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PurposeThis paper investigates the causality among gold prices, crude oil prices, bitcoin and stock prices by using daily data from January 2014 to December 2021. The study also examines the data during the COVID-19 outbreak from January 2020 to December 2021.Design/methodology/approachTo estimate the long- and short-run causality, this study considers the nonlinear autoregressive distributed lag (NARDL) cointegration test.FindingsThe analysis found the existence of an asymmetric long-run cointegration among selected assets. Findings indicate that positive changes in bitcoin do not affect stock market in the long term. Changes in crude oil prices have a significant impact on stock prices. Moreover, it is observed that variations in the stock prices trigger a negative impact on gold prices. During the COVID-19 period, the study notices the presence of an asymmetric long-term cointegration between selected assets except bitcoin. Besides, findings revealed that negative price adjustments in gold lead to significant positive shocks in stock market.Originality/valueThese results provide critical information for policy performers and researchers to develop new strategies. Policy regulators can also consider the potential effects of the COVID-19 outbreak while developing strategies for investment decisions.
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Purpose: The purpose of this study is to test the validity of the quantity theory of money (QTM) on South African sectoral data. The rationale of this study and its necessity for South Africa as the case study is that, although aggregate inflation may lie within the target range, inflation at a sectoral level, particularly in the food and transport sector, is still a matter of concern in South Africa. Methodology/approach: This study employed the Non-linear Autoregressive Distributed Lagged model (NARDL) to assess potential asymmetries in the effect of money supply to differentiate between the effects of contractional and expansional episodes on inflation at the sectoral level. Quarterly time series data spanning from 2002Q2 to 2021Q2 was utilised for the estimation. Ultimately, the causal effect amongst the variables is examined by employing the Pairwise Granger Causality test. Findings: The results suggest that in the short run, the effect of monetary policy shocks is very weak. On the other hand, in the long run, both negative and positive shocks in the money supply push inflation at the sectoral level in the opposite directions, and positive shocks (expansionary monetary policy) have a greater effect than negative shocks, which renders the QTM invalid in South Africa. The sectoral response was found to be heterogeneous in the long run, and this was also backed by the results of the Granger Causality test and the dynamic multipliers. Asymmetry in the effect of the money supply is assessed in some of the sectors only in the long run. Practical implications: Based on the results, this study confirms great discrepancies in sectoral responses. Therefore, aggregate inflation may not be a good indicator of the inflation path in South Africa, as it may underestimate sectoral variations. Originality/value: The originality of this study lies on testing the validity of the QTM on inflation at the sectoral level in the South African context using a non-linear approach to assess potential asymmetry between the effects of expansionary and contractionary episodes of monetary policy shocks.
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PurposeIndia is one of those countries that are severely affected by the COVID-19 pandemic. With the upsurge in the cases, the country recorded high unemployment rates, economic uncertainties and slugging growth rates. This adversely affected the real estate sector in India. As the relation of the housing market with the gross domestic product is quite lasting thus, the decline in housing prices has severely impacted the economic growth of the nation. Hence, the purpose of this paper is to gauge the asymmetric impact of COVID-19 shocks on housing prices in India.Design/methodology/approachStudies revealed the symmetric impact of macroeconomic variables, and contingencies on housing prices dominate the literature. However, the assumption of linearity fails to apprehend the asymmetric dynamics of the housing sector. Thus, the author uses a nonlinear autoregressive distributed lag model to address this limitation and test the existence of short- and long-run asymmetry.FindingsThe findings revealed the long- and short-run asymmetric impact of the COVID-19 outbreak and the peak of the COVID-19 on housing prices. The results indicate that the peak of COVID-19 had a greater impact on housing prices in comparison to the outbreak of COVID-19. This can be explained as prices will revert to normal at a speed of 0.978% with the decline in the number of COVID-19 cases. Whereas the housing prices rise at a rate of 0.714 as a result of government intervention to deal with the ill effects of the COVID-19 outbreak. Moreover, it can be inferred that both the outbreak and peak of COVID-19 will lead to a minimal decline in housing prices, while with the decline in the number of cases and reduction in the impact of the outbreak of COVID, the housing prices will rise at an increasing rate.Originality/valueTo the best of the authors' knowledge, this is the first study to understand the impact of the outbreak and peak of COVID-19 on the housing prices separately.
