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The study constructs a composite indicator to rank macroeconomic performance of countries and a separate composite indicator to rank countries by inequality using the TOPSIS methodology of Multiple Criteria Decision-Making Analysis. The intuitive idea of TOPSIS is to formulate an ideal solution with respect to each individual policy variable; the relative rank of any country is then determined, using a suitable distance metric, such that the best performer simultaneously has the shortest distance from the ideal solution and the farthest distance from the non-ideal. It uses the composite indicator based rankings together with the KOF Globalization Index and sub-indices based rankings to examine the overall relationship between globalization and macroeconomic performance of countries and reduction in inequality; the impacts of trade and financial globalization for 1990–2018 across countries and groups of the globe. It shows that though highly correlated with growth, globalization may not necessarily lead to an improvement in overall macroeconomic performances of countries when one also takes into account unemployment and inflation. Economic globalization is seen here to mostly coincide with rise in income inequality. Observations also support the fact that countries, even if they are not highly integrated may reap sufficient benefits of globalization for macroeconomic performance and inequality diminution given supportive policies.

The purpose of the chapter is to study regional (in the global scale) peculiarities of the 2008 global economic crisis and to determine socio-economic systems that are in the phase of crisis (long recession).

The research objects are regional associations of countries according to the classification of the participants of the global economic system of the International Monetary Fund. The research is conducted by aggregation (the method of finding direct average) of the annual growth rate of GDP in constant prices by the selected categories of regional socio-economic systems. Timeframe of the research covers 2006–2018 and the forecast period of 2019–2022. The methodological tools of the research include the methods of horizontal and trend analysis.

It is determined that most developing countries – Commonwealth of Independent States, emerging and developing Asia and Latin America, and the Caribbean – are in a long recession and will overcome the consequences of the crisis only in the mid-term. Developing countries from the categories the Middle East, North Africa, Afghanistan, Pakistan, and sub-Saharan Africa faced a deep and long second wave of the crisis and will have a long recession until 2022. They will overcome it only in the long-term. The only category of developing countries – emerging and developing Europe – despite the general downward trend of GDP in constant prices – shows sustainable development and has already overcome the crisis.

The influence of the global economic crisis on the global economic system through the prism of the regional aspect is specified. It is shown that at present (2018) most regions of the global economic system are covered with crisis and will have long recession until 2022. Developing countries have faced the highest damage from the 2008 crisis, and most of them have the second or even the third wave of crisis.

The present study aims to determine the existence of simultaneous relationship between economic growth, income inequality, fiscal policy, and total trade of the 13 emerging market economies as a group for the period 1980–2010. After establishing the existence of simultaneity between the above relationships, a simultaneous panel model has been formulated and estimated incorporating the nonlinearity among the variables as suggested by the existing literature. An inverted U-shape relationship is evident between (1) economic growth, income inequality, and total trade in economic growth equation, (2) income inequality, economic growth, and per capita income in income inequality equation, and (3) total trade and economic growth in total trade equation. Thus, the existence of a two-way nonlinear relationship is highlighted between economic growth, income inequality, and total trade. Apart from these nonlinear relationships, positive and significant effect of (1) gross capital formation, inflation, population growth, human capital, fiscal policy, monetary policy, and domestic credit to private sector on economic growth; (2) civil liabilities on income inequality; (3) gross capital formation and inflation on total trade; (4) total trade, population growth of those aged 65 years and above, political system on fiscal policy is highlighted. Also, negative and significant effect of (1) fiscal policy on income inequality and (2) income inequality on fiscal policy is revealed.

We compare the aggregated international assets and liabilities of banks that report to the Bank for International Settlements (BIS) to establish their gross and net international exposures during recent episodes of financial crisis. Initially we consider these positions worldwide and then focus on the cross-border flows within Europe, considered in terms of core and peripheral countries. These gross and net asset–liability positions are both time-varying and respond to crisis periods, through better matching of international assets and liabilities as well as the realignment of asset positions to reduce balance sheet risks. These conclusions are consistent with other studies that utilise international banking flow data, while the European experience highlights the diversity of international position taking. This is due to the complexity of managing risks within the eurozone (EZ) and peripheral countries, and those emerging European countries that retain legacy currencies.

