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<p>The recent surge in global financial and patent innovations and rising CO<sub>2</sub> emissions in the global energy sector have drawn significant attention to China’s transportation industry. This study examines how financial innovations (FINI), patent innovations (PTIN), and bioenergy (BIOE) affect CO<sub>2</sub> emissions in China’s transportation sector (TBCO<sub>2</sub>) using quarterly data from 2000 to 2018. This study employed a novel wavelet local multiple correlation (WLMC) methodology, alongside the time-varying causality test, to examine the time–frequency nexus, addressing a critical gap in the current literature. The WLMC bivariate analyses revealed a negative long-term relationship between PTIN and FINI with TBCO<sub>2</sub>. At the same time, BIOE showed only a short-term mitigating effect, with PTIN playing a dominant role in this nexus at various frequency levels. Furthermore, the three- and four-variate assessments highlight the consistent positive influence of all included factors on TBCO<sub>2</sub>. A time-varying causality test also demonstrated significant causal relationships between FINI, PTIN, BIOE, and TBCO<sub>2</sub> across different periods, confirming the robustness of our WLMC results. This study provides crucial insights, emphasizing the urgency of promoting FINIs, technological advancement, and bioenergy usage to reduce transportation emissions and pursue sustainable solutions to address China’s environmental challenges.</p>

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China’s transition to sustainable transport assessing the impact of financial innovation, patent innovation, and bioenergy: evidence from an innovative time–frequency analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月15日

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  • Kishwar Ali,
  • Qingyu Zhang,
  • Muhammad Kamran Khan,
  • Zakaria Boulanouar,
  • Fadhila Hamza,
  • Sami Ullah

摘要

The recent surge in global financial and patent innovations and rising CO2 emissions in the global energy sector have drawn significant attention to China’s transportation industry. This study examines how financial innovations (FINI), patent innovations (PTIN), and bioenergy (BIOE) affect CO2 emissions in China’s transportation sector (TBCO2) using quarterly data from 2000 to 2018. This study employed a novel wavelet local multiple correlation (WLMC) methodology, alongside the time-varying causality test, to examine the time–frequency nexus, addressing a critical gap in the current literature. The WLMC bivariate analyses revealed a negative long-term relationship between PTIN and FINI with TBCO2. At the same time, BIOE showed only a short-term mitigating effect, with PTIN playing a dominant role in this nexus at various frequency levels. Furthermore, the three- and four-variate assessments highlight the consistent positive influence of all included factors on TBCO2. A time-varying causality test also demonstrated significant causal relationships between FINI, PTIN, BIOE, and TBCO2 across different periods, confirming the robustness of our WLMC results. This study provides crucial insights, emphasizing the urgency of promoting FINIs, technological advancement, and bioenergy usage to reduce transportation emissions and pursue sustainable solutions to address China’s environmental challenges.