Stock Market Response to Covid-19 Pandemic Period In Asian Equity Markets: An Event Study

The purpose of the study was to evaluate the relationshi ps between factors and the variability of Asian Emerging Stock Markets for the time before, during, and following the COVID 19 Outbreak. Descriptive, ADF Test, GARCH (1.1) Model, and Pair-wise Granger Causality Test were used in the research. From the outcomes of empirical analysis, the study found that the information about the COVID 19 Pandemic played a major role in the movement of Asian emerging countries, stock markets. But the fear of a COVID 19 pandemi c exerci sed mi xed i mpact on t he count ry' s market performance. As a result, while investing in the stock markets, the i nvest or shoul d keep a keen wat ch on market movements. International stock market investors in particular, should watch numerous worldwide events, for a sound investment in the global stock markets. © Indian Institute of Finance.

Asymmetric dynamic risk transmission between financial stress and monetary policy uncertainty: thinking in the post-covid-19 world

Considering the dramatically increasing impact of the COVID-19 outbreak on monetary policy and the uncertainty in the financial system, we aim to examine the dynamic asymmetric risk transmission between financial stress and monetary policy uncertainty. Our sample covers 30 years of data. We first employ the conventional Granger causality test to examine the average relationship between financial stress and monetary policy uncertainty, and the results cannot provide evidence of causality between them. However, from an asymmetric perspective, we further detect the strongly apparent existence of the asymmetric structure of causality between them. Finally, we conduct further research on the asymmetric impacts from a time-varying perspective. The time-varying test finds that this relationship can be influenced by major events, especially the dot-com bubble, the 2009 financial crisis, and the current COVID-19 pandemic. Thus, one can learn more information about the influencing mechanism between financial stress and monetary policy with our work, which may be beneficial for making better decisions in the future. © 2023, The Author(s).

A study on the changes in the ICT industry after the COVID-19 pandemic

Purpose: The aim of this paper is to explore the changes in the ICT and global value chains (GVCs) after the COVID-19 pandemic. Design/methodology/approach: This study compared the difference between Korea' domestic ICT industries, ICT imports and ICT exports before and after the COVID-19 outbreak by using trade data of ICT products and national economic indicators, and presents growth strategy for the ICT industry in the post-COVID 19 era. For this purpose, this study determined the causalities between Korea's imports/exports of ICT products and composite Indexes before and after COVID-19, and derived implications in the ICT industry environment after the COVID-19 pandemic. Findings: Analysis results showed the following changes in Korea's ICT industry in the post-COVID-19 world. (1) Non-face-to-face and contact-free technologies related sectors in the ICT industry, such as the semiconductor sector, have grown exponentially;(2) as the USA has grown as the new key player, the causal relationship with China, a key player of the GVC in the pre-COVID-19 era, disappeared;and (3) the GVC of the ICT industry is not a rigid one-way vertical structure, but is changing to a flexible structure influenced by cooperation and competition between countries. Originality/value: The results indicate that it is essential to constantly develop new ICT sectors that make use of non-face-to-face and contact-free technologies in the post-COVID-19 era, and the main strategies in response to the changed GVC would be taking the initiative by securing source technologies and expanding through cooperation with other GVCs and resource sharing. © 2022, Emerald Publishing Limited.

Which is leading: Renewable or brown energy assets?

This study examines the relationship between crude oil, a proxy for brown energy, and several renewable energy stock sector indices (e.g., solar energy, wind energy, bioenergy, and geothermal energy) over various investment horizons. Using daily data from October 15, 2010, to February 23, 2022, we apply a combination of methods involving co-integration, wavelet coherency, and wavelet-based Granger causality. The results show that the relationship between crude oil and renewable energy indices is non-linear and somewhat multifaceted. Firstly, there are sectorial differences in the intensity of the relationships. Notably, the relationship intensity between the wind and crude oil is lower than that involving geothermal energy or bioenergy. Secondly, the relationship evolves with time. For example, the COVID-19 outbreak seems to have increased the relationship between crude oil and renewable energy markets, notably for solar, bioenergy, and geothermal. Thirdly, the relationship varies across scales. When controlling for the VIX (volatility index), a proxy of the sentiment of market participants, and EPU (economic policy uncertainty index), the relationship seems strong in the long term but weak in the short term. This result is confirmed using a Granger causality test on the wavelet-decomposed series. These findings have important implications for long-term investors, short-term speculators, and policymakers regarding the co-movement between brown and renewable energy markets. © 2022 Elsevier B.V.

