Spillover Analysis Research Articles

The Impact of the Ukrainian Crisis and Global Shocks on Stock Market Connectedness in Sub-Saharan Africa: Evidence from Diebold and Yilmaz (2012) Spillover Analysis

The Impact of the Ukrainian Crisis and Global Shocks on Stock Market Connectedness in Sub-Saharan Africa: Evidence from Diebold and Yilmaz (2012) Spillover Analysis

Has the ecological civilization pilot promoted the transformation of industrial structure in China?

Industrial structure transformation is important for realizing Chinese modernization, and ecological civilization is necessary for building a beautiful China. How to use the construction of ecological civilization to realize industrial structure transformation is a major issue for the economic development of China and other developing countries. The difference-in-differences method was used to evaluate the impact of the ecological civilization pilot policy (ECPP) on industrial structure transformation. The three-stage mediating effect method is used to explore the mechanism channel. Through heterogeneity discussion and spatial spillover analysis method, the effects of ECPP were further understood. The study reveals the following: Overall, the ECPP has promoted the transformation of the industrial structure. Specifically, the ECPP has a significant positive impact on industrial structure rationalization but a negative impact on industrial structure advancement. Several robustness checks support this finding. Second, the mechanism channels are primarily achieved through environmental investment, green finance infusion, and congestion alleviation. Third, good central-local relationships can enhance the trend toward industrial structure rationalization, while unfavorable relationships may pose hindrances to industrial structure advancement. In addition, the effect of the ECPP varies depending on the population density and environmental pollution. Lastly, the ECPP has a spatial positive spillover effect promoting industrial structure rationalization. The results above provide additional information about the effects of ECPPs on industrial structure transformation, both positive and negative, and help the ecological civilization strategy system be adjusted promptly.

Higher-order moment risk spillovers and optimal portfolio strategies in global oil markets

Investigating the dynamic interdependencies and risk connectedness in global oil markets is paramount for investors and regulatory bodies. Nevertheless, prevailing research has predominantly focused on the examination of lower-order moments, thereby imposing limitations on the extent of inquiry. This paper undertakes an analysis of higher-order moment risk spillovers in global oil markets employing the innovative time-varying parameter vector autoregression (TVP-VAR) extended joint connectedness approach. Moreover, this study pioneers the construction of minimum connectedness portfolio strategies encompassing oil markets worldwide, incorporating the outcomes of higher-order moment risk connectedness into multivariate portfolio construction. Our empirical investigation unequivocally highlights the ascendance of OPEC oil as the preeminent net transmitter of connectedness across all moments, reinforcing its pivotal role in the transmission of risk. Furthermore, our findings disclose significant heterogeneity in the connectedness outcomes, with discernible variations across diverse moment orders. Remarkably, the oil benchmarks of WTI and Brent undergo a discernible transformation, transitioning into net recipients when subjected to higher-order moment risk spillovers. Additionally, the dynamics of equicorrelations, pairwise correlations, as well as the time-varying total, net, and net-pairwise connectedness indices, exhibit a high degree of responsiveness to major crisis events. Finally, the incorporation of higher-order moment risk spillovers into oil portfolio strategies manifests enhanced efficacy in risk management. The policy implications derived from our findings bear practical significance for an array of stakeholders, including cross-market investors, portfolio managers, regulatory entities, and policymakers.

Do stochastic risks flow between industrial and precious metals, Islamic stocks, green bonds, green stocks, clean investments, major foreign exchange rates, and Bitcoin?

