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.

This study investigated the impact of natural resources, urbanization, biological capacity, and economic growth (EG) on the ecological footprint (EFP) in Turkey between 1970 and 2018. The Autoregressive Distributed Lag (ARDL) method was used to investigate the short- and long-term effects. The findings indicate that EG and biological capacity increase the EFP in both the short and long term. In addition to these results, the long-term results show that the Environmental Kuznets Curve (EKC) hypothesis is valid for Turkey and that urbanization has a negative impact on the EFP. The Vector Error Correction Model (VECM) applied to determine the relationship between the variables reveals that, in the short term, unilateral causalities exist from EG to the EFP, from urbanization to economic growth, and from biological capacity to EG. The long-term causality results show a bidirectional causality relationship between the EFP, urbanization and biological capacity. In light of these findings, important policy recommendations are provided for policymakers in Turkey to achieve sustainable growth and improve environmental quality.

Objective: The provision of healthcare facilities remains high on the manifesto of various political parties in Pakistan and healthcare spending has witnessed a significant surge in the last two decades that is expected to positively influence health outcomes in the country. Therefore, this research aims to explore the effects of healthcare expenditures on the actual health status of the masses in Pakistan for the period 1995Q1 to 2017Q1. Methods: We apply the Quantile Autoregressive Distributed Lag (QARDL) approach for estimation purposes. This is the most recent and emerging estimation technique in time series analysis. Results: Our findings confirm that public healthcare spending significantly impacts health outcomes in Pakistan both in the short-run and long-run. Public healthcare spending improves life expectancy and reduces death rate and infant mortality. Conclusion: The study concludes that public healthcare is the main focus of the current regime. It is noticed that spending on healthcare significantly contributes to the health outcomes in Pakistan. These efforts by the government significantly promote life expectancy and drop down the mortality ratio in the country. Based on these notable facts, the government should allocate sufficient resources towards the latest healthcare technologies and equipment to optimize health outcomes in the country.