Significant Spillover Effects Research Articles

Can green technology mergers and acquisitions enhance sustainable development? Evidence from ESG ratings

AbstractIn order to better understand the impact of green technology mergers and acquisitions (GTMA) on sustainable development, the difference‐in‐differences model is applied to investigate the direct impact and underlying mechanisms of GTMA on the environment, society, and governance (ESG) in China. Additionally, we established a two‐dimensional framework of “market versus government” to analyze the heterogeneity. The results show that: (1) GTMA is positively aligned with greater ESG performance, indicating that GTMA is an effective way to enhance sustainable development. (2) GTMA fosters ESG performance by boosting green subsidies (i.e., signal transmission channel), lowering financing costs (i.e., impression management channel), and enhancing green innovation (i.e., technology synergy channel). (3) The positive relationship is largely dependent on the collaborative supervision environment (i.e., “strong” market and “strong” government) and the appropriate policy environment (i.e., “big” market and “small” government). (4) Furthermore, GTMA carries significant spillover effects, with other enterprises in the same industry improving their ESG performance. Additionally, this paper proposes targeted directions for the government and enterprises to take advantage of GTMA dividends to realize superior ESG performance.

Quantile spillovers and connectedness between oil shocks and stock markets of the largest oil producers and consumers

This study explores the connectedness between major oil-producing and consuming countries' stock markets (United States, China, Russia, India) and different oil shocks categorized as demand, supply, and risk shocks, following Ready's (2018) framework. Employing a quantile-based connectedness approach and quantile cross-spectral dependence, our analysis spans from July 02, 2007 to May 31, 2023, encompassing diverse market conditions and events. These methodologies help identify interdependence patterns in extreme market scenarios at different time intervals. Key findings show variations in how these stock markets respond to oil shocks, depending on market conditions and quantiles. Demand-related shocks have the most significant spillover effects on the United States, Russia, and India, while risk-related shocks dominate as transmitters of shocks to the United States, China, and India in median quantiles. Market interconnectedness strengthens during extreme market conditions, reflecting historical events. Additionally, bearish markets offer diversification opportunities between these countries and crude oil. This study emphasizes the need for tailored investment strategies, monitoring global oil demand trends, dynamic portfolio management, crude oil inclusion in portfolios, and proactive responses to market players and geopolitical events. These insights benefit investors and policymakers seeking to optimize strategies in the interconnected global financial landscape.

Nonlinear Spatial Dynamic Panel Data Models with Endogenous Dominant Units: An Application to Share Data

This article develops a nonlinear spatial dynamic panel data model with one particularly interesting application to a structural interaction model for share data. To account for effects from dominant (popular) units, the spatial weights matrix in our model can allow for unbounded column sums. To account for heterogeneity, our model includes two-way fixed effects and heteroscedastic errors. We further consider the potential endogeneity of the spatial weight matrix constructed from socioeconomic distance. We investigate the quasi-maximum likelihood estimator (QMLE), generalized methods of moments estimator (GMME), and root estimator (RTE), and establish their consistency and asymptotic normality based on the near epoch dependence (NED) framework. The RTE can derive a relatively computationally simple and closed-form solution without evaluating the QMLE’s Jacobian matrix as well as the iterations by GMME. We consider both n , T → ∞ , and the strength of the dominant units is equal to 1 when T → ∞ . For the purpose of empirical analysis, we derive the marginal effects and their limiting distributions based on the proposed estimators. In an empirical application, we apply our model to China’s prefecture city-level data, revealing significant spillover effects of the tertiary industry share. These findings suggest that the development of the tertiary sector in large cities can foster its growth in small cities.