This study examines the interactions between Bitcoin (BTC) and other major financial markets (forex, equity and bond, and industrial and precious metals). This interaction is viewed from the spectrum of spillover analysis, hedging, and portfolio analyses. Due to the high volatility and volatility clustering nature of most financial series, particularly BTC, we rely on a Multivariate Factor Stochastic Volatility (mvFSV) Model of Kastner et al. (2017). In order to capture the influence of extreme market conditions, we use a quantile-based mvFSV Model. Among other things, results confirm the importance of quantile analysis as results are sensitive to market conditions. For instance, currencies and industrial and precious metals are net transmitters of shocks at lower and middle quantiles, while these assets change their status to the net receiver of shocks at the upper quantile. Results of the total connectedness show that there is a high degree of interconnectedness among the assets, as the total connectedness index ranges between 86% and 100%. Besides, Islamic equities perform such as the most currencies and conventional assets in terms of the transmission of shocks and diversification benefits. The hedging potentials of Bitcoin over other assets were also examined, and results confirm that the hedging effectiveness is commodity-specific. Policy implications of these results are discussed.

Understanding Systemic Risk Dynamics and Economic Growth: Evidence from the Turkish Banking System

The banking crisis experienced at the beginning of 2023 in the aftermath of the global 2008 crisis served as a stark reminder of the importance of systemic risk once again across the world. This study examines the dynamics of systemic risk in the Turkish banking system and its impact on sustainable economic growth between the period of 2007 and 2022. Through the Component Expected Shortfall (CES) method and quantile spillover analysis, private banks, such as Garanti Bank (GARAN), Akbank (AKBNK), İş Bank (ISCTR), and Yapı ve Kredi Bank (YKBNK), are identified as major sources of systemic risk. The analysis reveals a high level of interconnectedness among the banks during market downturns, with TSKB, Vakıfbank (VAKBNK), İş Bank (ISCTR), Halk Bank (HALKB), Akbank (AKBNK), Yapı ve Kredi Bank (YKBNK), and Garanti Bank (GARAN) serving as net risk transmitters, while QNB Finansbank (QNBFB), ICBC Turkey Bank (ICBCT), Şekerbank (SKBNK), GSD Holding (GSD), and Albaraka Türk (ALBRK) act as net risk receivers. Employing the Markov switching VAR (MS-VAR) model, the study finds that increased systemic risk significantly reduces economic growth during heightened financial periods. These findings underscore the importance of monitoring systemic risks and implementing proactive measures in the banking sector. The policy implications highlight the requirement for regulators and policymakers to prioritize systemic risk management. Close monitoring helps detect weaknesses and imbalances that could put financial stability at risk. Timely implementation of policies and rules is crucial in the prevention of the accumulation of systemic risks and in dealing with the existing hazards. Such measures protect the stability of the banking sector and mitigate potential negative effects on the broader economy.

Natural resources and green economic recovery in responsible investments: Role of ESG in context of Islamic sustainable investments

This study investigates the dynamic interactions between fossil fuel-free, ESG, and carbon-efficient investments and government stimulus in Europe before and after COVID-19. Using time-varying analysis, results show ESG investments benefited most from stimulus packages when looking at average performance. However, separating pre- and post-pandemic periods revealed more nuanced results. Pre-COVID, least-volatile carbon-efficient companies spilled over to stimulus beneficiaries, but post-COVID they benefitted from them. Islamic-screened sustainable investments were net receivers regardless of period. In contrast, conventional ESG and fossil fuel-free industries behaved oppositely to low-risk eco-friendly firms, transmitting benefits to stimulus recipients. Causality tests confirmed spillover analysis, showing nonlinear causality from stimulus recipients to Islamic investments across conditions and low-risk climate-conscious investments at lower quantiles. In summary, this study provides new perspectives on chain reactions between government-supported firms and purpose-driven enterprises, helping recovery planners and policymakers make more informed sustainable investment decisions.

New evidence on the impact of No-tillage management on agricultural carbon emissions.