Panel Vector Auto-Regressive Model For COVID-19 Infected Cases and Deaths

This study aims to model the dynamic relationships between the number of COVID-19 infected cases and deaths in all the districts of Kerala state, India, from January 2021 to December 2021 based on the panel vector auto-regressive model. The random effect panel vector auto-regressive model of order two was found suitable to model dynamic relationships. This model explains 62 % variations in the endogenous variable, deaths (number of deaths). The exogenous variable deaths (-1) are highly significant, whereas the exogenous variable cases (-1) are significant at a 5% level. Both of these exogenous variables positively influence the endogenous variable. The other exogenous variables, viz., deaths (-2) and cases (-2), are non-significant. The Durbin-Watson test statistic value confirms the independence of the residuals, and the Wald test confirms the validity of the significance of the estimated regression coefficients.

Air pollution and mobility in the Mexico City Metropolitan Area in times of COVID-19

This paper analyzes the relation between COVID-19, air pollution, and public transport mobility in the Mexico City Metropolitan Area (MCMA). We test if the restrictions to economic activity introduced to mitigate the spread of COVID-19 are associated with a structural change in air pollution levels and public transport mobility. Our results show that mobility in public transportation was significantly reduced following the government's recommendations. Nonetheless, we show that the reduction in mobility was not accompanied by a reduction in air pollution. Furthermore, Granger-causality tests show that the precedence relation between public transport mobility and air pollution disappeared as a product of the restrictions. Thus, our results suggest that air pollution in the MCMA seems primarily driven by industry and private car usage. In this regard, the government should redouble its efforts to develop policies to reduce industrial pollution and private car usage. © 2023 Universidad Nacional Autónoma de México, Instituto de Ciencias de la Atmósfera y Cambio Climático. This is an open access article under the CC BY-NC License (http://creativecommons.org/licenses/by-nc/4.0/).

Modeling COVID-19 Infected Cases and Deaths Based on Generalized Method of Moments

This paper investigates the dynamic relationships between the number of COVID-19 infected cases and deaths in all the districts of Karnataka state, India, from July 2020 to December 2021 based on the panel Generalized Method of Moments (GMM). The panel GMM model with the first difference transformation was found suitable for studying the dynamics of the number of deaths due to COVID-19 infections over time. The one-period lag (DEATHS (-1)) has a positive and significant effect on the number of deaths (DEATH). The Wald test confirms the validity of the coefficients' significance and adds explanatory power to the model. The correlation between number of fatalities at time t positively correlated with the number of deaths in the previous period. Also, the number of infected cases positively and significantly influences the number of deaths over time. Granger pairwise causality test reveals the existence of bi-directional causality relationships between the COVID-19 infected cases and deaths.

Cointegration Among The Bourse Of BRICS Countries: A Case Of COVID-19 Pandemic

This paper is aim to find out the relationship among stock markets of BRICS Countries during the COVID-19. International investors want different portfolio while investing in other countries and policy makers needs information about the economies of the countries so this paper help them to get the relationship among BRICS countries. To find out the Cointegration among these secondary data has been used from 31st December 2019 to 31st December 2020. ADF and PP Test used to check the stationarity in the data set and VAR Model used to find out the cointegration between these countries and Granger Causality test used to find out the Cause relationship among the stock prices of the BRICS Countries. After analysis this paper finds that a significant integration among the BRICS Countries.

