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The presence of economic power of BRICS nations could be felt from the late of nineteenth and beginning of twentieth century and during this period inflow of FDI also began to go up and spread across all the sectors. FDI has not only looked to capture the huge market of these economies, but while doing so, it has helped these nations in their economics progress. Our main contribution in this paper consists of analyzing both short-run and long-run interactions between status of knowledge and FDI in the form of inflow of FDI and proportion of GDP used for R&D activities accounting for possible development of knowledge in BRICS nations. For this purpose, our work is based on a sample of these five nations during the period 2006–2017. By the help of panel data analysis and having performed all the necessary tests, we have introduced both dynamic OLS and fully modified OLS to get the efficient long-run impact of FDI on knowledge. Our empirical results support long-run and short-run causality running from FDI to knowledge in all BRICS nations. Our policy recommendation includes encouragement of more FDI in development of knowledge-related activities as well as increase in proportion of GDP spent on R&D in BRICS nations.

This paper aims to investigate feedback trading and autocorrelation behavior in the cryptocurrency market.

It uses the GJR-GARCH model to investigate feedback trading in the cryptocurrency market.

The findings show a negative relationship between trading volume and autocorrelation in the cryptocurrency market. The GJR-GARCH model shows that only the USD Coin and Binance USD show an asymmetric effect or leverage effect. Interestingly, other cryptocurrencies such as Ethereum, Binance Coin, Ripple, Solana, Cardano and Bitcoin Cash show the opposite behavior of the leverage effect. The findings of the GJR-GARCH model also show positive feedback trading for USD Coin, Binance USD, Ripple, Solana and Bitcoin Cash and negative feedback trading for Ethereum and Cardano only.

This paper contributes to the literature by extending Sentana and Wadhwani (1992) to explore the presence of feedback trading in the cryptocurrency market using a sample of the most active cryptocurrencies other than Bitcoin, namely, Ethereum, USD coin, Binance Coin, Binance USD, Ripple, Cardano, Solana and Bitcoin Cash.

In spite of the certain risk imposed by financial stress on the real economy, the relationship between financial stress and economic activity is complicated and underresearched, meaning that important gaps still remain in the authors’ understanding of this critical relationship. Therefore, the current study aims to answer the significant question regarding whether a stressful financial sector has predictive power on the real sector and vice versa. Hence, the study examines the causal interrelationship between financial stress index (FSI) and economic activity in Luxembourg as a sample country.

In this study, accompanying the time domain Granger causality framework of Hacker and Hatemi-J (2012), the authors utilize the spectral causality technique of Breitung and Candelon (2006), which is based on the study of Geweke (1982) and Hosoya (1991). This method enables the researcher to measure the degree of a particular variation in time series. Moreover, it allows considering the nonlinearities and causality cycles. The authors further apply the recent method of Farné and Montanari (2018) that is a bootstrap framework on Granger-causality spectra, which allows for disambiguation in causalities.

The time-domain approach finds evidence of bidirectional causation between the variables. However, the spectral causality results indicate the causal linkages between the series are only valid under the medium-run frequency. This study’s findings emphasize covering the frequency causality to deliver a more comprehensive picture of the interrelationship between the variables.

There are many studies in this area that examine the nexus between financial stress and economic activity. However, the authors believe this paper is the first study in the context of Luxemburg. The authors focus on this country since its financial sector is designated as the most important pillar for the economy. Thus, a careful and reliable examination of the relationship between the financial sector and economic activity is likely to be of considerable interest to policymakers and researchers in this field.

The purpose of the paper is to model the modern global practice of social management of human capital – at the state and corporate levels – to determine the perspectives of its optimization and to develop the basic principles of a new methodological approach to social management of human capital, which is preferable in the conditions of social market economy.

The author uses mathematical tools, including correlation and regression analysis. These are applied to determine the influence of each of the 12 indicators for the labor market that are presented as part of The World Economic Forum's (WEF’s) ”The Global Competitiveness Report 2019” on The United Nations Development Programme's (UNDP) Human Development Index. The research objects are countries from each of the four categories of nations, as distinguished by UNDP, in the Human Development Index. By unifying the 2019 data from UNDP and WEF, a data set is formed.

It is substantiated that in modern economic practice, it is impossible to achieve the “ideal” conditions necessary for applying existing methodological approaches to the social management of human capital, which reduces how effectively current approaches function. Foundation on the existing methods leads to uncertainty as to management of human capital, which is social by 95.14% in 2019. Though the achieved value of the social management of human capital is close to being optimal, it is still not enough to achieve a high level of human development, which was 0.685 on average for the global economy in 2019 and is likely to increase by 31.43% until 2025, for acknowledging the social market status of the modern economy.