Controlling agricultural carbon emissions contributes to achieving peak carbon emissions and carbon neutrality. However, as a conservation management practice of farmland, the impact of No-tillage management (NTM) on agricultural carbon emissions needs to be further discussed. The main purpose of this paper is to assess the direct effect and spatial spillover effect of NTM on agricultural carbon emissions, revealing the regulating mechanism of NTM on agricultural carbon emissions and the combined application of NTM. Results indicate that NTM reduces agricultural carbon emissions, which is significant in the central and western regions, along with the primary grain, corn, and rice production areas, as well as the northern regions of the Huai River. Furthermore, the spatial spillover analysis reveals that the implementation of NTM increases agricultural carbon emissions in neighboring regions, but financial support and cross-regional services can negatively regulate the relationship between NTM and space agricultural carbon emissions. This paper also finds that combining straw-returning technology and NTM reduces agricultural carbon emissions. Building a cross-regional coordination mechanism, an incentive mechanism, and innovating the conservation tillage model is essential for promoting the NTM and achieving agricultural carbon reduction.

Extreme risk dependence between green bonds and financial markets

AbstractThe current study investigates the extreme risk dependence between green bonds and financial markets by employing the dual approaches of time‐varying optimal copula and extreme risk spillover analysis of dynamic conditional Value‐at‐Risk. We report significant symmetric (asymmetric) tail‐dependent copulas in the upper (lower) tails characterizing independent regimes. Green bonds offer sufficient diversification, safe‐haven, and hedging opportunities during stable and distressing times to financial markets. The extreme risk spillovers revealed that COVID‐19 transformed the spillovers between green bonds and financial markets except Bitcoin. We proposed insightful implications for policymakers, governments, investors, and portfolio managers to relish the findings for their investment avenues.

Assessing innovation spillovers from publicly funded R&D and innovation support: Evidence from the UK

Knowledgeembodied, explicit, and tacit - drives innovation. Research and development and other knowledge creation activities play a key role, as does the type of external knowledge sourcing central to models of open innovation. As knowledge is a semi-public or public good, however, firms may also obtain knowledge unintentionally through spillovers. We provide the first comprehensive analysis of the innovation spillovers from publicly funded R&D and innovation support activities in the UK to non-participating firms. Analysis is based on matched data from Gateway to Research, the UK Innovation Survey and the Business Structures Database. Conceptually we differentiate between horizontal (intra-industry), vertical (inter-industry) and university spillovers, each of which have different impacts. We also differentiate between the type of firms impacted by spillovers of each type and their position inside and outside clusters. Both reflect firms’ ability to appropriate spillover benefits. Spillovers prove weak in some instances and often limited in scale. University spillovers prove weak, although there is some evidence of a positive effect on patenting in high-tech and larger firms, and on new-to-the-market innovation in low-tech firms. Horizontal spillovers effects prove strongest in some rather specific regions, perhaps reflecting the relevance of industrial clustering in mediating knowledge spillovers, while vertical (inter-industry) effects prove more significant across a wider range of areas. Our study sheds new light on the mechanisms through which investment in the public science system has unintended innovation effects.

Carbon emissions trading schemes and economic growth: New evidence on the Porter Hypothesis from 285 China's prefecture-level cities.

The Chinese government has established carbon emissions trading schemes (CETS) to cope with climate change and reduce carbon emissions. This paper uses the multi-period difference in difference (DID) model to explore the impact of CETS on cities' GDP and GDP growth rates in China based on data from 285 prefecture-level cities from 2008-2019. We find that CETS increase the level of GDP by 3.4% and the GDP growth rate by 0.004. The mechanism of increasing GDP includes promoting investment and innovation, and the mechanism of increasing the GDP growth rate includes only promoting the investment growth rate. Thus, CETS satisfy both the weak and strong versions of the Porter Hypothesis from the GDP and growth rate perspectives. In the heterogeneity analysis, we find that the impacts of CETS on cities' GDP and GDP growth rates decrease with the increase of the corresponding dependent variable. In the spatial spillover analysis, we find that the establishment of CETS has a positive spillover effect on the GDP of cities around 50 km and 150 km, and a negative spillover effect on the GDP of cities around 200 km, but there is no spatial spillover effect on the GDP growth rate.

