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This article explores the dynamic causality between the COVID-19 Media Coverage Index (MCI) in China (Chinese mainland and Hong Kong) and the AH premium index (both price and volatility) by applying a novel time-varying causality technology. Our findings show that the MCIs in China do not significantly cause the log-prices of the AH premium index throughout the full sample period, whereas significantly positive and time-varying causalities from the MCIs in China to the volatilities of the AH premium index are detected. The results thus provide evidence that the change of the MCIs does not lead to a wider or narrower AH premium but unidirectionally causes the change of its volatilities. Furthermore, the effect of MCIs in Chinese mainland on the AH premium volatilities is more pronounced and stable compared to that in Hong Kong, which indicates that the AH premium disparity is more sensitive to the media coverage in the Chinese mainland than in Hong Kong. Finally, the causal relationship from the MCIs in China to the AH premium volatilities disappears after November 2021. Our results provide implications for policymakers to decrease the fluctuation of the AH premium by effectively guiding the trend of media coverage;the results also remind AH stock investors to pay more attention to the COVID-19 media coverage. © 2023, Bucharest University of Economic Studies. All rights reserved.
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Green finance is an essential instrument for achieving sustainable development. Objectively addressing correlations among different green finance markets is conducive to the risk management of investors and regulators. This paper presents evidence on the time-varying correlation effects and causality among the green bond market, green stock market, carbon market, and clean energy market in China at multi-frequency scales by combining the methods of Ensemble Empirical Mode Decomposition Method (EEMD), Dynamic Conditional Correlation (DCC) GARCH model, Time-Varying Parameter Vector Autoregression with Stochastic Volatility Model (TVP-VAR-SV), and Time-varying Causality Test. In general, the significant negative time-varying correlations among most green finance markets indicate a prominent benefit of risk hedging and portfolio diversification among green financial assets. In specific, for different time points and lag periods, the green finance market shock has obvious time-varying, positive and negative alternating effects in the short-term scales, while its time delay and persistence are more pronounced in the medium-term and long-term scales. Interestingly, a positive event shock will generate positive connectivity among most green finance markets, whereas a negative event including the China/U.S. trade friction and the COVID-19 pandemic may exacerbate the reverse linkage among green finance markets. Furthermore, the unidirectional causality of "green bond market - carbon market - green stock and clean energy markets” was established during 2018–2019. © 2023
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PurposeThe study aims to examine the relationship among economic policy uncertainty (EPU), geopolitical-risks (GPR), the interaction (EPGR) of EPU and GPR and the returns of gold, silver, platinum, palladium and rhodium using monthly data from January (1997) to May (2021).Design/methodology/approachThe paper employs the Markov-switching and the novel Shi et al. (2020) bootstrap time-varying Granger-causality approach.FindingsThough the Markov-switching shows variation in the responses of precious metals to EPU, GPR and EPGR across low and high states, the paper observes the safe-haven potential of the precious metals in the high regime while the hedging potency is also evident in the results. To further substantiate the safe-haven and hedging properties, the time-varying Granger-causality shows the causal effect of EPU on all the selected precious metal returns coinciding with global events. While the authors show that GPR Granger causes platinum, palladium and rhodium consistently under the rolling/recursive-evolving tests, the authors cannot find the causal effect of GPR on gold and silver returns across the algorithms. The paper also observes persistence in the causal effect of EPGR on palladium and platinum across all the algorithms, while gold and rhodium only show consistency in the responses under the rolling- and recursive-evolving algorithms given the conditions of homoscedasticity and heteroscedasticity.Practical implicationsThe authors' results are essential to investors and policymakers since both typically leverage the hedging and safe-haven characteristics of precious metals to obviate downside risks during highly uncertain periods.Originality/valueThe authors' techniques allow examining the hedging and safe-haven properties of precious metals across regimes and date-stamp critical periods of causation inherent in the relationship.
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This paper probes the relationship between geopolitical risks (GPR), WTI oil, and gold prices utilizing the time-varying causality and quantile regression approaches. The sample period spans from January 1986 to January 2022, comprising 433 monthly observations and representing the longest common period of data availability. The results show that there is no causality between the pairs of GPR–WTI, and GPR–gold prices for the full sample period, while the causality between gold and WTI is unidirectional, running from gold to WTI. Using the rolling causality test, however, the findings show that the dynamic causal relations strengthen over time. The Granger causality from the gold prices to GPR and WTI is stronger than the other way around, suggesting that the gold market dominates the other two variables in terms of strength of the lead-lag structure of causality. Besides, the findings reveal the strongest causation effects between GPR and WTI spot prices. Before 2009, the causal relationship between WTI and GPR is mostly unidirectional while also a bidirectional linkage emerges, coinciding with the crisis periods including the Dot-Com and 2007 US Subprime crises. During the causal periods, these variables respond negatively to changes in others. For the COVID19 period, the direction of causality considerably changes in favor of WTI for the GPR–WTI pair whereas it is unchanged for the WTI–gold pair. The results indicate that WTI has positive and negative predictive powers for GPR and gold while it receives negative and positive causation effects from GPR and gold during the pandemic, respectively. The results, in overall, may offer important insights for investors and regulatory authorities in building portfolio and risk management strategies as well as pricing and trading activities and constructing monetary policies over various market conditions. Copyright © 2022 Erkan Kara, Remzi Gökb. Published by Vilnius University Press.
