The coronavirus pandemic has highlighted the capitalist dysfunction showing that considering profit over people can be deadly. The study reveals the LME economies were more responsive toward the impact of the disease outbreaks as compared to the CME economies wherein the impact of the disease was moderated by the government involvement. This allows us to draw that the impact of the disease outbreaks can be moderated by increasing the involvement of the government authorities.

Reducing the urban–rural income gap stands as a pivotal factor in attaining sustainable economic development. Policymakers and researchers have focused on whether digital inclusive finance can narrow the urban–rural income gap. Utilizing provincial-level panel data from 31 regions in China, this paper empirically tests the impact of digital inclusive finance on the urban–rural income gap across different areas of China, specifically analyzing the mediation effect of rural loan availability. The findings indicate that (1) the expansion of digital inclusive finance can enhance the inclusiveness of financial services in rural areas and narrow the urban–rural income gap; (2) the effect of digital inclusive finance on the urban–rural income gap exhibits regional heterogeneity; (3) the rural loan availability has a mediation effect on the urban–rural income gap, but its growth will weaken the narrowing effect of digital inclusive finance on urban–rural income gap; and (4) the reduction in the urban–rural income gap attributable to digital inclusive finance exhibits a nonlinear relationship with the level of urbanization. This paper recommends guiding the digital transformation of rural financial institutions and enhancing farmers’ financial literacy to increase the availability of loans in rural areas. Furthermore, implementing region-specific policies and regulations could effectively narrow the urban–rural income gap.

Large-scale public health emergencies may exert significant adverse effects on market sentiment. This study utilizes interrupted time series analysis (ITSA) to explore the shift in Chinese investors' sentiment in response to the uncertainties due to the outbreak of the COVID-19 pandemic. The empirical findings demonstrate that COVID-19 had a notable impact on investor sentiment within China's stock markets. Before the outbreak of COVID-19, investor sentiment had been on an upward trend. However, since the onset of the pandemic, there has been a sustained decline in investor sentiment, aligning with the downward trend observed in China's stock markets. Interestingly, the immediate effect of the COVID-19 intervention was positive, briefly boosting investor sentiment. As of 2023, with the conclusion of the pandemic and the Chinese government's decision to end the zero COVID-19 policy, we anticipate resurgence in investor sentiment within China's stock markets.

Using the Global Preferences Survey dataset, this paper examines the effects of six measures of preferences (altruism, negative reciprocity, patience, positive reciprocity, risk-taking, and trust) on the per capita international tourist arrivals and the per capita incoming tourist receipts. The data focus on 74 countries for the period from 1995 to 2019. The paper finds that citizens’ trust is positively related to tourism development, and its impact is statistically significant. This evidence indicates that a country with a higher level of trust in other nations’ people attracts more tourists and generates higher tourism receipts.

The economic progress of China cannot be denied; however, deteriorating environmental quality is the primary concern to be addressed. Since the last few years, China’s legislators have intended to facilitate green transformation by sustaining natural resources and ensuring renewable energy consumption. Therefore, this study explores the impact of renewable energy, natural resource green innovation, and economic growth on ecological footprints in China. The bootstrap autoregressive distributed lag (ARDL) model has been deployed by taking the quarterly data ranging between 1990Q1 and 2020Q4. The results reveal that by enhancing green innovation, China can transform its economy into a clean environment. Similarly, the effective utilization of renewable energy consumption is indispensable to reducing the ecological footprint in the long run. Moreover, the Error Correction Term (ECT) is significantly negative, confirming a stable long-run equilibrium relationship between model variables. Similar results are found in the short run; however, the marginal impact of all variables is stronger in the long run. It implies that long-term planning is imperative in China for optimal benefits from renewable energy and green technologies.