Does the development of digital economy alleviate environmental problems-empirical evidence from the Yangtze River economic belt

The digital economy has become a new driving force for economic development. This paper takes 11 provinces and cities in the Yangtze River Economic Belt as research objects, constructs comprehensive evaluation indicators of environmental problems and digital economy, uses panel data of 11 provinces and cities in the Yangtze River Economic Belt from 2011 to 2020, and applies various econometric models to empirically test the impact of digital economy development on environmental problems in multiple dimensions. It was found that the development of the digital economy in the Yangtze River Economic Belt significantly mitigates environmental problems, a conclusion that still holds after the robustness analysis. The mediation analysis indicates that the development of the digital economy mitigates environmental problems through industrial structural upgrading and green technology innovation. The heterogeneity analysis shows that the digital economy development in the downstream areas of the Yangtze River Economic Belt has the largest environmental improvement effect and the smallest in the midstream areas. Spatial spillover analysis shows that digital economy development in the Yangtze River Economic Belt has significantly reduced environmental problems in surrounding areas through spatial spillover effects. The findings of the study provide empirical evidence that the development of the digital economy can mitigate environmental problems, and also serve as a policy reference for developing the digital economy and bringing the environmental improvement role of the digital economy into play.

How does digitalization drive carbon emissions? The inverted U-shaped effect in China

Digitalization has become an engine driving industrial transformation and social change; however, the impact on carbon emissions during digital transformation remains poorly understood. We used the Tencent Digitalization Index based on big data to explore the effects of digital development on carbon emissions in China's 281 cities. The results show that the impact of digitization on carbon emissions follows an inverted U-curve in China, supported by a series of robustness tests. Considering city geographical location and resource endowment, this non-linear effect of digitalization on carbon emissions is more significant in eastern and non-resource-based cities. The inverted U-shaped impact of digitalization in central and western cities is not significant and resource-based cities have not yet reached the carbon reduction inflection point. Spatial spillover analysis indicates that digitalization will reduce carbon emissions of neighboring cities in the mature digital period. Digitalization also affects carbon emissions by promoting industrial structure upgrading and economic development. Understanding the relationship between digitalization and carbon emissions is a key ingredient for urban sustainable transformation, representing crucial knowledge for building climate-resilient cities and for policy-making.

Bitcoin vs. fiat currencies: Insights from extreme dependence and risk spillover analysis with financial markets

We compare Bitcoin to fiat currencies (EUR, GBP, and JPY) using extreme dependence and temporal dynamic risk spillover analysis with various financial markets covering fixed-income, stock, and commodity indices. Using daily data from October 2010 to December 2022, covering various stress periods including the COVID-19 outbreak and the war in Ukraine, the results are summarized as follows. First, there is a similarity during the bearish market between Bitcoin and fiat currency markets regarding their relationships with fixed-income and gold markets in terms of temporal dynamic upside and downside risk spillover impacts despite the dissimilarity in their tail dependence structures. Thus, Bitcoin and fiat currency markets emerge as very feasible investments due to their insensitivity to the downside risk associated with fixed-income and gold markets. Second, there is a clear difference between Bitcoin and fiat currencies in their relationship with stock and crude oil markets based on the temporal dynamic upside and downside risk spillovers. Investors in stock and crude oil markets should consider fiat currencies for diversification purposes whereas these investors should take a short position on Bitcoin to protect their portfolio against downside extreme events such as the COVID-19 outbreak and Russia–Ukraine conflict. Our findings have implications for investors in terms of how they can protect their portfolios against extreme downward price movements.

