Could Cryptocurrency Policy Uncertainty Facilitate US Carbon Neutrality?

Investigating the essential impact of the cryptocurrency market on carbon emissions is significant for the U.S. to realize carbon neutrality. This exploration employs low-frequency vector auto-regression (LF-VAR) and mixed-frequency VAR (MF-VAR) models to capture the complicated interrelationship between cryptocurrency policy uncertainty (CPU) and carbon emission (CE) and to answer the question of whether cryptocurrency policy uncertainty could facilitate U.S. carbon neutrality. By comparison, the MF-VAR model possesses a higher explanatory power than the LF-VAR model;the former's impulse response indicates a negative CPU effect on CE, suggesting that cryptocurrency policy uncertainty is a promoter for the U.S. to realize the goal of carbon neutrality. In turn, CE positively impacts CPU, revealing that mass carbon emissions would raise public and national concerns about the environmental damages caused by cryptocurrency transactions and mining. Furthermore, CPU also has a mediation effect on CE;that is, CPU could affect CE through the oil price (OP). In the context of a more uncertain cryptocurrency market, valuable insights for the U.S. could be offered to realize carbon neutrality by reducing the traditional energy consumption and carbon emissions of cryptocurrency trading and mining.

Real world experience of drug-drug interactions for HCV patients receiving pan-genotypic direct-acting antivirals in the era of COVID-19 pandemic

Background and Aims: The treatment of chronic hepatitis C (CHC) has evolved from genotype-specific to pan-genotypic direct acting antivirals (DAAs) with high efficacy and safety. However, drug-drug interactions (DDIs) must be avoided when used in combination with other medications, especially with the possible concomitant use of COVID-19 infection antivirals during the COVID-19 pandemic. This study aimed to access the potential DDIs of concomitant drugs with pan-genotypic DAAs and COVID-19 infection antivirals, and actual incidence of DDIs in real-world experience. Method(s): From January 2022 to October 2022, consecutive 116 HCV patients receiving pan-genotypic DAAs were retrospectively enrolled in Taipei Veterans General Hospital. The number of comedications and their potential DDIs with three pan-genotypic DAA regimens and three COVID-19 infection antivirals were analyzed. The actual incidence of DDIs during DAAs treatment were also investigated. Result(s): The mean age was 60.9 years old, with male predominant (55.2%). Of them, 12 (10.3%) patients had cirrhosis, and 24 (20.7%) patients had diabetes mellitus. Most patients were within Child-Pugh class A (109/116, 94.0%). The distribution of HCV genotypes was 8.6% in GT 1a, 36.2% in GT 1b, 39.7% in GT 2, 6.9% in GT 6, and 8.6% in indeterminate genotype, respectively. Of them, 43 (37.1%) patients received GLE/PIB, 69 (59.5%) received SOF/VEL 7plusmn;RBV, and 4 (3.4%) received SOF/VEL/VOX as DAAs regimen. Noteworthy, four patients had COVID-19 infection during DAAs treatment course. The rates of ETVR and SVR12 were 97.6% and 95.3%. The mean number of concomitant medications was 2.01. The distribution of concomitant drugs was 64.7% with no concomitant drug, 11.2% with 1-3 drugs, 11.2% with 4-6 drugs, 9.5% with 7-9 drugs, and 3.4% had more than 9 drugs, respectively. In potential contraindicated (red) DDI class, GLE/PIB was the most prevalent (7.3%), followed by SOF/VEL/VOX (6.4%), and SOF/VEL (1.8%) for non-cirrhosis and compensated cirrhosis patients;and no red DDI occurred in decompensated cirrhosis patients. In addition, the percentage of patients without potential DDIs was higher with SOF/VEL (79.8%) than with the other regimens. The potential red DDIs were predominantly with lipid-lowering agents for DAAs. For potential red DDI class with COVID-19 infection antivirals, Nirmatrelvir/Ritonavir was the most prevalent (6%), followed by Remdesivir (0.9%), and no potential DDIs with Molnupiravir. For COVID-19 antivirals, the potential red DDIs was mainly with central nervous system drugs. Finally, the actual incidence of DDIs during DAAs treatment showed no red DDI occurred for all patients, and GLE/PIB was the most prevalent (93%) of no potential DDIs. Conclusion(s): The potential DDIs between these comedications differed, with the most potential DDIs occurring with GLE/PIB and Nirmatrelvir/Ritonavir. After careful assessment of comedications and their potential DDIs, the actual incidence of DDIs could be reduced, and optimize safety in real-world practice.