A study on the changes in the ICT industry after the COVID-19 pandemic

Purpose The aim of this paper is to explore the changes in the ICT and global value chains (GVCs) after the COVID-19 pandemic. Design/methodology/approach This study compared the difference between Korea' domestic ICT industries, ICT imports and ICT exports before and after the COVID-19 outbreak by using trade data of ICT products and national economic indicators, and presents growth strategy for the ICT industry in the post-COVID 19 era. For this purpose, this study determined the causalities between Korea's imports/exports of ICT products and composite Indexes before and after COVID-19, and derived implications in the ICT industry environment after the COVID-19 pandemic. Findings Analysis results showed the following changes in Korea's ICT industry in the post-COVID-19 world. (1) Non-face-to-face and contact-free technologies related sectors in the ICT industry, such as the semiconductor sector, have grown exponentially;(2) as the USA has grown as the new key player, the causal relationship with China, a key player of the GVC in the pre-COVID-19 era, disappeared;and (3) the GVC of the ICT industry is not a rigid one-way vertical structure, but is changing to a flexible structure influenced by cooperation and competition between countries. Originality/value The results indicate that it is essential to constantly develop new ICT sectors that make use of non-face-to-face and contact-free technologies in the post-COVID-19 era, and the main strategies in response to the changed GVC would be taking the initiative by securing source technologies and expanding through cooperation with other GVCs and resource sharing.

The Effects of COVID-19 and Workplace Mobility to Stock Price and Exchange Rate in Indonesia: An Econometric Approach

The COVID-19 pandemic has reached its 20th month in Indonesia and still damaged various sectors, particularly economy. The policies imposed by the government impacted mainly the stock price. exchange rate, and people mobility in Indonesia. However, there are limited studies that incorporate these variables in Indonesia context. Thus, this study investigates the relationship between the COVID-19 pandemic, stock price, exchange rate, and workplace mobility simultaneously. This study employs Vector Autoregressive (VAR) as the analysis considering its advantages in finding the causal relationship between variables and periodic interpretation using Impulse Response Function (IRF). The VAR results show that from the Granger Causality Test, it turns out that the shocks from COVID-19 positivity rate and mobility in workplaces caused the changes in stock price and exchange rate. On the other hand, the IRF results exhibit the depreciating responses of stock price and exchange rate due to the shocks of COVID-19 positivity rate and mobility are enormous in the short term. In the longer term, the stock price response needs a longer time to return to the initial condition than the exchange rate. Therefore, further policy evaluation and formulation become essential to maintain the stock price and exchange rate, mainly due to the effect of COVID-19 and workplace mobility. © 2022 IEEE.

Examining the agriculture induced Environmental Kuznets Curve hypothesis in BRICS economies: The role of renewable energy as a moderator

This study uses the economies of Brazil, Russia, India, China and South Africa (BRICS) to examine how economic growth, agriculture, renewable energy, information and communication technology (ICT) and human capital affect carbon emission during the period of 1990–2019. Several econometric techniques such as Pedroni Cointegration test, Mean Group techniques and Pairwise granger causality test are employed. The result from Augmented Mean Group suggests the existence of agriculture induced environmental Kuznets curve hypothesis for BRICS economies. The roles of both the renewable energy and ICT use are negative and significant on the carbon emission. Furthermore, the moderation effect of renewable energy with agriculture shows that it can moderate the agriculture's positive contribution towards the climate change while the moderation effect of ICT and human capital with agriculture do not yield any significant outcomes. The pairwise granger causality result further establishes bidirectional causality between CO 2 emission and renewable energy, ICT and CO 2 , agriculture and GDP, ICT and GDP, renewable energy and agriculture as well as between renewable energy and ICT. Finally, the study provides policy implications and insights for the BRICS governments and policymakers in their efforts to tackle the climate change through the use of renewable energy. [ FROM AUTHOR] Copyright of Renewable Energy: An International Journal is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Spillover Effects of Stock Markets in the COVID-19 Pandemic Period: Evidence From Central and East European Countries

This study aims to investigate the correlation and the spillover effects between Central and East European (CEE) Countries' stock markets during the Covid-19 Pandemic Period. CEE countries are listed as Bulgaria, Croatia, the Czech Republic, Hungary, Poland, Romania, the Slovak Republic, Slovenia, Estonia, Latvia, and Lithuania by OECD. The data set was obtained from the Bloomberg data services and includes 308 observations of daily returns between March 11th, 2020 and August 1st, 2021. As a result of the empirical analysis using the Pearson Correlation, the Multivariate VAR Model, and the Granger Causality Test, a high correlation was found between the stock markets of CEE countries, and 15 causality relationships were determined. The analysis also revealed bidirectional relationships between the Bulgaria Stock Exchange Index and Romania Bucharest Stock Exchange Index, the Polish Warsaw Stock Exchange Index and Croatia Zagreb Stock Exchange Index, the Romania Bucharest Stock Exchange Index and Bulgaria Stock Exchange Index, and the Croatia Zagreb Stock Exchange Index and Polish Warsaw Stock Exchange Index. High correlation and causality relationships, which are also supported by impulse-response and variance decomposition test results, reveal that there is a spillover effect between the stock markets of CEE countries.