The purpose of the chapter is to focus on the global industrial robotics market and trends of its development. In the framework of this chapter, the authors made the forecast of industrial robots' market future values in this chapter with the linear regression method and an econometric model. This analysis has provided a conclusive answer to the question about the prospects of the industrial robotics market and the leading countries. The completed forecast showed that the global robotics market will continue to grow, thanks to the wider adoption of industrial robots, which will be used in new industries, the development of contactless user interfaces, which, among other things, will be implemented in the automotive applications, the focus on predictive maintenance and remote monitoring of equipment, as well as the transition of a large number of enterprises to digital management and full automation of existing equipment to improve the quality and productivity of processes. The authors show that in 2020 the global robotics market volume decreased due to the COVID-19 pandemic and major shift in production value chains, but in 2021 the indicator will grow again, but not so rapidly, at a more moderate pace. By 2025, the global industrial robotics market may exceed $61.4 billion, with a growth rate of 8.5%.

The importance of sovereign bond as a source of financing revenue deficit, benchmarking for corporate bonds and debt management in Africa, calls for continual monitoring of its volatility dynamics. This study evaluates the nature of sovereign bond volatility interaction between African countries using bivariate BEKK-GARCH (1, 1) model. Based on a sample of eight African countries, the results show evidence of unidirectional volatility spillover from Morocco sovereign bond to Egypt sovereign bond. Next, the results show absence of volatility interaction between Ghana and Nigeria sovereign bonds. The results further show the existence of bidirectional volatility transmission between Uganda and Kenya. Finally, the results indicate evidence of bidirectional volatility interaction between Botswana and South Africa. Overall, the results show existence of full interaction between Uganda–Kenya and Botswana–South Africa sovereign bond returns, partial interaction between Egypt and Morocco sovereign bond returns and no interaction between Ghana and Nigeria sovereign bonds markets. Thus, these results provide valuable implications for sovereign and corporate credit risk management, as well as strategy for monitoring and minimising negative effect of sovereign bond volatility spillover in Africa.

Both investors and the stock markets are believed to behave in a perfectly rational manner, where investors focus on utility maximization and are not subjected to cognitive biases or any information processing errors. However, it has been discovered that the sentiment of the social mood has a significant impact on the stock market. This study aims to analyze how did the protest event of Tesla happened in April 2021 have a significant effect on the company's stock performance as well as its competitors, Nio, under the competitive effect.

The research is based on time series data collected from Tesla and Nio by employing 10 days, 15 days and 20 days anticipation and adjustment period for the event study. This study employed a text sentiment analysis to identify the polarity of the sentiment of the protest event using the Microsoft Azure machine learning tool which utilizes MPQA subjective lexicon.

The findings provide further evidence to show that a company-specific negative event has deteriorating effects on its stock performance, while having an opposite effect on its competitors.

The paper argues that negative sentiments through social media word of mouth (SWOM) affect the stock market not just in the short run but potentially in the longer run. Such negative sentiments might create a snowball effect which causes the market to further scrutinize a company's operations and possibly lose confidence in the company.

This study explores how the Tesla's protest event at Shanghai Auto Show 2021 has a significant impact on Tesla's stock performance and prolonged negative impact although Tesla implemented immediate remedial actions. The remedial actions were not accepted positively and induced a wave of negative news which had a more persistent effect.

The purpose of this paper is to analyse the role that different financial sources and financial specialization have on private research and development (R&D) activity in OECD countries.

The authors developed several panel regressions choosing as a final model a two-way random effects regression to understand which funding sources are related to the R&D expenditure, and how financial specialization has links to the private portion of R&D aggregated expenditure. The authors include data from the years 2000 to 2016 for OECD countries.