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PurposeThe purpose of this study is to investigate the effect of foreign direct divestments (FDD) on economic growth and development in South Africa for the period 1991–2019.Design/methodology/approachThe non-linear autoregressive distributed lag technique is used for the empirical analysis. Two regression models are specified, one for economic growth and the other for development which is proxied by poverty.FindingsThe empirical results suggest that foreign divestments are detrimental to both economic growth and development. Furthermore, the results suggest that the negative effects of foreign divestments outweigh the positive effects of FDI inflows.Practical implicationsSouth African policymakers should thus use policies that promote the retention of FDI inflows together with those that attract inflows. Furthermore, policies that promote economic freedom such as transparency and reduction in the time frame for granting government permits for business operations are also of paramount importance.Originality/valueMost of the available literature on FDD focuses on the firm perspective. Available studies on the effect of FDD on economic growth do not investigate the effect of divestment on economic development. Economic growth is a necessary but not a sufficient condition for the achievement of socioeconomic development.
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This study uses the structural vector autoregression (SVAR) and nonlinear autoregressive distributed lag (NARDL) models to examine the long- and short-term asymmetric effects of structural state media shocks on the Chinese stock market. The findings, obtained using Xinwen Lianbo as a stand-in for state media, indicate that attention shocks on Xinwen Lianbo have an asymmetrical impact on the aggregate stock market returns in both the short and long run. The sectoral and overall stock market results are similar, with CCTV having a stronger impact in the first half of the pandemic. Employing other COVID-19 news measurements, we validated our primary findings and discovered that the price function differs among various state media's attention to COVID-19.
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This study investigates the effect of global supply chain pressures and crude oil prices on the consumer price index from October 1997 to February 2022 using panel linear and nonlinear autoregressive distributed lags (ARDLs, NARDLs). The results showed that the asymmetric effect of the global supply chain on the inflation rate is stronger when the supply chain increases than when it decreases in the long run for advanced economies and vice versa in emerging markets. A one standard deviation of the supply chain pressures has rebounded the inflation rate by about 1.7% and 0.71% for advanced economies and emerging markets, respectively. The findings establish that a 10 U.S. dollar increase in oil prices leads the inflation rate to rise by 0.1%–0.6% for all countries in the short run. However, the impact of the global supply chain index fits much better with the inflation rate than the oil prices in the short and long run, including the subprime crisis, such as the COVID‐19 outbreak, and the beginning of the Russo–Ukrainian conflict. Thus, the empirical results of the current study provide acumens for policymakers of advanced economies and emerging markets to consume green energy and make use of green technology and environmental innovations for counterbalancing the inflation issues induced by the higher rates of oil prices without halting the economic growth and sustainable development. [ABSTRACT FROM AUTHOR] Copyright of Geological Journal is the property of John Wiley & Sons, Inc. 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 abstract 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 abstract. (Copyright applies to all Abstracts.)
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Globally, the outbreak of COVID‐19 and the associated containment measures adopted by governments are causing disruptions that sow uncertainty in several sectors of the economy. In this study, we explore the asymmetric impact of pandemic uncertainty and global trade policy on food prices in Togo. The study uses a nonlinear autoregressive distributive lag (NARDL) framework and causality tests for the period 2000 M1–2021 M5. The results show that the different types of uncertainty affect food price stability in the short and long run, but the shock is more pronounced in the case of pandemic uncertainty, as they are sudden and disrupt food price stability. The main findings remain significant when we use various alternative methods and estimation techniques. However, our results suggest that the Togolese food market is facing pandemic uncertainty and trade policy, which should lead policymakers and stakeholders to take corrective measures to control losses.
