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Dynamics of China's development: Long–short perspectives on institutions, globalization, technology, and environmental quality using auto regressive distributive lag

Author

Listed:
  • Niu Shuhai
  • Ali Zeb
  • Mohsin Rasheed
  • Obaid Ullah
  • Naeem Ud Din

Abstract

This study investigates the connections among institutional quality (IQ), globalization, technological innovation, and environmental sustainability in China, using time‐series data from 1995 to 2022. The autoregressive distributive lag model (ARDL) and Granger causality, stability, and diagnostics approaches were employed for rigorous data analysis. Results of the ARDL test reveal that IQ and technological innovation have a negative and significant impact on carbon dioxide (CO2) emissions in the long run. In the short run, globalization has an insignificant impact on CO2 emissions; on the other hand, IQ, technological innovation, foreign direct investment, and economic growth significantly affect CO2 emissions in China. The result of Granger causality also confirmed unidirectional causality running from globalization, technological innovation, and IQ toward CO2 emissions. Furthermore, the NARDL analyses supported this research's findings. The study suggests that implementing effective environmental regulations, improving governance, and promoting transparency and accountability can enhance the enforcement of environmental policies. Although allowing the limited short‐term impact of globalization, planned global engagement associated with ecological goals is also recommended. Furthermore, policy recommendations include investing in research and development of green technologies, incentivizing companies to adopt eco‐friendly practices, and supporting startups focused on environmental solutions, which can drive positive change toward environmental sustainability in China.

Suggested Citation

  • Niu Shuhai & Ali Zeb & Mohsin Rasheed & Obaid Ullah & Naeem Ud Din, 2026. "Dynamics of China's development: Long–short perspectives on institutions, globalization, technology, and environmental quality using auto regressive distributive lag," Natural Resources Forum, Blackwell Publishing, vol. 50(1), pages 567-594, February.
    • Handle: RePEc:wly:natres:v:50:y:2026:i:1:p:567-594
    DOI: 10.1111/1477-8947.12583
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