Key market identification, mechanism transmission, and extreme shock during the risk spillover process: an empirical study of the G20 FOREX markets.

The role of the G20 in global governance has been increasingly prominent in the context of the extensive spread of coronavirus disease 2019 and the aggravation of financial risk contagion. Detecting the risk spillovers among the G20 FOREX markets is crucial to maintain financial stability. Therefore, this paper first adopts a multi-scale approach to measure the risk spillovers among the G20 FOREX markets from 2000 to 2022. Furthermore, the key markets, the transmission mechanism, and the dynamic evolution are researched based on the network analysis. We derive the following findings: (1) The magnitude and volatility of the total risk spillover index of the G20 countries are highly associated with extreme global events. (2) The magnitude and volatility of risk spillovers among the G20 countries are asymmetric in the different extreme global events. (3) The key markets in the risk spillover process are identified, and the USA always occupies a core position in the G20 FOREX risk spillover networks. (4) In the core clique, the risk spillover effect is obviously high. In the clique hierarchy, as the risk spillover effect is transmitted downward, the risk spillovers present the decrease trends. (5) The density, transmission, reciprocity, and clustering degrees in the G20 risk spillover network during the COVID-19 period are much higher than that in other periods.

The linkage between oil price, stock market indices, and exchange rate before, during, and after COVID-19: Empirical insights of Pakistan

This study analyzes the trilateral relationship between macroeconomic variables of oil prices, stock market index, and exchange rate to demonstrate their behavior and inter-relationship in the economic setup of Pakistan. The investigated period includes daily time series data ranging from 4 January 2016 to 30 April 2021. The study consists of three sub-periods: the pre-COVID-19 period ranging from 4 January 2016 to 31 December 2019, COVID-19 period ranging from 1 January 2020 to 30 April 2021, and overall period ranging from 4 January 2016 to 30 April 2021 by using a Vector Autoregressive (VAR) model. The results illustrate that oil prices changes, and stock index have an insignificant direct relationship both in pre-COVID-19 and overall sub-periods of study while a positive and statistically significant relationship during the COVID-19 period. This research also suggests that stock index has a direct and statistically significant but negative impact on the exchange rate in all sub-periods of study. This research also gives practical implications for forex investors and traders to analyze the inflating and deflating stock market patterns for future investment opportunities. However, most of the previous studies emphasized on the direct influence of exchange rate on the stock market and no effort is made on vice versa association. Furthermore, this research presents a practical relevance for the stock market investors that health uncertainty regime affected the insignificant association between oil price and stock market indices and this relation turns out to be significant during the crisis regime.

Supply chain risks of critical metals: Sources, propagation, and responses

In the era of globalization, industries of critical metals are organized through the global supply chain. However, the global supply chains have been disrupted since 2020 by the outbreak of COVID-19 and a series of geopolitical crises. To better address the supply chain challenges of critical metals, a review is needed about the sources, propagation, and responses of the supply chain risks. Firstly, this review provides an overview about the research progress in identifying the risk sources and assessing the risks and then proposes a new supply chain framework, categorizing relevant risk factors into upstream risks, middle-stream risks, downstream risks, and general risks, for risk analysis of critical metals. Secondly, this review offers a comprehensive understanding about how the risks propagate horizontally and vertically. Finally, responses such as supply diversification, stockpiling, material substitution, recycling and circular economy strategy, price volatility hedging, and supply chain traceability are reviewed. This survey features the supply chain perspective, overviews on network-based studies, and affirms the urgency and need for further studies on supply chain risks and resilience, which may contribute to a smooth clean energy transition.

