The environmental degradation and the concern for sustainable development have garnered extensive attention from researchers to evaluate the prospects of green bonds over other traditional assets. Against this backdrop, the current study measures the asymmetric relationship between green bonds, U.S. economic policy uncertainty (EPU), and bitcoins by employing the Nonlinear Autoregressive Distribution Lag (NARDL) estimation technique recently developed by Shin et al. The outcome of the empirical analysis confirms an asymmetric cointegration between EPU, bitcoins, the clean energy index, oil prices, and green bonds. The NARDL estimation substantiates that positive shock in EPU exerts a negative impact on green bonds, whereas a negative shock in EPU increases the performance of green bonds. It implies, in the long run, a 1 percent increase (decrease) in EPU decreases (increases) the performance of green bonds by 0.22 percent and 0.11 percent, respectively. Likewise, the study also confirms a bidirectional relationship between bitcoins and green bonds. A positive shock in bitcoin increases the performance of green bonds and vice versa. In addition, our study also reveals a direct co-movement between clean energy, oil prices, and green bonds. This outcome implies that green bonds are not a different asset class, and they mirror the performance of other asset classes, such as clean energy, oil prices, and bitcoins. The findings offer several implications to understand the hedging and diversification properties of bitcoins, and assist in understanding the role of U.S. economic policy uncertainty on green bonds.

The advancement in fintech technological development in emerging countries has accelerated the role of digital finance in economic development. Digital finance assists in financial inclusion; however, it may also increase the chances of financial instability due to systematic risks. Emerging countries are also in the clutches of shadow economic growth, which reduces taxable income revenue and creates pressure on financial inclusion prospects. The current study attempts to measure the impact of digital finance on the shadow economic growth and financial stability among the selected South Asian emerging countries. We have used the CUP-FM and CUP-BC estimation methods to measure the above relationship on two model frameworks from 2004 to 2018, with the former measuring the influence of digital finance on the shadow economy and the latter examining the relationship between digital finance and financial stability. In addition, the second-generation unit root test, and the Westerlund cointegration analysis are also employed to confirm the stationarity and cointegration among the variables. The result of the Westerlund’s cointegration confirms a long cointegration between the explanatory and outcome variables. Furthermore, the long-run estimation results conclude that an increase in digital finance helps in reducing the growth of the shadow economy among the selected sample countries. However, it also increases the likelihood of systematic risks and increases financial instability. The study also reveals that the control variables like unemployment and industrial productivity also have a significant influence on financial stability and the shadow economy. The findings will assist readers in comprehending how digital finance influences the shadow economy and promotes financial inclusion and stability in emerging nations.

COVID-19 is certainly the first sustainability crisis of the 21st century. The paper examines the impact of COVID-19 on the Indian stock and commodity markets during the different phases of lockdown. In addition, the effect of COVID-19 on the Indian stock and commodity markets during the first and second waves of the COVID-19 spread was compared. A comparative analysis of the stock market performances and sustainability of selected South Asian countries is also included in the study, which covers the lockdown period as well as the time frame of the first and second waves of COVID-19 spread. To examine the above relationship, the conventional Welch test, heteroskedastic independent t-test, and the GMM multivariate analysis is employed, on the stock return, gold prices, and oil prices. The findings conclude that during the different phases of lockdown in India, COVID-19 has a negative and significant impact on oil prices and stock market performance. However, in terms of gold prices, the effect is positive and significant. The results of the first wave of COVID-19 infection also corroborate with the above findings. However, the results are contradictory during the second wave of coronavirus infection. Furthermore, the study also substantiates that COVID-19 has significantly affected the stock market performances of selected South Asian countries. However, the impact on the stock market performances was only for a short period and it diminished in the second wave of COVID-19 spread in all the selected South Asian countries. The findings contribute to the research on the stock and commodity market impact of a pandemic by providing empirical evidence that COVID-19 has spill-over effects on stock markets and commodity market performances. This result also helps investors in assessing the trends of the stock and commodity markets during the pandemic outbreak.