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This paper examines dynamic return spillovers and connectedness networks among international stock exchange markets. The authors account for asymmetry by distinguishing between positive and negative returns.

This paper employs the spillover index of Diebold and Yilmaz (2012) to measure the volatility spillover index for total, positive and negative volatility.

The results show time-varying and asymmetric volatility spillovers among the stock markets under investigation. During the coronavirus disease 2019 (COVID-19) pandemic, bad volatility spillovers are more pronounced and dominated over good volatility spillovers, indicating contagion effects.

The presence of confirmed COVID-19 cases positively (negatively) affects the good and bad spillovers under low and intermediate (upper) quantiles. Both types of spillovers at various quantiles agree also influenced by the number of COVID-19 deaths.

The authors test the granularity hypothesis to international inflation spillovers using annual exports and inflation data for 138 countries from 1991 to 2020. This study aims to discuss the aforementioned objective.

First, the authors quantify the power law for the right tail of the export volumes distribution and discuss its implications. Then, the authors compute the granular residual, a measure of shocks to the largest countries.

The authors find export volumes across countries are not Gaussian-distributed but follow a power law. This finding means the largest countries disproportionately impact world inflation. In addition, the authors find that countries with higher relative weight in international trade determine a portion of international spillovers greater than their trade share. Moreover, eight big grains are responsible for the bulk of inflation spillovers.

The policy implication is that other countries' central banks should closely monitor the eight big grains when conducting their domestic monetary policy.

This is the first study spotting the problem of granular inflation spillovers.

This study is the first that aims to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

Multiple spatial weight matrices can capture the contiguity of spatial units from various dimensions, which could be exploited to improve the precision of inference as well as prediction accuracy. To the best of the authors’ knowledge, this is the first study to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

With network structure analysis, this study finds that they contain different information content from the perspective of graphical display, node strength and correlation. Developed and emerging countries all play major roles in trade connection, while only developed countries play major roles in financial linkage. Second, by applying the multidimensional SAR model, only the spatial autocorrelation coefficients for trade and financial linkages are significant during the full sample period, which is in sharp contrast to published studies using the SAR model with a single matrix. Third, the spillover channels that play major roles in various periods are different. Only trade channel plays a role during crisis periods and it is the most important. Fourth, the spatial correlation among countries greatly amplifies the shock’s impacts on one market. And spatial effect for developed countries is larger than those for emerging countries, while the mean spatial effect of a unit shock in the USA on emerging countries is slightly greater than that on developed countries.

Multiple spatial weight matrices can capture the contiguity of spatial units from various dimensions, which could be exploited to improve the precision of inference as well as prediction accuracy. To the best of the authors’ knowledge, this is the first study to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

This paper explains the mechanisms underlying the generation of two-way knowledge spillovers through the interaction of subsidiaries with differentiated local responsibilities and domestic firms.

The study is based on firm-level panel data from a census of Colombian manufacturing firms for the period 2003–2012. The estimation procedure involves two stages. In the first one, total factor productivity (TFP) of foreign and domestic firms is estimated. In a second step, we estimate conventional spillovers (from foreign-owned to local firms) and reverse spillovers (from local to foreign-owned firms) separately, using a random effect approach.

This study’s findings reveal that only locally creative subsidiaries enjoy positive and significant two-way knowledge spillover effects. The connectivity of subsidiaries to local and international networks is reinforced by reciprocal relationships among actors that enhance bidirectional knowledge flows, these being favored by the dynamics of clustering effects.

The paper contributes with new empirical evidence about the mechanism explaining how the technological heterogeneity of subsidiaries plays a determinant role in the generation of both knowledge flows from foreign to domestic firms and to the reverse, all integrated into the same framework.

This paper aims to provide new perspectives on the integration of East Asian stock markets and the dynamic volatility transmission to the Bitcoin market utilising daily data from 2014 to 2020.

The authors undertake comprehensive analyses of the dependency dynamics, systemic risk and volatility spillover between major East Asian stock and Bitcoin markets. The authors employ a vine-copula-CoVaR framework and a VAR-BEKK-GARCH method with a Wald test.

(a) With exception of KS11 and N225; HSI and SSE; HSI and KS11, which have moderate dependence, dependencies among other markets are low. In terms of tail risk, the upper tail risk is more significant in capturing strong common variation. (b) Two-way and asymmetric risk spillover effects exist in all markets. The Hong Kong and Japanese stock markets have significant risk spillovers to other markets, and quite notably, the Chinese stock market is the largest recipient of systemic risk. However, the authors observe a more significant risk spillover from the Chinese stock market to the Bitcoin market. (c) The VAR-BEKK-GARCH results confirm that the Korean market is a significant emitter of volatility spillovers. The Bitcoin market does provide diversification benefits. Interestingly, the Chinese stock market has an intriguing relationship with Bitcoin. (d) An increase in spillovers in East Asia boosts spillovers to Bitcoin, but there is no intuitive effect of Bitcoin spillovers on East Asian spillovers.

For the first time, the authors examine the dynamic linkage between Bitcoin and the major East Asian stock markets.

This study aims to elucidate the volatility spillovers among commodities, equities and socially responsible investments, underpinning their dynamic correlations during the economic instability wrought by the COVID-19 pandemic and associated financial crises.

This research quantitatively analyzes volatility transmission across various financial assets from January 2005 to October 2020 by employing the Diebold and Yilmaz (2012) spillover index. The methodology incorporates a temporal examination to capture the evolution of volatility dependencies pre and post the emergence of COVID-19.

The findings indicate substantial volatility spillovers among the assets in question, aligning with the current financialisation of commodity markets and a rise in financial market integration. These spillovers also show variation over time. Notably, the interconnectedness among the assets intensifies during periods of stress. For instance, the total spillover index significantly surpassed 80% toward the end of January 2020, following the onset of the COVID-19 crisis. Furthermore, the results imply that financial markets appear to be segmented.