GEOPOLITICS, UNCERTAINTY, AND CRYPTOCURRENCY: A LOVE TRIANGLE GONE WRONG

This study aims to investigate the spillover effects from geopolitical risks (proxied by the geopolitical risk index GPRD) and cryptocurrencies-related uncertainty (proxied by the Cryptocurrency Uncertainty Index UCRY) to cryptocurrencies. We utilize the Baruník and Křehlík (2018) framework to detect time-frequency connectedness. Our investigation for the period 2017 to 2022 discovers significant spillover effects from both indices (GPRD and UCRY) to cryptocurrencies. Utilizing the information transmission theory and network graphs, our findings reveal that some cryptocurrencies function as net receivers of spillovers from geopolitical risks and uncertainty in the short-term, while over longer time horizons they transform into net transmitters of spillovers to uncertainty. The study underscores the importance of comprehending how uncertainty due to various factors (geopolitical, policy changes, regulatory changes, etc.) could affect the cryptocurrencies’ markets.

Volatility spillovers of cloud stocks: Evidence from China using the dynamic connectedness approach

AbstractBased on daily data from 2013 to 2022, this study examines the spillover effects of volatility between cloud stocks and other asset classes (global stocks, treasury bonds, gold and crude oil) using the VAR connectedness approach. The results show that there is a significant spillover effect from global stocks and crude oil markets to the cloud stock market. The spillover effects become stronger whenever there are shocks such as economic crisis, turbulence in the international financial markets, COVID‐19 and global inflation. However, nearly 91% of the variations of cloud stocks come from within, suggesting that the diversification/hedging value of cloud stocks is potentially high.

Assessing and mapping water-energy-food nexus smart innovations and practices in Vhembe District Municipality, Limpopo Province, South Africa

Water, energy, and food and their interactions (commonly referred to as the WEF nexus) are critical pillars to resolving the intractable global challenges such as poverty, hunger, malnutrition, poor sanitation, climate, and health crises. The nexus approach, practices, and innovations at the household level are critical determinants of whether resource use efficiency, co-benefits, basic rights to water and food, and sustainability governance are attained. In particular, smart WEF innovations can contribute to the current generations' economic, social, and environmental needs without compromising the needs of the future generation. The study aimed to identify smart innovations, practices, and factors influencing their adoption to inform policy and decision-making processes. The study intends to support scaling up the adoption of innovations and practices that enhance sustainability and resource security in support of the sustainable development goals (SDGs). Semi-structured interviews and key informant interviews (KII) supplemented with observational checklists were used to identify the WEF nexus smart technologies, innovations, and practices in Vhembe District Municipality, Limpopo Province, South Africa. Data were collected from a sample size of 128 households in the study area. Our findings revealed synergistic smart innovation practices across WEF resource use and management practices. Though indigenous knowledge (IK) practices were widely evident in the study area, non-existent WEF smart knowledge support systems existed in the study area. Indigenous knowledge practices were the most elicited innovation by 99.2% of households, suggesting it is critical to advancing WEF smart innovations and practices and needs to be integrated into any policy and governance interventions. A proportion of households recycle water (27%), whilst 53% use untreated water. Furthermore, the knowledge systems on smart WEF innovations were fragmented despite their potential to synergize sustainability objectives. Exploring innovation platforms (IPs) as vehicles for dissemination, innovation, and extension and advisory service delivery, as well as validation of Indigenous Knowledge Systems (IKS), has the potential to contribute to the diffusion, uptake, and scaling of existing innovation and practices with significant spill-over effects on WEF resource security and sustainability outcomes both at local and extra local scales.

Can innovation factor agglomeration enhance the government’s environmental governance capacity?

Innovative manpower agglomeration and innovative capital agglomeration provide vitality and guarantees for a country to achieve high-quality development, and the improvement of the government's environmental governance capacity can guarantee the smooth advancement of the country's ecological civilization construction work; thus, it is very important to study the impact of innovation factor agglomeration on the government's environmental governance capacity. Based on this, this article establishes a mediated moderating effect model and a spatial econometric model, adopts the panel data of 30 provinces in China from 2009 to 2020 as an example, and divides innovation factor agglomeration into innovation manpower agglomeration and innovation capital agglomeration to study the relationship between them and the government's environmental governance capacity. The results of the empirical analysis show that (1) both innovation manpower agglomeration and innovation capital agglomeration can significantly promote the improvement of the government's environmental governance capacity. (2) Technological innovation plays a mediating role in promoting the government's environmental governance capacity through innovation factor agglomeration. Voluntary environmental regulation can promote the government's environmental governance capacity, but it attenuates the role of innovation capital agglomeration in promoting the government's environmental governance capacity. (3) Local innovative manpower agglomeration has a significant spillover effect, and innovative manpower agglomeration in neighboring places inhibits the enhancement of local governments’ environmental governance capacity. (4) Innovation capital agglomeration in neighboring places will inhibit the local government's environmental governance capacity, but its effect is much smaller than the promotion effect of local innovation capital agglomeration on the government's environmental governance capacity.