Can Consumer Credit Stimulate Consumer Confidence? Evidence from the Time-Varying Aspect

This study discusses the nexus between consumer credit (CC) and consumer confidence (CF) in the case of China with a bootstrap rolling-window causality test. The new empirical results demonstrate that CC improves CF in specific periods by loosening liquidity constraints and increasing consumer power temporarily. Meanwhile, a negative link is also found, which can be explained by policy adjustment and financial instabilities. On the contrary, CF negatively influences CC in some periods, reflecting consumers' attitudes toward the future would change borrowing behaviors. But this relationship would be disrupted by government intervention and public events such as the COVID-19 pandemic. The contribution is that time-varying, multiple-directional and dynamic causalities are captured, which enriches the theoretical framework between CC and CF. Therefore, the government must design and adjust loaning policies against specific circumstances and transmit positive signs to consumers. Future study needs to pay attention to different types of CC and try to reveal their heterogeneous influences on CF. In addition, the effect evaluation for CC policy is also another focus in the next research.

Oil prices and the green bond market: Evidence from time-varying and quantile-varying aspects

This paper investigates the link between crude oil prices (COP) and green bonds through a rolling-window Granger-causality test. The positive, negative, and uncorrelated impacts of COP on the green bond index (GBI) are captured with the same sample. The positive effects show that the prosperity of the green bond market is promoted by the high COP, demonstrating that green bonds can avoid shocks from COP. Nevertheless, due to the high profits of the green energy industry and the excess supply on the oil market, the negative impact between COP and GBI is also found. These results are not completely consistent with the price correlation model between oil and green bonds. Furthermore, the positive impact of the GBI on COP shows that green bonds cannot moderate the oil crisis due to COVID-19, instability in the international political environment, and the immaturity of green bonds market. In addition, depending on the quantile Granger-causality test, only high COP affects the GBI, and this asymmetric feature is attributed to increasing production costs and environmental protection pressure. Understanding the nexus between COP and the GBI is of practical significance for bond issuers, regulators, and investors. © 2022 Borsa Ä°stanbul Anonim Åžirketi

Can the green bond market enter a new era under the fluctuation of oil price?

This paper investigates how oil price (OP) influences the prospects of green bonds by utilising the quantile-onquantile (QQ) method and researching the interactions between OP and green bond index (GBI) from 2011:M1 to 2021:M11. We find that impacts from OP on the GBI are positive in the short run. The positive effects indicate that high OP can promote the development of the green bond market, indicating that green bonds can be considered an asset to avoid OP shocks. However, in the medium and long term, there is a negative impact due to the oversupply of the oil market and the increase in green energy industry profits. These results are identical to the supply and demand-based correlation model of green bonds and oil price, which underlines a specific effect of OP on GBI. The GBI effect on OP is consistently positive across all quantiles. It indicates that green bonds cannot be considered efficient measures to alleviate the oil crisis due to the instability of the Middle East COVID-19 and the small scale of green bonds. The issuers of green bonds can make decisions based on OP. Understanding the relationship between OP and GBI is also beneficial for investors. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Is a consumer loan a catalyst for confidence?

In the context of the global economic downturn, the approach guided by consumer loans (CL) to boost consumer confidence is a feasible way to promote the internal circulation of the Chinese economy. Therefore, we use a time-varying rolling-window approach to identify how CL affects the consumer confidence index (CCI). We find that CL can be seen as vital support for promoting confidence because it can ease liquidity constraints and improve consumption levels. The empirical outcome is supported by the Rational Expectations Perpetual Income Hypothesis (RE-PIH), emphasizing that increasing CL can boost consumer confidence. Conversely, CCI has both positive and negative effects on CL. The positive effects suggest that consumers’ optimistic confidence leads them to increase borrowing, which in turn creates a heavier debt burden. This statement cannot be supported by the negative effect due to consumers’ blind self-confidence will cause cognitive bias, which is not conducive to the loan market development. Against the backdrop of increased global uncertainty due to the COVID-19 pandemic and the government’s continuous adjustment of loan policies, consumers can effectively optimise their consumption decision-making through borrowing. The policymaker can maintain loan stability by effectively promoting consumer confidence and raising the consumption level of the whole society. © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