The Analysis of Causality and Risk Spillover between Crude Oil and China's Agricultural Futures.

This paper aims to apply the time-varying Granger causality test (TVGC) and the DY Spillover Index (Diebold and Yilmaz, 2012) to measure the Granger causality and dynamic risk spillover effects of the international crude oil futures market on China's agricultural commodity futures market from the perspectives of return and volatility spillovers. Empirical evidence relating to the TVGC test suggests the existence of unidirectional Granger causality between crude oil futures and agricultural product futures. This relationship shows a strong time-varying property, in particular for sudden or extreme events such as financial crises and natural disasters. On the other hand, the volatility spillover in crude oil and agricultural product futures markets responds asymmetrically and bidirectionally according to the result of the DY Spillover index, and the periodicity of total volatility spillover correlates closely with the occurrence of global economic events, which indicates that the spillover effect between crude oil and agricultural commodity futures markets will be exacerbated in turbulent financial and economic times. Such findings are expected to help in formulating policy recommendations, portfolio design, and risk-management decisions.

Contagion Effect of Financial Markets in Crisis: An Analysis Based on the DCC–MGARCH Model

Global crises have created unprecedented challenges for communities and economies across the world, triggering turmoil in global finance and economy. This study adopts the dynamic conditional correlation multiple generalized autoregressive conditional heteroskedasticity (DCC–MGARCH) model to explore contagion effects across financial markets in crisis. The main findings are as follows: (1) the financial crisis and COVID-19 pandemic intensified the connection between the Chinese and US stock markets in the short term;(2) the dynamic conditional correlations (DCCs) during the COVID-19 pandemic are higher than those during the 2008 financial crisis owing to the further opening of the Chinese capital market, and financial institutions’ investments in the European market are higher than those in the American markets;(3) a stepwise increase is observed in the dynamic conditional correlation between the returns on the S&P 500 Index and SSEC during and after the onset of a destructive crisis;and (4) a unidirectional contagion effect exists between the Chinese market and US market, and the Hong Kong stock market contributes to the risk spillover. Effective transmission channels of external negative shocks may be investors’ sentiments, financial institutions, and the RMB exchange rate in the stock markets. This study provides useful suggestions to authorities formulating financial regulations and investors diversifying risk investments.

Panel Cointegration Modelling of COVID-19 Monthly Infected Cases and Deaths

In this paper, the cointegration relationships between COVID-19 new infection cases and the number of deaths due to COVID-19 in all 37 districts of Tamil Nadu state, India, during the period from July 3, 2020 to March 31, 2021 are investigated based on a panel regression Fully Modified Least Squares method and the Granger causality test © 2022. Natural Sciences Publishing Cor

Tourism–Growth Nexus in the Presence of Instability

This paper contributes to the tourism–growth literature by applying the new vector autoregressive-based Granger causality test in the presence of instability to reassess the Granger causality between Hong Kong’s tourism and economic growth. The results of the traditional and recursive Granger causality test under the VAR framework show that the tourism-led economic growth hypothesis (TLEGH) and the economy-driven tourism growth hypothesis (EDTGH) are both unstable in Hong Kong. The results of the vector autoregressive-based Granger causality test in the presence of instability generally support bidirectional causality between tourism and economic growth. However, the relationship between tourism and economic growth is vulnerable to sudden major political incidents, public health incidents, and financial crises. Among these incidents and crises, political events have long-term effects on the relationship between Hong Kong’s tourism and economic growth. In contrast, economic policies, financial crises, and public health emergencies have short-term impacts on the relationship.