The findings afford investors a more comprehensive insight into both the character and scale of the interdependencies across a broad array of financial markets. Indeed, grasping the extent to which financial markets are segmented or integrated during times of stress and stability is crucial for investors. Such understanding is key to more accurately evaluating risks, diversifying investment portfolios and devising more efficient hedging strategies.

This study contributes to financial literature by offering a comprehensive investigation into the spillover effects across a diverse set of asset classes during an unprecedented global health crisis, filling a gap in existing research on market behavior against the backdrop of a pandemic-induced financial crisis.

The purpose of this work is to study the connections generated between stock market indices, representing firms whose practices focus on fighting climate change and several global risk factors in accordance with the sustainability objectives defined in the 2030 Agenda. An endogenous perspective is adopted, considering the spillovers generated within the low carbon stock market sector, as well as the latter’s exposure to exogenous shocks of an economic and financial nature.

This work uses a multivariate model of dynamic correlation (GARCH-corrected dynamic conditional correlation [cDCC]), which can accompany the correlations generated over time.

Considering five low carbon indices, representing various parts of the world, and four global macro-economic and financial variables, over a period of approximately eight years, it was possible to understand that the variables studied transmit between each other a statistically significant spillover. The period of the pandemic crisis shows a sharp increase in the information transmission process. It was also possible to conclude that some global variables are risk factors, performing the role of transmission channels for the spillover effects to low carbon indices, increasing the risk of contagion and reducing the possibilities of diversifying the investment portfolio.

Firstly, this work analyses the connection and spillover effects between low carbon indices. Secondly, considers an extended sample covering different market phases, particularly that of the pandemic crisis and the Ukrainian War, creating conditions to compare connection patterns between those indices. Thirdly, it studies the variable influence over time of global risk factors in the transmission of spillover between low carbon indices.

This article analyzes the impact of monetary policy on income inequality across 16 advanced economies. The author investigates three key points: (1) the relationship between domestic monetary policy and domestic income inequality, (2) the spillover effect of USA monetary policy (including quantitative easing) on international inequality and (3) the quantitative influence of the monetary policies of both the USA and the Eurozone on the formation of domestic income inequalities.

The author employed the Global Vector Autoregressive (GVAR) model, which uses Vector Autoregressive with Exogenous Variables (VARXs) models of each economy to build an integrated system that enables us to evaluate individual responses to global shocks.

The author's analysis reveals that (1) contractionary monetary policy exacerbates domestic inequality and (2) USA monetary policy, including quantitative easing, affects international inequality. Furthermore, the author's variance decomposition analysis highlights that USA monetary policy is especially influential on income inequality in Norway and Sweden. Additionally, the cointegrating analysis confirms that monetary policy's impact on inequality persists in the long term.

Most of the studies focused on investigating domestic economies as closed economies. However, the author's approach differs in that the author uses the GVAR, which treats all economies as open. This allows us to incorporate the world economy into the domestic dynamics and connect the economies using bilateral trade. Another advantage of the GVAR is that it captures spillover effects by modeling each economy and constructing the international economy.

This study aims at exploring the nexus between herding behavior and the spillover effect in G7 and BRICS stock markets.

The authors used the dynamic connectedness approach TVP-VAR model of Antonakakis et al. (2019) to capture the spillovers across different markets. Moreover, to explore herding behavior, the authors used a modified version of the CSAD measure of Chang et al. (2000) including extreme market movements. Finally, to study the link between these two phenomena, the authors estimated a DCC-GARCH model.

The results show that herding behavior exists in the American market and some BRICS markets. Furthermore, spillover between G7 and BRICS increases in times of crisis. Moreover, the authors find a dynamic conditional correlation between herding behavior and spillovers both in the short and long run. The authors conclude that in times of crisis, the transmission of shocks between markets is more frequent, fuelling uncertainty and pushing investors to suppress their own beliefs and follow the general market trends.

This paper uses the TVP-VAR model to explore the spillover effect and the DCC-GARCH model to explore the connectedness between herding behavior and the spillover effect in G7 and BRICS countries in both the short and long run.

Wine tourism is spreading from the “old world” wine countries to Asia. The purpose of this paper is to introduce the GLOW framework capturing the tension of homogenization and globalization of touristic experiences, the tourists' rising environmental concerns and their conflict of searching for authentic experience with new sensations.

In a mixed-method procedure, evidence describing the wine tourists’ perceptions and motivations is assessed using a quantitative survey and fitting a structural equation model using the PLS algorithm. Complementing evidence through qualitative interviews with Indian entrepreneurs on designing a glocalized experience is analyzed.

Spillover from international travel is the most relevant driver of wine tourism in India. However, types of wines and the experiences are adjusted to the local conditions. The winemakers are remarkably advanced in implementing environmentally sustainable production and avoiding over tourism which perfectly meets their clients’ expectations.

Entrepreneurial creation theory as described by Alvarez and Barney (2007) is illustrated in the Asian glocalisation context giving special attention to the entrepreneur’s individual capabilities as called by Helfat and Peteraf (2015) and Liñán et al. (2020).

Conservation of biodiversity and the aesthetics of the local landscape are essential for the vividness of the entrepreneurial ecosystem and the attractiveness for the guests.

Local adaptation of the touristic experience in terms of entertainment, indigenous cuisines and local specialty supports sustainable development of all the stakeholders.

Novelty arises from the projection of the visitors considering the wine cellar experience as an alternative to international travels in combination with analyzing how the entrepreneurs create entrepreneurial opportunities by carving out an authentic experience for their guests.