The Impact of Monetary Policy on Real Estate Market during Covid-19 Crisis Using a Dsge Model of a Small Open Economy

Using a new Keynesian small open economy dynamic stochastic general equilibrium model (NK SOE DSGE) with the housing sector, this paper evaluates the impact of housing collateral and changes in openness of economy on the business cycle in the Czech economy. We devote special attention to the setting of the loan to value (LTV) ratio, which we believe plays an important role as a regulator of the monetary transmission mechanism. Moreover, we try to simulate the effects of a reduction in the openness of the economy in the context of an incoming pandemic crisis. The impacts alternative LTV level and openness level setting are quantified by simulating the responses of monetary shock on key macroeconomic variables. Our simulations are based on an estimated DSGE model. Our approach allows a better understanding of the response of the real economy to monetary tightening mitigated by different levels of LTV, and allows a comparison of how these effects change in an environment of altered economic openness. Our results show that higher loan to value ratios strengthen the effect of the monetary transmission mechanism to consumption and output. In contrast, changes in the openness of the economy showed no significant changes in the dynamics of monetary transmission to real variables.

High altitude Relieves transmission risks of COVID-19 through meteorological and environmental factors: Evidence from China.

Existing studies reported higher altitudes reduce the COVID-19 infection rate in the United States, Colombia, and Peru. However, the underlying reasons for this phenomenon remain unclear. In this study, regression analysis and mediating effect model were used in a combination to explore the altitudes relation with the pattern of transmission under their correlation factors. The preliminary linear regression analysis indicated a negative correlation between altitudes and COVID-19 infection in China. In contrast to environmental factors from low-altitude regions (<1500 m), high-altitude regions (>1500 m) exhibited lower PM2.5, average temperature (AT), and mobility, accompanied by high SO2 and absolute humidity (AH). Non-linear regression analysis further revealed that COVID-19 confirmed cases had a positive correlation with mobility, AH, and AT, whereas negatively correlated with SO2, CO, and DTR. Subsequent mediating effect model with altitude-correlated factors, such as mobility, AT, AH, DTR and SO2, suffice to discriminate the COVID-19 infection rate between low- and high-altitude regions. The mentioned evidence advance our understanding of the altitude-mediated COVID-19 transmission mechanism.

Price and Volatility Transmissions among Natural Gas, Fertilizer, and Corn Markets: A Revisit

In this paper, we revisit price and volatility transmission among natural gas, fertilizer, and corn markets;an important issue was explored in previous work. An update of the results is urgently needed due to the recent enormous price volatility in the commodities, fertilizer, and energy markets. We followed the same methodology as previous work and used the vector error correction model and the multivariate generalized autoregressive heteroskedasticity model, but we adopted a new methodology to gather higher frequency data for fertilizer to estimate the interactions and examine the mechanisms between these market prices. Our results are consistent with previous research showing that natural gas price returns in the short-term are significantly affected by its lagged returns from itself and corn markets, and it will be affected by its lagged return sand fertilizer markets. However, we did not find a significant relationship among fertilizer, corn, and natural gas markets from May to November 2021. Moreover, the lagged conditional volatility of corn prices will affect the conditional volatility in the natural gas market but not vice versa.

What influences stock market co-movements between China and its Asia-Pacific trading partners after the Global Financial Crisis?

This paper investigates the stock market co-movements between China and its 12 trading partners in the Asia-Pacific region after the Global Financial Crisis. The Dynamic Conditional Correlation (DCC) - Mixed Data Sampling (MIDAS) model is adopted to extract short and long-run correlations. The author utilizes the weekly conditional correlations to detect contagion and explores transmission mechanisms by regressing the monthly economic and financial variables on the monthly conditional correlations. The empirical results show that recent events (specifically, the Shanghai stock market crash, the US-China tariff war, and the COVID-19 pandemic) have increased the contagion incidences across the stock markets in China and its trading partners. Moreover, bilateral trade and market similarities are major drivers of stock market co-movements between China and developed partners as well as between China and emerging partners. Apart from country-pair-specific factors, common factors (such as the Chinese illiquidity pressure) also affect the co-movements between Chinese and its partners' stock markets during the whole and turmoil periods. Besides, the regression results for contagion episodes are mixed. On the one hand, stock market co-movements are irrelevant to most economic fundamentals, indicating pure contagion. On the other hand, differences in industrial production growth and market size affect stock market co-movements between China and its emerging partners.