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This research investigates the asymmetric effects of the three major stock prices of the US, Europe, and China on WTI and Brent oil futures prices before and after the COVID-19 announcement by covering weekly data from January 2015 to April 2021. The results of the nonlinear autoregressive distributed lag (NARDL) model show that the US stock price has a significant positive effect in both models prior to the COVID-19 announcement but loses its effect on the WTI oil futures price after the COVID-19 announcement. Its impact on the Brent oil futures price remains after the COVID-19 announcement. The Europe stock price has a significant positive effect in all states. China stock price is not significant in the pre-COVID-19 period, but it has a significant effect after the COVID-19 announcement in both models. However, the only positive asymmetric changes in China stock price show a significant effect on the Brent oil futures price. Before COVID-19, the US stock price is the strongest, while the Europe stock price is the strongest after the COVID-19 announcement.
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Purpose: This study investigates the impact of the COVID-19 pandemic on financial stability in Vietnam, a developing country characterized by a bank-based financial system. Design/methodology/approach: Using a sample of daily data from January 23, 2020 to June 30, 2022, the VECM and NARDL models are employed to study Vietnam's financial stability in face of the COVID-19 disaster. Following the literature on COVID-19, the authors measure the impact of the pandemic by the number of daily infected cases and the national lockdown. Given the reliance of the Vietnamese government on the banking system to regulate the economy, the authors evaluate financial stability from the interbank market and stock market perspectives. Findings: The authors find that the pandemic imposes a destructive effect on financial stability during the early time of the pandemic;however, the analysis with an extended period indicates that this effect gradually fades in the long term. In addition, from the NARDL results, the authors reveal an asymmetric relationship between the financial market and the COVID-19 pandemic in both short term and long term. Research limitations/implications: An implication drawn from this study is that unprecedented health disasters should be resolved by unprecedented stringent countermeasures when conventional methods are ineffective. Although rigorous remedies may increase short-term liabilities, their implementation quickly ceases disease diffusion and helps an economy enter the recovery stage in a timelier manner. Originality/value: The study is the first to examine the impact of the COVID-19 pandemic on financial stability, via the interbank market lens, in a developing country that relies on the bank-based financial system. © 2023, Emerald Publishing Limited.
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Objective: Coronavirus-19 (COVID-19) outbreaks have been reported in a range of climates worldwide, including Bangladesh. There is less evidence of a link between the COVID-19 pandemic and climatic variables. This research article's purpose is to examine the relationship between COVID-19 outbreaks and climatic factors in Dhaka, Bangladesh. Methods: The daily time series COVID-19 data used in this study span from May 1, 2020, to April 14, 2021, for the study area, Dhaka, Bangladesh. The Climatic factors included in this study were average temperature, particulate matter ( P M 2 . 5 ), humidity, carbon emissions, and wind speed within the same timeframe and location. The strength and direction of the relationship between meteorological factors and COVID-19 positive cases are examined using the Spearman correlation. This study examines the asymmetric effect of climatic factors on the COVID-19 pandemic in Dhaka, Bangladesh, using the Nonlinear Autoregressive Distributed Lag (NARDL) model. Results: COVID-19 widespread has a substantial positive association with wind speed (r = .781), temperature (r = .599), and carbon emissions (r = .309), whereas P M 2 . 5 (r = -.178) has a negative relationship at the 1% level of significance. Furthermore, with a 1% change in temperature, the incidence of COVID-19 increased by 1.23% in the short run and 1.53% in the long run, with the remaining variables remaining constant. Similarly, in the short-term, humidity was not significantly related to the COVID-19 pandemic. However, in the long term, it increased 1.13% because of a 1% change in humidity. The changes in PM2.5 level and wind speed are significantly associated with COVID-19 new cases after adjusting population density and the human development index.