NONLINEAR DEPENDENCE BETWEEN ECONOMIC POLICY UNCERTAINTY AND FDI INFLOWS IN CHINA

Foreign direct investment (FDI) is the most reliable form of international capital flows, and it may be notably prone to increased uncertainty because of its high fixed costs. In this paper, we use the rolling window causality and the quantile-based Granger causality method to investigate the nonlinear dependence between economic policy uncertainty (EPU) and foreign direct investment (FDI) inflows in China for the period between 1999:M06 to 2021:M12. The empirical findings of the study show that EPU exerts a negative impact on FDI inflows during the majority of the time periods that have been studied. However, during the U.S subprime crisis in US, the effect was positive. That is, it can be inferred that the FDI inflows are not always hampered by the Chinese government's economic policy uncertainty. We enlarged our study with the quantile-based Granger causality method to assess robustness. In view of the recent dynamic economic condition and COVID-19 pandemic, the results suggest China's government should focus on more openness and improving its domestic business environment to enhance foreign investors' trust and avoid a possible drop-off in FDI inflows. © 2022, Bucharest University of Economic Studies. All rights reserved.

Can the green bond market enter a new era under the fluctuation of oil price?

This paper investigates how oil price (OP) influences the prospects of green bonds by utilising the quantile-onquantile (QQ) method and researching the interactions between OP and green bond index (GBI) from 2011:M1 to 2021:M11. We find that impacts from OP on the GBI are positive in the short run. The positive effects indicate that high OP can promote the development of the green bond market, indicating that green bonds can be considered an asset to avoid OP shocks. However, in the medium and long term, there is a negative impact due to the oversupply of the oil market and the increase in green energy industry profits. These results are identical to the supply and demand-based correlation model of green bonds and oil price, which underlines a specific effect of OP on GBI. The GBI effect on OP is consistently positive across all quantiles. It indicates that green bonds cannot be considered efficient measures to alleviate the oil crisis due to the instability of the Middle East COVID-19 and the small scale of green bonds. The issuers of green bonds can make decisions based on OP. Understanding the relationship between OP and GBI is also beneficial for investors.

Bitcoin: A safe haven asset and a winner amid political and economic uncertainties in the US?

Bitcoin is considered to be an exclusive marvel of the Fourth Industrial Revolution, and is one of the most sophisticated technological and financial products. It has long been a pivot point of attention for investors who are in pursuit of a safe haven asset. In this paper, we use the wavelet-based quantile-on-quantile method, and the quantile-based Granger causality method, in order to investigate the notion of Bitcoin in actually being a safe-haven asset, amid political and economic uncertainty in the US for the period between 2010:M06, and 2020:M10. Using the Partisan Conflict Index (PCI), and the Economic Policy Uncertainty Index (EPU) as proxies of uncertainties, we find that although Bitcoin effectively appears to be a safe haven asset when uncertainties are on the rise, however, this relationship tends to change during the short- to long-run. In this regard, our sample provides us with a unique opportunity to evaluate the safe haven hypothesis for Bitcoin, amid a time span with three Presidential elections in the US, and recently, an ongoing COVID-19 outbreak, which has been declared as a global pandemic. We have also supplemented our analysis with the bootstrap rolling window causality method, as a measure of robustness. In light of the recent COVID-19 pandemic, and the dynamic economic situation, our work provides valuable knowledge for investors, who wish to construct investment portfolios based on Bitcoin, and also provide insights for regulators about how to regulate the cryptocurrency speculation in an effective manner. © 2021

How does trade policy uncertainty affect agriculture commodity prices?

The present paper explores the impact of trade policy uncertainty (TPU) on agricultural commodity prices (ACP) by employing bootstrap full- and subsample rolling-window Granger causality tests. We find that TPU has both positive and negative effects on ACP, suggesting that TPU may change the supply of and demand for agricultural commodities, leading to fluctuations in ACP. These results support the hypotheses derived from the general equilibrium model, which highlights that TPU can significantly affect ACP. In turn, we find a positive impact of ACP on TPU, indicating that the agricultural commodity market reflects trade conditions in advance. In the context of Sino-U.S. trade frictions and the COVID-19 pandemic, the interaction between TPU and ACP can provide insights for governments to prevent large fluctuations in agricultural commodity markets and stabilize the national economy. © 2021 Elsevier B.V.