How Is the Risk of Major Sudden Infectious Epidemic Transmitted? A Grounded Theory Analysis Based on COVID-19 in China.

The outbreak of a sudden infectious epidemic often causes serious casualties and property losses to the whole society. The COVID-19 epidemic that broke out in China at the end of December 2019, spread rapidly, resulting in large groups of confirmed diagnoses, and causing severe damage to China's society. This epidemic even now encompasses the globe. This paper takes the COVID-19 epidemic that has occurred in China as an example, the original data of this paper is derived from 20 Chinese media reports on COVID-19, and the grounded theory is used to analyze the original data to find the risk transmission rules of a sudden infectious epidemic. The results show that in the risk transmission of a sudden infectious epidemic, there are six basic elements: the risk source, the risk early warning, the risk transmission path, the risk transmission victims, the risk transmission inflection point, and the end of risk transmission. After a sudden infectious epidemic breaks out, there are three risk transmission paths, namely, a medical system risk transmission path, a social system risk transmission path, and a psychological risk transmission path, and these three paths present a coupling structure. These findings in this paper suggest that people should strengthen the emergency management of a sudden infectious epidemic by controlling of the risk source, establishing an efficient and scientific risk early warning mechanism and blocking of the risk transmission paths. The results of this study can provide corresponding policy implications for the emergency management of sudden public health events.

SARS-CoV-2 and other pathogens in municipal wastewater, landfill leachate, and solid waste: A review about virus surveillance, infectivity, and inactivation.

This review discusses the techniques available for detecting and inactivating of pathogens in municipal wastewater, landfill leachate, and solid waste. In view of the current COVID-19 pandemic, SARS-CoV-2 is being given special attention, with a thorough examination of all possible transmission pathways linked to the selected waste matrices. Despite the lack of works focused on landfill leachate, a systematic review method, based on cluster analysis, allows to analyze the available papers devoted to sewage sludge and wastewater, allowing to focalize the work on technologies able to detect and treat pathogens. In this work, great attention is also devoted to infectivity and transmission mechanisms of SARS-CoV-2. Moreover, the literature analysis shows that sewage sludge and landfill leachate seem to have a remote chance to act as a virus transmission route (pollution-to-human transmission) due to improper collection and treatment of municipal wastewater and solid waste. However due to the incertitude about virus infectivity, these possibilities cannot be excluded and need further investigation. As a conclusion, this paper shows that additional research is required not only on the coronavirus-specific disinfection, but also the regular surveillance or monitoring of viral loads in sewage sludge, wastewater, and landfill leachate. The disinfection strategies need to be optimized in terms of dosage and potential adverse impacts like antimicrobial resistance, among many other factors. Finally, the presence of SARS-CoV-2 and other pathogenic microorganisms in sewage sludge, wastewater, and landfill leachate can hamper the possibility to ensure safe water and public health in economically marginalized countries and hinder the realization of the United Nations' sustainable development goals (SDGs).

Food-trade-associated COVID-19 outbreak from a contaminated wholesale food supermarket in Beijing.

The re-emerging outbreak of COVID-19 in Beijing, China, in the summer of 2020 originated from a SARS-CoV-2-infested wholesale food supermarket. We postulated that the Xinfadi market outbreak has links with food-trade activities. Our Susceptible to the disease, Infectious, and Recovered coupled Agent Based Modelling (SIR-ABM) analysis for studying the diffusion of SARS-CoV-2 particles suggested that the trade-distancing strategy effectively reduces the reproduction number (R0). The retail shop closure strategy reduced the number of visitors to the market by nearly half. In addition, the buy-local policy option reduced the infection by more than 70% in total. Therefore, retail closures and buy-local policies could serve as significantly effective strategies that have the potential to reduce the size of the outbreak and prevent probable outbreaks in the future.