big data comprehensive test. Struct Change Econ D. 2025, 72,89-102.

Du M., Huang C., Liao L. Trade liberalization and energy efficiency: Quasi-natural experiment evidence from the pilot free trade zones in China. Econ Anal Policy 2025, 85,1739-1751.

Wang Q., Yi H. New energy demonstration program and China's urban green economic growth : Do regional characteristics make a difference? Energ. Policy 2021, 151,14.

Yu B., Fang D., Pan Y., Jia Y. Countries' green total-factor productivity towards a low-carbon world : The role of energy trilemma. Energy 2023, 278,11.

Shen X., Wang Z. Can digital industrialization promote energy conservation development in China ? Empirical evidence based on national big data comprehensive pilot zone policy. J. Environ. Manage. 2024, 368,17.

Li J., Li M., Gao L., Li J. Empowering more balanced energy futures: The role of the digital economy in alleviating China's energy trilemma at the city-level. Energy 2024, 303,15.

Xue Y., Tang C., Wu H., Liu J., Hao Y. The emerging driving force of energy consumption in China : Does digital economy development matter? Energ. Policy 2022, 165,18.

Objavljeno

2025-08-01

Številka

Rubrika

Article

Kako citirati

How Does AI Innovation Development Pilot Zones Improve Green Total Factor Productivity in China? Evidence From Chinese City Level Data. (2025). Lex Localis - Journal of Local Self-Government, 23(7). https://doi.org/10.52152/800189