Modeling the impact of the COVID-19 outbreak on environment, health sector and energy market

The global outbreak of COVID-19 disease had a significant impact on the entire globe. Such a notable public health event can be seen as a ?black swan? that brings unpredictable and unusual forces into the economic context and that it could typically lead to a chain of adverse reactions and market disruptions. Hence, the purpose of this study is to examine how COVID-19 affects the environment, health, and the oil and energy markets. To achieve this objective, we used daily data for several measures that refer to the environment, health, and oil and energy, for the first wave of the COVID-19 pandemic (December 31, 2019?May 22, 2020). The variable integration mix led to the approach of the ARDL model, and the Granger causality test was also employed. These empirical techniques allowed us to examine the cointegration between variables and causal relationships. The econometric results of the ARDL models exhibited that the global new cases and new deaths of COVID-19 have short and long-term effects on the environment, the health sector, the oil, and energy measures. However, no significant causal connection was found between the pandemic and the environment, the health sector, or the oil and energy industry, according to the Granger causality test. The uniqueness of current approach consists in the investigation of pandemic impact on the health, environment, oil, and energy sector by applying the ARDL model that permits the analysis of cointegration both in the long run and in the short term. This study provides important insights for investors and policy makers.

Facing COVID-19 in China and the US: Do we have the same emotions?

COVID-19, a global pandemic, has provided a unique background for examining the commonalities and differences in the rules of public mood change under different cultures. This study used China and the United States as the representative countries of tight and loose cultures, respectively. We constructed an attention index of the pandemic and five emotion indexes of China and the US, respectively, to examine the commonness of human emotional responses to crises and the gradual change law among different types of emotions, and the influence of tight-loose cultures on various kinds of public emotions. The trend data of Baidu Index and Google Trends was collected for a three-step analysis. First, the time series chart of the attention index and public emotion index of the COVID-19 pandemic in the two countries were compared;Second, the Granger causality test was used to analyze the relationship among different types of emotions. Finally, the differences in the proportion of various emotional indexes during the outbreak period between China and the US were compared using the t-test. The results showed that in both countries, fear was the dominant emotion at the beginning of the pandemic, and it was gradually taken over by depression and sadness. We also found that fear and anger can be used to predict sadness and depression in the middle and long term. Moreover, our data showed that the proportion of anger and fear in China was significantly higher than that in the US, while the proportion of sadness in China was significantly lower. The positive emotion index was significantly higher in China than in the US. The results can relatively verify the response to stress at the group level and the psychological characteristics of tight-loose cultures, which to some extent can be used as a general reference for crisis psychological assistance under different cultures. © 2021 IEEE

Vector Error Correction Modeling of COVID-19 Infected Cases and Deaths

The main objective of this paper is to investigate the dynamic relationship between the COVID-19 infected cases and the number of deaths due to COVID-19 using the Johnsen-Fisher co-integration test, vector error correction model and Granger causality test. The daily COVID-19-infected new cases and daily deaths due to COVID-19 in the United States, Canada, Ukraine and India were collected from the website for the period from 01-04-2020 to 26-12-2020. The summary statistics revealed that the highest numbers of COVID-19-infected cases were registered in the United States, followed by India, Canada and Ukraine;the highest numbers of deaths due to COVID-19 were registered in the United States, followed by India, Ukraine and Canada. The death percentage is exceedingly high in Canada, followed by the United States, Ukraine and India. The Johnsen-Fisher co-integration test results reveal the existence of one co-integration equation. The vector error correction model and Granger causality test reveal that long-term and short-term causality exists between COVID-19 infection and death cases. The speed of adjustment is found to be 9.9%. © 2022 NSP Natural Sciences Publishing Cor.

Diverging from News Media: An Exploratory Study on the Changing Dynamics between Media and Public Attention on Cancer in China from 2011-2020.

Over the past decade, China has witnessed fast-paced technological advancements in the media industry, as well as major shifts in the health agenda portrayed in the media. Therefore, a key starting point when discussing health communication lies in whether media attention and public attention towards health issues are structurally aligned, and to what extent the news media guides public attention. Based on data mined from 73,060 sets of the Baidu Search Index and Media Index on 20 terms covering different types of cancer from 2011 to 2020, the Granger test demonstrates that, in the last decade, public attention and media attention towards cancer in China has gone through two distinct phases. During the first phase, 2011-2015, Chinese news media still held the key in transferring the salience of issues on most cancer types to the public. In the second phase, from 2016-2020, public attention towards cancer has gradually diverged from media coverage, mirroring the imbalance and mismatch between the demand of active public and the supply of cancer information from news media. This study provides an overview of the dynamic transition on cancer issues in China over a ten-year span, along with descriptive results on public and media attention towards specific cancer types.