This paper investigates the dynamic interactions between green finance, economic growth, and green energy consumption for the Organization of Economic Cooperation and Development (OECD) members. The econometric analysis is conducted on annual data gathered throughout 2010–2020 using different estimation techniques of the Vector Autoregressive model, causality, and co-integration approaches. The main results confirmed a positive bi-directional relationship between GDP and green energy consumption. In addition, there is a two-way relationship between the volume of green bond issuance and the use of green energy in OECD countries. The recommended practical policy recommendations are establishing a unified green bonds market among OECD member states, prioritizing green projects to support the issued green bonds, improving the financial system, and financing rural electrification and electric vehicle transition by green bonds.

This paper examines the effects of the pandemics-related uncertainty on corporate innovation in Chinese firms. For this purpose, the recent uncertainty measure of pandemics, the Pandemics Discussion Index (PDI), is used. The findings from the fixed-effects estimations show the negative impact of the PDI on corporate innovation. Government subsidies, operation profits, and total exports also positively affect corporate innovation. In addition, firms' management efficiency promotes corporate innovation. These results hold when the Blundell-Bond estimations are utilized to address potential endogeneity. Various robustness analyses, such as considering the lagged PDI and the lagged controls, are also conducted. Consequently, the main results remain robust. Thus, this paper provides novel and robust evidence on the negative impact of pandemics on Chinese firms' corporate innovation behavior.

To improve the level of oral English teaching, improve students’ oral communicative competence (OCA), and promote successful communication with native English speakers, this study studies the pragmatic function of dialogue markers and constructs the cognitive evaluation system of artificial intelligence (AI) by comparing the two cognitive evaluation systems of human subjectivity and knowledge base; in this study, the credibility of human subjective evaluation and the coupling degree of machine objective evaluation are discussed. The key coefficient R2 is obtained by the linear regression method, and the correlation is obtained by the Spearman correlation algorithm. The cognitive effects of knowledge base and AI are verified; the results show that the cognitive analysis system of pragmatic function of discourse markers in oral English based on AI has good teaching value. In the context of AI computing, we can put forward targeted learning methods and learning methods for students according to the amount and accuracy of markers in oral English that students have mastered, so that students can quickly improve the learning quality and the learning effect of oral English markers, which is more conducive to improving students’ oral English level and realizing students’ effective communication.

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