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Purpose: This study aims to analyze the relationship between the consequences of the pandemic and the housing sector with econometric tests that allow for structural breaks. Design/methodology/approach: Study data were collected weekly between March 9, 2020, and February 4, 2022, and analyzed for Turkey. In the model of the study, housing loans were used as a housing market indicator, and the number of new deaths and new cases were used as data related to the pandemic. The exchange rate, which affects the use of housing loans, was added to the model as a control variable. This study was analyzed to examine the relationship between the pandemic and the housing sector, time series analysis techniques that allow structural breaks were used. Findings: Based on the result of the analyses, it was concluded that there is a long-run relationship between the pandemic stages and housing markets along with structural breaks. As a result of the time-varying causality test developed to determine the causality relationship between the variables and its direction, a bidirectional causality relationship was identified between all variables at certain dates. Research limitations/implications: Study data were collected weekly between March 9, 2020, and February 4, 2022, and analyzed in the case of Turkey. Practical implications: Based on results of the study, it is recommended that policy makers and market actors take into account extraordinary situations such as pandemics and create a budget allocation that is always ready to use for this purpose. Originality/value: The empirical examination of the relationship between the pandemic and the housing sector in Turkey provides originality to this study in terms of its topic, sample, methodology, contribution to the literature and potential policy recommendations. © 2023, Emerald Publishing Limited.
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The connection between the green economy, technology, and finance has recently become a popular topic for analyzing economic and policy matters. Financial technology can provide not only an opportunity to tap into new pools of private capital to finance green and sustainable projects through innovative financial instruments but also provide support to clean technologies through the adoption of voluntary sustainability codes of conduct. However, there is still a lack of clear scientific evidence in the literature about how the green economy interacts with these relevant indicators of sustainable finance. Thus, this paper examines the time-varying causal relationship between indexes of financial technology (FinTech), clean technology (CleanTech), and the green economy (GECON), by applying the novel method proposed by Shi et al., 2018, Shi et al., 2020 on daily data from June 15, 2012 to December 15, 2021. This study finds a higher volatility and causality running from GECON to CleanTech and FinTech for the entire period. Furthermore, the green economy Granger causes FinTech and CleanTech with very significant episodes, especially at the start of the COVID-19 pandemic. The robustness of the results was checked with a rolling window and recursive evolving techniques that overall confirm bidirectional causal relationships between green economy and technology variables. The findings imply that global initiatives to achieve low-carbon economies need to be complemented with the use of clean technologies in the production process and the continuous digitalization of financial sectors. The promotion of clean technology production by governments and the increased interest of investors in FinTech industries will stimulate green economic growth.
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This study investigates the connection/disconnection between the stock market and macroeconomic fundamentals in the United States from January 1960 to December 2021. Using a recent time-varying Granger causality framework, tests revealed asymmetric bidirectionnal causality. The lead-lag relationships between stock prices and key macroeconomic indicators are more prevalent during recession phases. However, the significance and intensity of the causal relationships during the Covid crisis varied greatly;which could indicate a possible disconnection.
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This paper investigates the dynamic relationships between the crude oil price (COP) and the unemployment rate (UR) in Russia and Canada with a bootstrap subsample rolling-window causality test. This approach relaxes linear assumptions, fully considers structural breaks, and captures time-varying causalities between variables;thus, it performs better than traditional long-run causality tests. The empirical results indicate that there are dynamic causal links between the COP and the UR in certain subsample intervals, which does not fully support Carruth's model. Furthermore, the causality between the COP and the UR in Russia can be described based on Western sanctions, China-Russia energy cooperation and the COVID-19 pandemic. In contrast, a decrease in major oil companies' production and the development of U.S. shale oil are employed to explain the fluctuating relationship between the COP and the UR in Canada. Our study identifies potential heterogeneous reasons for the dynamic causalities of major exporting countries, and it reveals novel influencing mechanisms between these two variables. Thus, some policies are suggested to alleviate shocks from oil prices, including oil risk management and oil cooperation for Russia and oil export structural adjustments and monitoring mechanism establishment for Canada.
