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The COVID-19 pandemic is known to have affected the logistics and supply chains; however, there is no adequate empirical evidence to prove in which way it has affected the relationship between the stocks related to this field with the corresponding cryptocurrencies. This paper aims to test the dynamic relationship of cryptocurrencies with supply chain and logistics stocks.

In this paper, the author tests the causal and long-run relationship between logistics and supply chain stocks with the corresponding cryptocurrencies related to these fields, or those that are known to exhibit characteristics that can be utilized by these fields, testing also whether the COVID-19 pandemic affected this relationship. To do so, the author performs the variable-lag causality to test the causal relationship, and examines if this relationship changed due to COVID-19. The author then implements the multifractal detrended cross-correlation analysis to investigate the characteristics of a possible long-run relationship, testing also whether they changed due to COVID-19.

The results indicate that there is a positive long-run relationship between each logistics and supply chain stocks and the corresponding cryptocurrencies, before and also during COVID-19, but during COVID-19 this relationship becomes weaker, in most cases. Moreover, before COVID-19, the majority of the cases indicate a causal direction from cryptocurrencies to the stocks, while during COVID-19, the causal relationships decrease in multitude, and most cases unveil a causal direction from the stocks to cryptocurrencies.

The causal pattern changed during COVID-19, and the long-run relationship became weaker, showing a change in the dynamics in the relationship between logistics and supply chain stocks with cryptocurrencies.

By combining econometrics and multifractal methods, utilizing a financial framework, this paper will examine with objectivity the economic, financial and social impact of coronavirus disease 2019 (COVID-19) on society.

Through Granger causality, the authors test the effect of the COVID-19 pandemic on excessive gaming and gambling activities, and through econometrics and multifractal methods, they combine the results to analyze a possible long-run relationship.

The COVID-19 confirmed cases Granger cause all examined stocks. Based on the co-integration technique, and the multifractal cross-correlation analysis, a long-run relationship exists between all examined stocks and COVID-19.

This is an empirical examination of a very important subject in the field of economics, namely, the consequences of the COVID-19-related events on the behavior of global citizens. It proposes a different and more objective approach (than the interviews and questionnaires) in the examination of this specific subject, through a financial framework, depicting the stock performance of the gaming and online gambling-related companies, and reflecting on the activity of these companies. It combines two different approaches from two different disciplines, namely econometrics and multifractal analysis, to test and describe the causal and the long-run relationship between the phenomena examined, combining the results to an overall and multidimensional view of this occurrence.

This research paper uses a novel methodological approach to investigate the spillover effects among the key sectors of the US economy.

The paper links the US sectors via a node theoretic scheme based on a general equilibrium framework, whereas it estimates the general equilibrium equation as a Global Vector Autoregressive process, taking into consideration the potential existence of dominant units.

Based on our findings, the dominant sector in the US economy, for the period 1992–2015, is the sector of information technology, finance and communications, a fact that gives credence to the view that the US economy is a service-driven economy. In addition, the US economy seems to benefit by the increased labour mobility across knowledge-intensive sectors, thus avoiding the ‘employment trap’ which in turn enabled the US economy to overcome the financial crisis of 2007.

Firstly, the paper models by means of a network approach which is based on a general equilibrium framework, the linkages between the US sectors while treating the sector of information, technology, communications and finance as dominant, as dictated by its degree of centrality in the network structure. Secondly, the paper offers a robustness analysis regarding both the existence and the identification of dominant sectors (nodes) in the US economy. Thirdly, the paper studies a wide period, namely 1992–2015, fully capturing the recent global recession, while acknowledging the impact of the global crisis through the introduction of the relevant exogenous dummy variables; Lastly and most importantly, it is the first study to apply the GVAR approach in a network general equilibrium framework at the sectoral level.