Time-Varying Relationship and Volatility Spillovers Among Oil, Gold, Forex and Stock Markets in Indian Context: The Juxtaposition of Global Economic Crisis and COVID-19 Pandemic

This article explores the dynamic interdependencies, returns and volatility spillovers among oil, gold, foreign exchange and equity markets. It also compares how the leading and most active commodity markets, forex and equity markets reacted to each other during the period of the global economic crisis and COVID-19 pandemic. The time-varying relationship between oil and gold, oil and forex and gold and exchange rate is predominantly positive, whereas it is negative for oil and stock price, gold and stock price and exchange rate and stock price. This continues to hold even in the crisis period, except for the oil and stock price relationship during the COVID-19 crisis. However, the degrees of relationship significantly high during both crises. The returns and volatility spillovers obtained from forecasted error variance decomposition based on vector autoregression show that the spillovers among these four markets remained low for the whole period but drastically increased during both crises. Compared to the return spillover, the volatility spillover is strong in the crisis period and was too high during the COVID-19 crisis. The rolling-sample spillover analysis shows that both return and volatility spillovers significantly vary across different periods, and the volatility spillovers are predominant. JEL Codes: C32, F31, G15, Q40

Effects of COVID-19 on green bonds, renewable power stocks, and carbon markets: A dynamic spillover analysis

This study investigates the effects of the COVID-19 pandemic on green bonds, carbon pricing, and renewable energy equities. It uses daily data from January 4, 2015, to September 22, 2020. The dataset includes the price indices for Standard and Green Bond, Selective International Solar, Wind, S&P Global Sustainable Energy, and Carbon to explore return spillover and connectedness. This study investigates the use of the TVP-VAR approach with least variance collection by economic events. Additionally, a spillover dynamic connectedness model was implemented for robustness. Our findings indicate that the implied dynamic connectedness and effectiveness of green-bound assets are long- and short-term positions in the green bound against volatilities. Specifically, clean energy uses connectedness as the primary net transmitter of shocks from green bond markets and renewable energy during COVID-19. This study provides evidence that a high interconnection between green bonds highlights multivariate portfolios. Finally, the green bound, with the lowest dynamic connectedness information regarding the return transmission process, was useful for renewable energy, during the COVID-19 pandemic, a similar pattern was found.

Business activity and business confidence: a new volatility transmission relationship

PurposeThe purpose of this study is to examine the transmission of volatility between business confidence index and stock market indices in Greece. The country remains the riskiest project in European Union (EU) and previous studies fail to reach an accurate conclusion regarding the direction of this transmission.Design/methodology/approachThe study covers the period from January 2013 to August 2022 in monthly basis where important economic events occur. Considering that these economic events derive strong volatility moments, the authors adopt a new methodology that measures the transmission of volatility with higher precision. This is the generalized spillover analysis by Diebold and Yilmaz (2009, 2012).FindingsThe results indicate that Business Confidence Index (BCI) is the main receiver of volatility spillovers in Greece under all aspects of the used methodology. The specificity of the results shows that business activity through a green growth model is what drives investor confidence and then their activities.Originality/valueAlthough a handful of studies have considered the transmission of volatility between BCI and stock market indices, this study contributes in several ways. This study focuses on one country (Greece), avoiding the dispersion of the results from the examination of the relationship in several countries. The used country remains the riskiest project in EU even nowadays, while other studies fail to confirm the main direction of volatility spillovers from business confidence to stock returns. This study covers a period that is ignored by previous studies and includes important economic events. In addition, considering that these economic events derive strong volatility moments, a new methodology is adopted in this field of research that measures the transmission of volatility with higher accuracy.

Determinants and spatial spillover of inter-provincial carbon leakage in China: The perspective of economic cycles

Measuring and analysing carbon leakage are the foundation for improving environmental responsibility. Based on the origin–destination approach and spatial spillover analysis, this study explores factors of China's inter-provincial carbon leakage. A multiregional input–output model was used to obtain the carbon footprint of consumption, and the factors of carbon leakage were assessed. The results revealed that the economic development and environmental regulations of the origin and destination have opposite effects on carbon leakage. Accordingly, provinces with high-energy intensity and abundant energy resources are mainly net-exported carbon, whereas provinces with underdeveloped secondary industries are mainly net-imported carbon. Notably, a positive spillover effect of energy intensity exists at the origin, and a negative one occurs at the destination. Moreover, a positive spillover affects the origin's energy output, and the surrounding areas' energy endowment can create favourable conditions for carbon leakage at the origin. Finally, corresponding policy suggestions are presented based on the above analysis.

