Development of Digital Financial Inclusion in China's Regional Economy: Evidence from Panel Threshold Models
Main Article Content
Keywords
Digital Financial Inclusion, Regional Economy, Panel threshold model
Abstract
This study aims to investigate the effect of digital financial inclusion and air pollution on economic growth for 31 Chinese provinces between 2003 and 2022 using Panel Threshold Auto-Regressive (PTAR) and Panel Smooth Transition Auto-Regression (PSTAR) models. The results show that there is a nonlinear link between digital financial inclusion and economic growth in China. For PTAR, the LnDFII thresholds are 4.264 (i.e., DFII = 71.094), and for PSTAR are 4.563 (i.e., DFII = 95.871). Below these thresholds, digital financial inclusion significantly boosts economic growth by 0.061 and 0.063 in the PTAR and PSTAR models, respectively. However, above these thresholds, the positive impact diminishes, with coefficients dropping to 0.015 and 0.004 in the PTAR and PSTAR models, respectively. Additionally, both models indicate that digital financial inclusion positively affects reducing air pollution, thereby potentially fostering economic growth. Hence, authorities should strategically implement digital technologies and strengthen collaborative efforts at the regional level to maximize these benefits.
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Ding, R., Shi, F., & Hao, S. (2022). Digital inclusive finance, environmental regulation, and regional economic growth: An empirical study based on spatial spillover effect and panel threshold effect. Sustainability, 14(7), 4340. https://doi.org/10.3390/su14074340
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Feng, G., Jingyi, W., Zhiyun, C., Yongguo, L., Fang, W., & Aiyong, W. (2019). The Peking university digital financial inclusion index of China (2011–2018). Institute of Digital Finance, Peking University, April, 1–70. https://en.idf.pku.edu.cn/docs/20190610145822397835.pdf
Frees, E. W. (1995). Assessing cross-sectional correlation in panel data. Journal of econometrics, 69(2), 393–414. https://doi.org/10.1016/0304-4076(94)01658-M
Frees, E. W. (2004). Longitudinal and Panel Data: Analysis and Applications in the Social Sciences. Cambridge: Cambridge University Press.
Friedman, M. (1937). The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American statistical association, 32(200), 675–701. https://doi.org/10.1080/01621459.1937.10503522
González, A., Teräsvirta, T., & Dijk, D. V. (2005). Panel smooth transition regression models (No. 604). SSE/EFI Working Paper Series in Economics and Finance. https://hdl.handle.net/10419/56363
González, A., Teräsvirta, T., van Dijk, D., & Yang, Y. (2017). Panel Smooth Transition Regression Models. SSE/EFI Working Paper Series in Economics and Finance 604, Stockholm School of Economics, revised 11 Oct 2017. https://EconPapers.repec.org/RePEc:aah:create:2017-36
Grossman, G. M., & Krueger, A. B. (1995). Economic growth and the environment. The quarterly journal of economics, 110(2), 353–377. https://doi.org/10.2307/2118443
Guo, J., Zhou, Y., Ali, S., Shahzad, U., & Cui, L. (2021). Exploring the role of green innovation and investment in energy for environmental quality: An empirical appraisal from provincial data of China. Journal of Environmental Management, 292, 112779. https://doi.org/10.1016/j.jenvman.2021.112779
Guo, Q., Ma, X. & Zhao, J. (2023). Can the digital economy development achieve the effect of pollution reduction? Evidence from Chinese Cities. Environmental Science and Pollution Research, 30(29), 74166–74185. https://doi.org/10.1007/s11356-023-27584-z
Hansen, B. E. (1999). Threshold effects in non-dynamic panels: Estimation, testing, and inference. Journal of econometrics, 93(2), 345–368. https://doi.org/10.1016/S0304-4076(99)00025-1
He, Y., & Wang, M. (2021). Nonlinear and heterogeneous economic growth effects of digital financial inclusion: An empirical study based on smooth transition model and quantile model. Journal of Sichuan Normal University, 48, 54–64.
Higon, D. A., Gholami, R., & Shirazi, F. (2017). ICT and environmental sustainability: A global perspective. Telematics and Informatics, 34(4), 85–95. https://doi.org/10.1016/j.tele.2017.01.001
Jahanger, A., Yu, Y., Hossain, M. R., Murshed, M., Balsalobre-Lorente, D., & Khan, U. (2022). Going away or going green in NAFTA nations? Linking natural resources, energy utilization, and environmental sustainability through the lens of the EKC hypothesis. Resources Policy, 79, 103091. https://doi.org/10.1016/j.resourpol.2022.103091
Jarque, C. M., & Bera, A. K. (1987). A test for normality of observations and regression residuals. International Statistical Review, 55(2) 163–172. https://doi.org/10.2307/1403192
Jiang, S., Tan, X., Hu, P., Wang, Y., Shi, L., Ma, Z., & Lu, G. (2022). Air pollution and economic growth under local government competition: Evidence from China, 2007–2016. Journal of Cleaner Production, 334, 130231. https://doi.org/10.1016/j.jclepro.2021.130231
Kalai, M., Becha, H., & Helali, K. (2024). Threshold effect of foreign direct investment on economic growth in BRICS countries: new evidence from PTAR and PSTAR models. International Journal of Economic Policy Studies, 18(1), 227–258. https://doi.org/10.1007/s42495-023-00126-8
Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of econometrics, 90(1), 1–44. https://doi.org/10.1016/S0304-4076(98)00023-2
Li, J., & Li, S. (2020). Energy investment, economic growth and carbon emissions in China—Empirical analysis based on spatial Durbin model. Energy Policy, 140, 111425. https://doi.org/10.1016/j.enpol.2020.111425
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Mar 27, 2024
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Ben Abdallah, A., Becha, H., Kalai, M., & Helali, K. (2024). Development of Digital Financial Inclusion in China’s Regional Economy: Evidence from Panel Threshold Models. Journal of Telecommunications and the Digital Economy, 12(1), 637–656. https://doi.org/10.18080/jtde.v12n1.838
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Special Issue: Emerging Technologies and Innovation for Digital Economy and Transformation
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Author Biographies
Amal Ben Abdallah, Faculty of Economics and Management of Sfax, University of Sfax, Tunisia
Assistant professor in Economics, Faculty of Economics and Management of Sfax, University of Sfax. E-mail address: benabdallahamal5@gmail.com
Hamdi Becha, Faculty of Economics and Management of Sfax, University of Sfax, Tunisia
Assistant professor in Economics, Faculty of Economics and Management of Sfax, University of Sfax. E-mail address: bechahamdi@yahoo.com
Maha Kalai, Faculty of Economics and Management of Sfax, University of Sfax, Tunisia
Assistant professor in Quantitative Methods, Faculty of Economics and Management of Sfax, University of Sfax. E-mail address: maha.kalai@fsegs.usf.tn
Kamel Helali, University of Sfax, Tunisia
Full Professor in Quantitative Methods, Faculty of Economics and Management of Sfax, University of Sfax. Address: Aerodrome Road km 4.5, B.P. 1088-3018, Sfax, Tunisia. Laboratory: Research Laboratory in Competitiveness, Commercial Decisions and Internationalisation (CODECI). E-mail address: kamel.helali@fsegs.usf.tn Telephone number: +216 98667705. Post office: 1146. Fax: +21674279139.
