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While many recent studies have used the ecological footprint as a comprehensive indicator of environmental degradation instead of CO2 emission, these were mainly focused on consumer responsibility. This study, however, aims to cover both aspects of consumption and production to elicit a more comprehensive understanding. Furthermore, this study addresses another information gap by analyzing the effect of aggregated and disaggregated economic activities on the environment. Panel data were used and sourced from 92 countries classified by income group spanning 1992 to 2015. Comprehensive financial development indicators, energy structure, energy intensity, trade openness, and urbanization were considered in examining their impacts on environmental degradation. The pooled mean group estimation was adopted in examining the long-run and short-run relationship between variables. The main findings suggest that financial development promotes green investment in high-income and upper-middle-income countries but increases degradation in lower-middle and lower-income countries. Renewable energy improves the environment in general, and energy intensity is a crucial factor in environmental modeling across all groups. Most importantly, a U-shape relationship is found on both the consumption and the production side for all income groups except for lower-income countries (inverse U-shape) on the production side. Interestingly, a U-shape relationship was found in high-income and upper-middle-income countries in the industrial sector, but a monotonic relationship in the service sector. A U-shape relationship was found for the industrial and service sectors in lower-middle-income and lower-income countries, but an inverse U-shape for agriculture outputs in lower-middle-income countries. This finding suggests the need to shift from fast-growth strategies to strategic growth planning that considers the nature of the relationship between economic sectors and the environment while diversifying the economic structure to allow for the recovery of natural capital.

This paper investigates the spillover effects of Chinese real and monetary sector shocks on the Belt Road Initiative (BRI) economies. The study adopted a panel vector autoregression (PVAR) estimation technique to analyse the dynamic propagation of Chinese shocks in the real sector (gross domestic product (GDP) and trade openness (OPEN)) and monetary sector (nominal interest rate (NIR)) for a sample of 50 BRI countries from 2000 to 2017. The main results revealed that Chinese income shocks positively spill over to all macroeconomic variables except BRI countries’ consumer price index (CPI). However, the Chinese trade openness shock only has a temporary positive spillover to BRI international trade and a temporary negative spillover on its monetary policy. In addition, the Chinese monetary policy shock has a negative spillover on GDP and a positive spillover on CPI in BRI economies. Chinese shocks, however, do not constitute a significant source of variation in any interest variable. As explained by the Chinese income shock, the BRI interest rate is the highest percentage of variable variation accumulated over time. Further, the highest variation of Chinese trade shock is BRI trade openness, and lastly, the highest variation of Chinese interest rate shock is CPI in BRI economies. The beggar-thy-neighbour effect may dominate the positive trade effect and is a negative impact of the Chinese shocks. Hence, BRI economies should alleviate the adverse shocks since the upcoming rapid growth from the Chinese has disturbed the BRI economies. Our results reveal the importance of Chinese development on BRI partners’ economies and the significance of Chinese shocks in real and monetary sectors in assisting policymakers in designing international and monetary policy for BRI economies.

This paper estimates the comovement between two leading cryptocurrencies and the G7 stock markets. It then attempts to explain the comovement with the rational investment theory by examining whether it is driven by market uncertainty measures, public attention to COVID-19, and the government’s containment and health responses to COVID-19. Wavelet Coherence heatmaps show that the stock-cryptocurrency comovements increase significantly and positively during the pandemic, indicating that cryptocurrencies lose their safe haven properties against stocks during the heightened market uncertainties. Over the longer investment horizons, Bitcoin reemerges as a safe haven or strong hedger while Ethereum’s properties weaken. Seemingly Unrelated Regression results reveal that the stock-cryptocurrency comovements are rationally explained by market uncertainties, government responses to COVID-19, and market fundamentals. However, the comovements are also driven by the fear of COVID-19 to a certain extent. Our findings offer valuable insights for investors considering cryptocurrencies to rebalance their equity portfolios during market distress. For policymakers, the Economic Policy Uncertainty (EPU) results suggest that government policies and regulatory frameworks can be used to regulate speculation and investment activities in the cryptocurrency market.