The results reinforce the critical role that stock markets have in enhancing private R&D and that bond markets have an inverse relationship with private R&D national expenditures. The authors do not find evidence of a link between bank sources and private R&D. Specialized financial systems (banking or market) support innovation in a better way than a mixed arrangement of those two systems.

The findings of this study have considerable policy implications. Policymakers need to be aware of these results, given that some variables related to financial markets, seems to boost the inputs for R&D. In the long term, this could be a signal that national and regional systems of innovation need a broad view of the factors hampering scientific activity, and also a signal that there are other ways to impact the results of the complex innovation activity through the development of stronger financial systems backing up national systems of innovation.

The authors found that the long discussion about the financial system that a country has to choose to enhance growth with R&D&I may have been misleading the public policy. The findings show that rather than a bank or a stock market financial system, economies looking to boost R&D&I, must specialize in one of the two systems, deepen these and generate the appropriate policies to promote science, technology and innovation using those financial markets.

Injections of foreign direct investment (FDI) are often followed by injections of foreign culture which may not be well received among the local population. If this is the case, culture may impede any positive externalities from FDI. On the other hand, if the people of the host country embrace injections of FDI, this may lead to boosts in not only short-run factors of production but also longer-term technological spillovers. We measure what role cultural make-up of a country plays on the effect of FDI on growth in GDP.

Using values system data from the World Values Survey (WVS), and socioeconomic data from the World Bank, we estimate and plot the marginal effect of FDI on growth as a function of a country's values system for a panel of 73 countries over a span of three decades.

We find that the marginal effect of FDI on growth in GDP differs across varying degrees of cultural values, even after adjusting for level of development. In other words, our analysis indicates that a country's cultural norms do indeed affect foreign investment's impact on economic growth.

To date there is no research that systematically assesses the effect that cultural make-up has on the marginal effect of FDI on growth. We go beyond the use of isolated cultural variables by using data on cultural dimensions that account for most of the observed cultural differences between countries. We believe our findings will work as a launchpad for more novel ways to capture country heterogeneity in growth research.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2019-0549.

The main purpose of this paper is to explore size of the shadow economy of 31 European Countries in 2014 and size of the shadow economy of 28 European Union countries over 2003-2014 (in per cent of official GDP). An additional objective is to identify tax evasion, as the problem of all the EU countries, answering the questions how better combat the tax fraud.

Estimates of the shadow economy for all 28 European Union countries and other three countries from Europe, i.e. Norway, Switzerland and Turkey – MIMIC method was applied.

The average size of the shadow economy in 28 EU countries was 22.6 per cent in 2003 and decreased to 18.6 per cent (of official GDP) in 2014. We also consider the most important driving forces of the shadow economy. The biggest ones are with 14.6 per cent unemployment and self-employment, followed by tax morale with 14.5 per cent and GDP growth with 14.3 per cent. The proportion of tax evasion (accounting for indirect taxation and self-employment activities) was on average 4.2 per cent (of official GDP) in Poland, 1.9 per cent in Germany and 2.9 per cent in the Czech Republic.

The MIMIC statistics do not address a large part of the wholly illegal economy (of typically criminal nature) and, accordingly, it is not an absolute magnitude of the whole unofficial economy. However, it does not seem that other, alternative, methods of measuring the unofficial economy are better in individual terms.

Current statistical research should lead to practical acceptance in the framework of need for developing better organizational & legal ways for multi-level governance within the European Union, leading to effective methods of counteracting – in particular intra-Union fraud. In addition, the presentation of a review of typology of the main theories and studies regarding the unofficial economy aspects relating to tax evasion constitutes a practical review of the pursued research areas.

Safeguarding the national economy as a whole, by seeking ways of reducing the scope of shadow economy.

Both regarding presentation of the latest shadow economy estimates and typology of its main studies and theories.