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This study attempts to explore the causal linkage of the COVID-19 pandemic, economic policy uncertainty, geopolitical risk, and tourism arrivals in the United States taking data from January to November 2020. In order to analyze the above relationship, this study uses a novel time-varying granger causality test developed by Shi et al. (2018), which incorporates its three causality algorithms such as forward recursive causality, rolling causality, and recursive evolving causality. The findings from forward recursive causality could not confirm any significant causal relationship between COVID-19 and tourism, geopolitical risk (GPR) and tourism, economic policy uncertainty and tourism, and geopolitical risk and COVID-19 but found causality between economic policy uncertainty and COVID-19. The rolling window causality reported bidirectional causality between COVID-19 and tourism and unidirectional causality running from tourism to geopolitical risk. However, the recursive evolving causality identified a significant bidirectional causal relationship between all the variables. Based on the findings, policy implications for the tourism sector are provided.
Subject(s)
COVID-19 , Economic Development , COVID-19/epidemiology , Carbon Dioxide/analysis , Humans , Pandemics , Policy , Uncertainty , United States/epidemiologyABSTRACT
This study reexamines the causal relationship between oil price and economic performance (proxy by GDP returns) in seven selected advanced economies: Australia, Canada, China, the US, the UK, Japan, and Germany. We employ the homoscedastic and heteroscedastic-consistent versions of the Shi et al. (2020) bootstrap time-varying Granger causality to detect and date stamp causal changes in the relationship between oil price and GDP returns of the sample countries. Findings indicate bidirectional causality between oil price and economic performance for at least one month across all sample countries within notable global events such as the global financial crisis and the COVID-19 pandemic. The study also detects and date stamps long periods of causality running from the economic performances of Canada, China, the US, Japan, and Germany to oil prices using GDP returns as a predictor. The results indicate the weight and significance of the predictive power of the GDP growth of these economies in shaping the cyclical fluctuation of oil prices extending through pre and post COVID-19 epidemic. The findings inform some policy implications.
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The literature lacks enough evidence on the nexus of green finance and clean energy although the terms ‘green’ and ‘clean’ have been eminent concepts in sustainable development. Therefore, the fundamental objective of this study is to carry out the causal relationship among green finance, clean energy, environmental responsibility, and green technology by applying the novel time-varying causality test (Shi et al., 2018, 2020) on the daily data spanning from July 31, 2014, to October 12, 2021. The data follow persistent upward and downward movements;thus, the application of a time-varying approach should be reliable and robust. The recursive evolving and rolling window algorithms show bidirectional causalities among green finance, clean energy, environmental responsibility, and green technology, but not for the entire period, and with a special decrease and loss of significance in the COVID-19 period. In addition, clean energy caused by green finance is less evident, except in specific periods, especially at the start of the pandemic. However, higher volatility and significance of causality are observed for the entire period running from clean energy to green finance. Thus, green finance investments are promoted and proportionated by the need for clean energy. This study exhibits the need to design a comprehensive policy for strengthening environmental responsibility and green finance through the funding of green technology to successful energy transition and sustainable development goals.
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Due to the heterogeneity of investor structure between the Chinese mainland stock market (A-share market) and the Hong Kong stock market (H-share market) as well as the limitations on arbitrage activities, most cross-listed stocks in the two markets (AH stocks) have the characteristics of “one asset, two prices”, in which AH stocks with the same vote rights and dividend streams are traded at different prices in different markets. Based on the VAR (LA-VAR as well) model and a four-variable system including AH stock indices (AHXA, AHXH), the China Securities Index 300 (CSI 300), and the Hang Seng Index (HSI), this paper applies a new time-varying causality test to examine the causalities in prices and volatilities for two pairings (AXHA-AHXH pairing and CSI 300-HSI pairing) during the sample period spanning from 4 January 2010 to 21 May 2021. The empirical results exhibit statistically significant time-varying causalities of the two pairings. Specifically, at the price level, AHXH has a significant negative causal effect on AHXA from October 2017 to February 2020 except for several months in 2018, while AHXA merely has a negative impact on AHXA during a short period from March 2017 to May 2017. Of note, the direction of causalities in volatilities between AHXA and AHXH reverses. A positive causality is found from AHXA to AHXH at the 5% significance level during the period of April 2014 through May 2021, while no causality is detected in the opposite direction during the whole sample period. Meanwhile, the volatilities of CSI 300 significantly Granger cause those of HSI over the whole sample period, but not vice versa. Implications of our results are discussed.
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This study examines the causal relationships between oil prices and the MSCI stock index of G7 countries between September 2004 and October 2020. This study is novel in implementing symmetric and asymmetric time-varying causality tests based on the bootstrap rolling-window approach. The results reveal that the causal link between oil prices and G7 stock markets is time-dependent. The periods of bidirectional causality roughly coincide with the global financial crisis and the ongoing COVID-19 pandemic. When asymmetry is accounted for, the results suggest an asymmetric causality between the two markets expressed by different patterns regarding positive and negative oil shocks. The results also indicate symmetric causality during the COVID-19 pandemic. These findings have implications for portfolio design and hedging strategies that are important to both policymakers and investors.