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The digital economy has become a new engine for economic development, promoting the upgrading and transformation of traditional industries as well as fostering emerging industries and forms of business. Nonetheless, how does the digital economy affect innovation? The research objective is to explore the specific impact of the digital economy on innovation output.

This paper innovatively adopts the dynamic panel data model (DPDM) to carry out an empirical study on the impact of the digital economy on innovation output, through the observation of 30 provincial-level administrative regions in China. Furthermore, the paper innovatively analyzes the impact of different dimensions of the digital economy on innovation output and the impact of the digital economy on different dimensions of innovation output.

It is found that the digital economy is conducive to boosting innovation output considering innovation continuity. Specifically, the driving impact of core industries and enterprise application of digital economy on innovation output is more prominent, but the driving impact of infrastructure and personal application on innovation output is not fully played. Meanwhile, the driving impact of the digital economy on the innovation output quality is more significant than that digital economy on the innovation output quantity.

This study employs a DPDM for the first time to investigate the specific impact of the digital economy on innovation output, and contributes to the existing literature on the digital economy and digital economy-driven innovation. The findings offer a comprehensive explanation for the impact of the digital economy on innovation output, which has reference value for the formulation of innovation policies driven by digital economy, thereby providing impetus for the sustained and stable development of China's economy.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

This paper empirically tests the impact of capital sudden stops on the economic growth using quarterly data from 49 emerging economies.

This paper applies the GMM dynamic panel estimation method.

The results show that capital sudden stops can significantly inhibit the economic growth of emerging economies. It was also found that the inhibiting effect on low-savings-rate economies is greater, but less on high-savings-rate economies. In addition, this paper examined the impact of different types of capital sudden stops on economic growth in emerging economies. The results reveal that the impact of sudden stops of direct investment is not significant.

Little existing research considers the impact of capital sudden stops through the perspective of savings rate differences. Based on our research using the GMM model, we argue that capital sudden stops will lead to a decline in investment kinetic energy in emerging economies, and therefore, a decline in economic growth. There are also few studies on the economic effects of capital sudden stops. And the time series model is generally used in a single economy. This paper, however, uses the data from 49 emerging economies and takes the panel approach to more comprehensively study the capital sudden stops of emerging economies.

This study aims to explore potential paradigm shift in how “global economies” react to adverse macroeconomic conditions from key dominant economies such as the US and the Chinese economies. This is done by examining how economic activities within key economies around the world react to, or are impacted by, modeled adverse macroeconomic condition emanating from the Chinese and the US economies.

To verify potential paradigm shift in how external macroeconomic uncertainty impacts “global” industrial productivity and overall gross domestic product (GDP) growth within selected economies, this study opts for seemingly unrelated regression (SUR) model. Adoption of this method has been influenced by the potential for correlated error terms between modeled adverse macroeconomic condition, industrial productivity and GDP growth variables being tested in a two-equation system.

Empirical results based on SUR analysis find no evidence of this potential paradigm shift within the time frame examined in the study. Estimated results suggest that notwithstanding the recent growth surge of the Chinese economy, macroeconomic happenings within the US economy still exert significantly more influence on key economies around the world. For instance, this study finds that macroeconomic uncertainty associated with the US economy significantly constrains both industrial productivity and overall GDP growth within most of the economies tested, whereas the same condition emanating from the Chinese economy seems to rather have a weak positive impact on the same macroeconomic variables.

Research results are strictly limited to the focus time frame for this study; it is likely that expanded data involving more years beyond what was analyzed in this study could yield different results.

This study is an original research based on data from a reputable US federal institution.

The purpose of this study is to assess the potential economic cost of the COVID-19 pandemic on China's macroeconomy and agri-food system and provide policy recommendations to stimulate economic growth and agri-food system development.

An economy-wide multisector multiplier model built on China's most recent social accounting matrix (SAM) for 2017 with 149 economic sectors is used to assess the impact of COVID-19 on China's macroeconomy and agri-food system. SAM multiplier analysis focuses on supply chain linkages and captures the complexity of an interconnected economy.

The paper finds that both the macroeconomy and agri-food systems are hit significantly by COVID-19. There are three main findings. First, affected by COVID-19, GDP decreased by 6.8% in the first quarter of 2020 compared with that in 2019, while the economic loss of the agri-food system is equivalent to 7% of its value added (about RMB 0.26 trillion). More than 46m agri-food system workers (about 27% of total employment) lost their jobs to COVID-19 in the lockdown phase. The COVID-19 affects the employment of unskilled labor more than that of skilled labor. Second, when the economy starts to recover during the second and third quarters, the growth rate in the value added of the agri-food system turns positive but still modest. Many jobs resume during the period, but the level of agri-food system employment continues to be lower than the base. The agri-food system employment recovery is slower than that of other sectors largely due to the sluggish recovery of restaurants. Agri-food system employment drops by 8.6m, which accounts for about 33% of the total jobs lost. Third, although the domestic economy is expected to be normal in the fourth quarter, external demand still faces uncertainties due to the global pandemic. The agri-food system is projected to grow by 1.1% annually in 2020 with resuming export demand, while only by 0.4% without resuming export demand. These rates are much lower than an annual growth rate of 4.3% for the agri-food system in 2019. The results also show that, without resuming export demand, China's total economy will grow less than 1% in 2020, while, with export demand resumed, the growth rate rises to 1.7%. These rates are much lower than an annual GDP growth rate of 6.1% in 2019.