It is proven that there is a need for a new, mixed, methodological approach to the social management of human capital, which would optimally combine the best practices of both state and corporate management. The principles for the practical implementation of such an approach are offered, and proposals are developed to substantiate the contribution of this approach to the achievement of the global goals of sustainable development.

After the COVID-19 outbreak, the Federal Reserve has undertaken several monetary policies to alleviate the pandemic consequences on the stock markets leading to a misunderstanding on the cryptocurrency market response. This paper aims to evaluate the effects of the Federal Reserve monetary policy on the Islamic and conventional cryptocurrency dynamics during the COVID-19 pandemic. We, specifically, examine the associate bubbles and feedbacks effects.

This paper developed a novel methodology that detects market bubbles using the statistical indicators defined by Psychological (PSY) tests. It also investigated the effect of the Federal Open Market Committee (FOMC) announcements on conventional and Islamic cryptocurrencies compatible with Islamic laws “Shari’ah” by using the event-driven regression.

The empirical results show that the FOMC announcements have a positive significant effect after one day of the event and a negative effect before two days of the announcement on the conventional cryptocurrency markets. However, the reaction of Islamic cryptocurrencies to these events is not significant except for Hello Gold after one day of the announcement. Besides, the Hello Gold and X8X cryptocurrencies present no bubbles during this period. However, Bitcoin and Ethereum markets have short-lived bubbles.

The main contribution of this study is the investigation of the response and vulnerability to pandemic shocks of a new category of cryptocurrencies backed by tangible assets. This work has practical implications as it provides new insights into trading opportunities and market reactions.

To our knowledge, this work is the first study that compares the response of Islamic and conventional cryptocurrency markets to FOMC announcements during the COVID-19 pandemic and examines the presence of bubbles in these markets. Besides, the originality of this work is derived from the novelty of the data employed and the method used (PSY tests) in this study.

The purpose of the research is to determine the social consequences of economic globalization based on experience of developed and developing countries and to determine the perspectives of optimization of this process through regulation.

The research method is correlation analysis, for it allows determining dependencies between the indicators without requirements to their close mutual dependence. The research objects are top ten developed and top ten developing countries as to the KOF globalization index in 2019.

It is determined that, contrary to high economic risks, social risks of globalization are very low. Instead of this, in the course of globalization the social advantages increase – they are expressed in the form of harmonization of the labor market, development of digital society and increase of population's quality of life – in particular, provision of balance of the global society by leveling the social disproportions between developed and developing countries. It is substantiated that consequences that stimulate the increase of population's quality of life in developing countries are more expressed than in developed countries. This means that developing countries, which are traditionally more inclined to limiting the influence of globalization on them due to economic reasons, have to reconsider their foreign economic policy and include the measures on stimulation of globalization in the interests of social development. Other than that, the differences in consequences for developed and developing countries are minimal. There is no imbalance of consequences that is peculiar for the economic sphere, in which the main advantages are obtained by developed countries, and developing countries bear most of the costs. From the social point of view, globalization could be characterized as a positive phenomenon of modern times.

The offered authors' recommendations will allow optimizing the influence of globalization on the social environment in developed and developing countries and ensuring usage of economic globalization as a mechanism of implementation of the global goals in the sphere of sustainable development.

The purpose of this paper is to estimate the wage difference between overeducated and adequately educated workers in a sample of semi-skilled and low-skill occupations in Iran’s labor market. The objective is to see if overeducated employees in these occupations enjoy higher wages in comparison to their adequately educated co-workers.

The authors use the propensity score matching (PSM) model to estimate the wage difference between overeducated and adequately educated workers in a sample of semi-skilled and low-skill occupations in Iran’s labor market. The PSM method allows the authors to prevent selection bias by comparing each group of overeducated workers with a matched group of adequately educated workers with similar socio-economic characteristics.