Spatiotemporal Hybrid Air Pollution Early Warning System of Urban Agglomeration Based on Adaptive Feature Extraction and Hesitant Fuzzy Cognitive Maps

Long-term exposure to air pollution will pose a serious threat to human health. Accurate prediction can help people reduce exposure risks and promote environmental pollution control. However, most previous studies have ignored the spatial spillover of air pollution, i.e., that the current region’s air quality is also correlated with that of geographically adjacent areas. Therefore, this paper proposes an innovative spatiotemporal hybrid early warning system based on adaptive feature extraction and improved fuzzy cognition maps. Firstly, a spatial spillover analysis model based on the Moran index and local gravitational clustering was proposed to capture the diffusion and concentration characteristics of air pollution between regions. Then, an adaptive feature extraction model based on an optimized Hampel filter was put forward to process and correct the outliers in the original series. Finally, a hesitant fuzzy information optimized fuzzy cognitive maps model was proposed to forecast the air quality of urban agglomeration. The experimental results show that the air quality forecasting accuracy of urban agglomerations can be significantly improved when the geographical conditions and other interactions among cities are comprehensively considered, and the proposed model outperformed other benchmarks and can be used as a powerful analytical tool during urban agglomeration air quality management.

Spatiotemporal influencing factors of energy efficiency in 43 european countries: A spatial econometric analysis

The increase in consumption and the increase in the use of resources linked to increasing human activity puts both energy security and sustainability at risk, which has led to a global restructuring of the policy agenda to ensure and integrate environmental well-being through channels such as energy efficiency (EE). Bearing this in mind, the objective of this research is to analyze the relationship between energy efficiency, renewable energy and financial development? For this reason, an analysis is conducted, which includes energy intensity measured by the Gross Domestic Product (GDP) per unit of energy use as a measure of efficiency for 43 European countries (period 1990–2019). The objective is to observewhether the use of renewable energy and the investments being made are driving economies towards higher EE and sustainable economic growth. The present study leverages on spatial econometrics models, which allow for the analysis of spillovers between economies. The results obtained allow us to observe the existence of spatial autocorrelation of EE between countries in Europe. Secondly, it is observed that the use of renewable energies promotes EE in neighbouring economies, as well as in the return effect. On the other hand, financial development shows that only the institutional component favours EE by generating a return effect on the economy itself, while the stock market component deteriorates the EE of neighbouring economies and on the same economy. Therefore, the analyzed data shows that the use of renewable energies promotes the improvement of EE and that being close to countries that replace the use of traditional energies with alternative sources has a positive effect on national EE. These mechanisms would allow policy makers to develop mechanisms for greener and more sustainable development, while encouraging efficient energy use.

Spillover analysis across FinTech, ESG, and renewable energy indices before and during the Russia–Ukraine war: International evidence

AbstractThis study is epicentral to analyze the impact of the Russia–Ukraine war on the financial markets, specifically focusing on the connectedness and spillover dynamics of FinTech, Environmental, Social, and Governance (ESG), renewable energy, gold, and Morgan Stanley Capital International (MSCI) indices in developed and emerging countries. Data are collected from Thomson Reuters, ranging from May 8, 2020, to May 11, 2022, and a time‐varying parameter vector autoregression (TVP‐VAR) and the dynamic conditional correlation (DCC) generalized autoregressive conditional heteroskedasticity (GARCH) t‐Copula (DCC‐GARCH t‐Copula) are used to analyze the data. The results show that FinTech, ESG, and MSCI are net transmitters in developed countries, whereas gold and renewable energy are net receivers pre‐ and during war periods. ESG and MSCI are net transmitters in emerging countries, while FinTech, renewable energy, and gold become net receivers in both periods. The hedging ratio sheds light on the costs and weights of efficient pair investments that might change in the context of each region and under the combined scenario. The study has important implications for merchant bankers, policymakers, investors, hedgers, and risk managers.