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We explore the impacts of economic and financial dislocations caused by COVID-19 pandemic shocks on food sales in the United States from January 2020 to January 2021. We use the US weekly economic index (WEI) to measure economic dislocations and the Chicago Board Options Exchange volatility index (VIX) to capture the broader stock market dislocations. We validate the NARDL model by testing a battery of models using the autoregressive distributed lags (ARDL) methodology (ARDL, NARDL, and QARDL specifications). Our study postulates that an increase in WEI has a significant negative long-term effect on food sales, whereas a decrease in WEI has no statistically significant (long-run) effect. Thus, policy responses that ignore asymmetric effects and hidden cointegration may fail to promote food security during pandemics.
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After rising for decades, carbon emissions fell in 2020 by 2.3 billion tonnes. The objective of the study is to investigate the effect of COVID-19 on carbon emissions in India by employing the nonlinear autoregressive distributed lag model over the period March 25, 2020, to August 31, 2021. Unit root test confirms that all variables are integrated at order I(0) and I(1). Bounds test supports long-run association amongst the variables. Results of the study validate the asymmetric relationship between COVID-19 determinants and CO2 emissions. It presents that lockdown has significantly reduced the CO2 emissions. This asymmetric relationship indicates that COVID-19 has become the major cause of reduction in greenhouse gases, but this cannot be treated as a permanent solution to environmental destruction. Thus, the study suggested that governments and policymakers should formulate FDI policy on high-tech low carbon technology while preparing a strict environmental access system and promote environmentally sustainable investment through subsidies.
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We investigate the impact of macroeconomic surprise and uncertainty on G7 financial markets around COVID-19 pandemic using two real-time, real-activity indexes recently constructed by Scotti (2016). We applies the wavelet analysis to detect the response of the stock markets to the macroeconomic surprise and an uncertainty indexes and then we use NARDL model to examine the asymmetric effect of the news surprise and uncertainty on the equity markets. We conduct our empirical analysis with the daily data from January, 2014 to September, 2020. Our findings indicate that G7 stock markets are sensitive to the macroeconomic surprise and uncertainty and the effect is more pronounced at the long term than the short term. Moreover, we show that the COVID-19 crisis supports the relationship between the macroeconomic indexes and the stock prices. The results are useful for investment decision-making for the investors on the G7 stock indices at different investment horizons.
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This paper explores the asymmetric effect of COVID-19 pandemic news, as measured by the coronavirus indices (Panic, Hype, Fake News, Sentiment, Infodemic, and Media Coverage), on the cryptocurrency market. Using daily data from January 2020 to September 2021 and the exponential generalized autoregressive conditional heteroskedasticity model, the results revealed that both adverse and optimistic news had the same effect on Bitcoin returns, indicating fear of missing out behavior does not prevail. Furthermore, when the nonlinear autoregressive distributed lag model is estimated, both positive and negative shocks in pandemic indices promote Bitcoin's daily changes; thus, Bitcoin is resistant to the SARS-CoV-2 pandemic crisis and may serve as a hedge during market turmoil. The analysis of frequency domain causality supports a unidirectional causality running from the Coronavirus Fake News Index and Sentiment Index to Bitcoin returns, whereas daily fluctuations in the Bitcoin price Granger affect the Coronavirus Panic Index and the Hype Index. These findings may have significant policy implications for investors and governments because they highlight the importance of news during turbulent times. The empirical results indicate that pandemic news could significantly influence Bitcoin's price.
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Globally, the outbreak of COVID-19 and the associated containment measures adopted by governments are causing disruptions that sow uncertainty in several sectors of the economy. In this study, we explore the asymmetric impact of pandemic uncertainty and global trade policy on food prices in Togo. The study uses a nonlinear autoregressive distributive lag (NARDL) framework and causality tests for the period 2000 M1-2021 M5. The results show that the different types of uncertainty affect food price stability in the short and long run, but the shock is more pronounced in the case of pandemic uncertainty, as they are sudden and disrupt food price stability. The main findings remain significant when we use various alternative methods and estimation techniques. However, our results suggest that the Togolese food market is facing pandemic uncertainty and trade policy, which should lead policymakers and stakeholders to take corrective measures to control losses.