The results show that in Iran’s labor market, the overeducated workers enjoy a wage premium in the range of 10-25 percent for their excess education when they have to work in semi- or low-skill occupations. While this relative advantage has gradually declined for private sector employees over the period 2001-2013, it has remained stable for public sector jobs. The result is attributable to the fact that salary and benefits for public sector employees are directly linked to education attainment and their work experience. The findings show that the relative wage advantage of overeducation is larger for the younger employees with ten or fewer years of experience who have more education than older workers. Overall these findings offer an explanation for the strong desire of Iranian youth for university education. If a university graduate finds a job that matches her/his specialization she/he will enjoy a higher salary than a high school graduate. If she/he has to accept a semi-skilled or low-skill job for which she/he is overeducated, she/he still enjoys a wage premium over her/his co-workers who are not overeducated.

The analysis makes three unique contributions: first, the authors use a unique and detailed micro-data for an economy (Iran) in which the public sector dominates the private sector. The authors investigate the hypothesis for private and public sectors separately. Second, the authors divide the sample of workers into market newcomers and experienced workers. The authors analyze the impact of overeducations on each group separately. Third, the authors use the treatment effect of being overeducated on the individual’s monthly wage by the PSM. The advantage of the PSM method is that it eliminates the selection bias in the wage effect of overeducation, whereas the traditional regression-based techniques may result in this type of bias.

The purpose of this paper is to extend the literature on the spillovers across economic policy uncertainty (EPU) and cryptocurrency uncertainty indices.

This paper uses cross-country economic policy uncertainty indices and the novel data measuring the cryptocurrency price uncertainties over the period 2013–2021 to construct a sample of 946 observations and applies the time-varying parameter vector autoregression (TVP-VAR) model to do an empirical study.

The findings suggest that there are cross-country spillovers of economic policy uncertainty. In addition, the total uncertainty spillover between economic policies and cryptocurrency peaked in 2015 before gradually decreasing in the following periods. Concomitantly, the cryptocurrency uncertainty has acted as the “receiver.” More importantly, the authors found the predictive power of economic policy uncertainty to predict the cryptocurrency uncertainty index. This paper’s results hold robust when using alternative measurement of cryptocurrency policy uncertainty.

This study is the first research that deeply investigates the association between two uncertainty indicators, namely economic policy uncertainty and the cryptocurrency uncertainty index. We provide fresh evidence about the dynamic connectedness between country-level economic policy uncertainty and the cryptocurrency index. Our work contributes a new channel driving the variants of uncertainties in the cryptocurrency market.

The purpose of this paper is to evaluate the importance of financial liquidity and solvency on US commercial and domestic banks’ cost efficiency while accounting for internal and external factors.

The Stochastic Frontier Analysis and Data Envelopment Analysis estimators are used to estimate the cost efficiency of 11,044  US commercial and domestic banks from 2005 to 2017. Using Tobit regression model, the importance of financial liquidity and solvency on cost efficiency is examined.

The results provide evidence that the financial liquidity and solvency negatively impact the cost efficiency of US commercial and domestic banks. Overall, US commercial and domestic banks were inefficient during the financial crisis in comparison to the tranquil period. The importance of financial solvency on the cost efficiency was not statistically significant, while the financial liquidity negatively collapsed because of contagion. Finally, the results provide evidence that the amount of total assets matters in the improvement of the cost efficiency.

This paper estimates and identifies the 2007-2009 financial crisis with liquidity, solvency or both financial factors.

The purpose of the paper is to model and develop recommendations for regulating the development of social market economy under the influence of noneconomic factors.

The authors determine the existing examples of social market economies, in which quality of life clearly correlates with economic growth – and the research objects are thus determined. Then, the list of noneconomic factors, which could be quantitatively characterized based on the official statistics, is formed. The econometric model of dependence of the rate of economic growth of the selected noneconomic factors is created, and it is determined at which combination of these factors' influence it is possible to reach the target rate of economic growth of social market economy. Data are processed automatically by compiling the descriptive statistics and conducting regression analysis within the method of imitation modeling and multiparametric nonlinear optimization.

It is shown that, unlike the classical market economy (pure capitalism), in which economic factors dominate, social market economy (mixture of capitalism and socialism) is also influenced by noneconomic factors. This changes the view on economic growth as one of the most significant processes in the economic practice and one of the key research objects in economics. It is substantiated that there's a necessity not for micro- (as in the classical market economy) but for macroeconomic view on economic growth through the prism of factors that are external to entrepreneurship.

The results of imitation modeling allowed reducing the uncertainty and reflecting the specifics of economic growth of social market economy. The compiled model of multiple linear regression allowed narrowing down the circle and outlining four main noneconomic factors of economic growth of social market economy. The authors' recommendations for regulation of these factors are offered, and a mechanism of regulation of development of social market economy based on noneconomic factors management is offered.