The results show that continuously reducing economic dependency on exports and stimulating domestic demand are key areas that require policy support. The agri-food system can play an important role in supporting broad economic growth and job creation as SMEs are major part of the AFS. Job creation requires policies to promote innovation by entrepreneurs who run numerous SMEs in China.

This paper represents the first systematic study assessing the impact of COVID-19 on China's agri-food system in terms of value added and employment. The assessment considers three phases of lockdown, recovery and normal phases in order to capture the full potential cost of COVID-19.

The purpose of this paper is to develop a dynamic computable general equilibrium (DCGE) model to analyze economy‐wide impacts of different types of public spending in China. A particular focus is placed on their impacts on food economy.

In this paper, DCGE model is developed to analyze economy‐wide impacts of different types of public spending in China. The effects of increased agricultural subsidies, agricultural R&D, and irrigation are simulated by using China DCGE model.

The results show that public spending has significant impact on food production, price, and trade. The increased public spending on agricultural R&D, irrigation, and agricultural subsidy also has modest impacts on other sectors such as industry, service, and GDP growth.

The paper constructs the China dynamic CGE model and analyzes economy‐wide impacts of different types of public spending in China, especially for the food economy.

The role of money and monetary policy of the central bank in pursuing macroeconomic stability has significantly changed over the period since the end of World War II. Globalization, liberalization, integration, and transition processes generally shaped the crucial milestones of the macroeconomic development and substantial features of economic policy and its framework in Europe. Policy-driven changes together with variety of exogenous shocks significantly affected the key features of macroeconomic environment on the European continent that fashioned the framework and design of monetary policies.

This chapter examines the key basis of the central bank’s monetary policy on its way to pursue and preserve the internal and external stability of the purchasing power of money. Substantial elements of the monetary policy like objectives and strategies are not only generally introduced but also critically discussed according to their accuracy, suitability, and reliability in the changing macroeconomic conditions. Brief overview of the Eurozone common monetary policy milestones and the past Eastern bloc countries’ experience with a variety of exchange rate regimes provides interesting empirical evidence on origins and implications of vital changes in the monetary policy conduction in Europe and the Eurozone.

The authors aim to report empirical linkages between the US and Brazil, Russia, India and China (BRIC) financial stress indices catalyzing catalyzing dependent economic policy initiatives (an extended version of Singh and Singh, 2017a).

Initially, the study develops financial stress indices for the respective BRIC financial markets. Later, it captures linkages among the said US-BRIC indices by using Johansen cointegration, vector autoregression/vector error correction models (VECM), generalized impulse response functions, Toda–Yamamoto Granger causality, variance decomposition analyses and bivariate generalized autoregressive conditional heteroskedasticity (GARCH) model under constant conditional correlation framework, in general. Markov regime switching and efficient causality tests proposed by Hill (2007) are also used.

Overall, there are both short-run and long-run dynamic interactions observed between the US and Indian financial stress indices. For rest of the markets, only short-run interactions are found to be in existence. The time-varying co-movement coefficients report financial contagion impact of the US financial crisis on Russian and Indian financial systems only. Contrary to this, Brazilian and Chinese financial systems are largely exhibiting interdependence with the US financial system. Efficient causality tests report indirect impact of the Russian financial system on Brazilian via auxiliary Indian financial system.

The present study is the first of its kind capturing linkages among the US-BRIC financial stress indices by using diverse econometric models. The results support different market participants and policymakers in understanding effectiveness and implementation of economic policies while considering their cross-market interactions as well.

This research investigates Airbnb’s financial implications in emerging economies and their potential to influence stock market profitability.

Employing a multifaceted approach, the study combines parametric and nonparametric tests, robustness checks, and regression analysis to assess the impact of Airbnb’s announcements on emerging economy stock markets.

Airbnb’s announcements affect emerging economies' stock markets with a distinct pattern of cumulative abnormal returns (CAR): negative before the announcement and positive afterward. Informed investors strategically leverage this opportunity through short selling before the announcement and acquiring positions following it. Regression analysis validates these trends, revealing that stock index returns and inbound tourism affect CAR before announcements, while GDP growth influences CAR afterward. Announcements pertaining to emerging economies exert a more pronounced impact on stock indices compared to city-specific announcements, with COVID-19 period announcements demonstrating greater significance in abnormal returns than non-COVID-19 period announcements.

This study advances existing literature through a comprehensive range of statistical tests, differentiation between emerging countries and cities, introduction of five macroeconomic variables, and reliance on credible primary Airbnb data. It highlights the potential for investors to leverage Airbnb announcements in emerging markets for stock market profits, emphasizing the need for adaptive investment strategies considering broader macroeconomic factors.

This paper presents an integrated overview of the empirical literature on the impact of all forms of unconventional monetary policy on macroeconomic variables and on markets.

This survey covers the findings concerning portfolio rebalancing, signaling, liquidity, bank lending and confidence channels.

The positive effect of QE announcements on stock and bond prices seems to be unified across studies. A contagion effect from US QE to other emerging markets is identified, while currency devaluation is present in most cases for the country that its central bank adopted such policies. Moreover, impacts of non-conventional practices on GDP, inflation and unemployment are examined. The studies presenting weak instead of strong positive effects on inflation are more, and these studies, also, present weak positive effects on GDP growth.

Based on the large body of research on non-conventional action taking, this is the first survey including effects of each country that adopted quantitative easing (QE) measures and that provides results from every methodology employed in order to estimate unconventional practices' impacts.