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Purpose: This study aims to investigate the asymmetric impact of daily announcements regarding COVID-19 on investor sentiment in the stock market. Design/methodology/approach: This study uses a Non-Linear Autoregressive Distribution Lag (NARDL) model that relies on positive and negative partial sum decompositions of the Coronavirus indicators. Five investor sentiments had been used and the analysis is conducted on the full sample period from 24th February 2020 to 25th March 2021. Findings: The results show that new cases have a greater impact on investor sentiment compared to daily announcements of new deaths related to COVID-19. In addition to revealing a significant impact of new COVID-19 new cases and new death announcements on a daily basis on investor sentiment over the short- and long-term, this paper also highlights the nonlinearity and asymmetry of this relationship in the short and long run. Investors' sentiments are more affected by negative news regarding Covid 19 than positive news. Originality/value: Financial markets have been severely affected by COVID-19 pandemic. This study is the first to measure the extent of reaction of investors to positive and negative announcements of COVID-19. Interestingly, this study examines the asymmetric effect of daily announcements on new cases and new deaths by COVID-19 on investor sentiments and derive many implications for portfolio managers. © 2022, Emerald Publishing Limited.
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This paper estimates the asymmetric relationship between the crude oil market, stock market and COVID-19 pandemic in the case of KSA during the period of March 15, 2020–February 03, 2021. Nonlinear and long-run asymmetric cointegration were utilized for comprehensive research on this topic. Our findings are as follows: positive and negative shocks to the COVID-19 pandemic reduce stock market. Moreover, positive shock to crude oil market increases stock market, but negative shock has a negative and insignificant effect. Based on the results, this study concludes with suitable policy prescription. © 2022, Econjournals. All rights reserved.
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This study constructs a financial stability index for the Islamic financial system of Indonesia using the dynamic factor model and then links it to economic performance employing a nonlinear autoregressive distributed lag (NARDL) model. The financial stability index constructed from a broad range of macrofinancial variables captures well the 2008-2009 global financial crisis and the 2020-2021 COVID 19 pandemic crisis periods. The most significant results suggest that positive and negative shocks in Islamic financial stability in the long run increase and decrease economic performance, respectively. The quantile regression results also demonstrate that Islamic financial stability is statistically significant throughout all quantiles in promoting economic performance, although it plays a greater role at lower quantiles and diminishes when the economic performance is at a high level. Our results highlight that the stability of the Islamic financial system deepening would positively enhance economic performance. © 2021 Asociación Española de Historia Económica.
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The COVID-19 pandemic has led to extensive news coverage, causing investor sentiment to swing, which has further increased financial market price volatility. There is an increasing need to find a hedge against sentiment risk. This paper examines the hedge capabilities of gold and Bitcoin against COVID-19-related news sentiment (CNS) risk under a nonlinear autoregressive distributed lag (NARDL) model. Our empirical results reveal that there is an obvious asymmetric effect from the CNS on gold prices in the short run and that the decrease in the COVID-19-related news index would have a greater impact on gold prices than when it increases. The impact of CNS on Bitcoin prices is asymmetric in the long and short term, especially in the long term. In addition, we conclude that gold is a hedge against CNS risk in the long term, and the hedging effect of Bitcoin is mainly reflected in the short-term.
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In this paper, we employ the NARDL model to examine whether non-fungible tokens (NFTs) can act as hedges and safe havens for stocks, bonds, US dollar, gold, crude oil and Bitcoin. In addition to examining whether NFTs can act as hedges for other assets during the full period (January 1, 2018–March 31, 2022), we also study the hedging properties of NFTs during the pre-COVID-19 period and the safe haven properties of NFTs in times of stress after the COVID-19 outbreak. The empirical results show that in the full period, NFTs are hedges for bonds, US dollar and gold on average;in the pre-COVID-19 period, NFTs are hedges for stocks and US dollar on average;in the COVID-19 period, NFTs can act as safe havens for US dollar. Our empirical findings have important implications for investors looking for hedging and safe haven instruments for major asset classes.