Spatio-temporal pattern assessment of China's environmental performance and its spatial drivers: evidence from city-level data over 2003-2019.

A comprehensive assessment of China's environmental performance (EP) and an investigation into its driving factors are essential prerequisites for advancing environmental protection efforts. However, existing studies have often exhibited a one-sided EP evaluation approach and lacked a systematic perspective. Consequently, this study has adopted a holistic approach by integrating environmental protection and pollution within the same theoretical framework. We have employed the "P-S-R" model to comprehensively assess the EP of 272 cities from 2003 to 2019. Concurrently, we have applied the spatial Durbin model to analyze EP drivers utilizing three spatial matrices. The findings of this study reveal several vital insights. Firstly, the mean EP value for China is 0.1138, indicating a low level, but it demonstrates a consistent upward trend over the years. When comparing cities with high EP, they are predominantly situated in northern China, northeastern China, and certain areas along the southeastern coast. Secondly, from a spatial perspective, the directionality of EP exhibits a trend from "northeast to the southwest," with the center of gravity located in and around Zhumadian, Henan Province, gradually shifting towards the northeast. The majority of cities fall within the H-H and L-L clusters, displaying significant positive spatial autocorrelation effects. Thirdly, EP drivers encompass a wide range of factors, including economic development, urbanization, resource dependence, industrial structure, infrastructure construction, environmental regulation, government regulatory capacity, scientific and technological innovation, and foreign direct investment. These drivers also exhibit significant spillover effects. Finally, the characteristics of EP development vary between resource-based cities (RBCs) and non-resource-based cities (non-RBCs), as well as among the eastern, central, and western regions. Moreover, there are disparities in the driving factors' direct, indirect, and overall effects. Consequently, we must propose tailored strategies and recommendations to enhance EP, considering the heterogeneous effects of influencing factors across different city types, regions, and collaboration approaches.

Biased innovation and network evolution: digital driver for green innovation of manufacturing in China

ABSTRACT The study aims to explore the spatial association network characteristics of biased green innovation in the manufacturing sector and its core drivers. This study constructs a Malmquist-Luenberger decomposition index model to identify the input and output biases of green technological innovation (GIIM and GIOM) in the manufacturing industry. This study uses a modified gravity model and social network analysis method to conduct a robust assessment of GIIM spatial association network of 30 provinces in China from 2012 to 2021. The results show: (1) The GIIM association network structure is stable and has good accessibility, with close connections between provinces and blocks, and significant spillover effects between provinces. (2) The regional network shows a “core-periphery” spatial variation, with the core area expanding and the peripheral area shrinking. (3) The digital transformation characteristics of the network components and the intensity of environmental regulation have a significant impact on GIIM.

The implication of cryptocurrency volatility on five largest African financial system stability

This study examined the interconnectedness and volatility correlation between cryptocurrency and traditional financial markets in the five largest African countries, addressing concerns about potential spillover effects, especially the high volatility and lack of regulation in the cryptocurrency market. The study employed both diagonal BEKK-GARCH and DCC-GARCH to analyze the existence of spillover effects and correlation between both markets. A daily time series dataset from January 1, 2017, to December 31, 2021, was employed to analyze the contagion effect. Our findings reveal a significant spillover effect from cryptocurrency to the African traditional financial market; however, the percentage spillover effect is still low but growing. Specifically, evidence is insufficient to suggest a spillover effect from cryptocurrency to Egypt and Morocco’s financial markets, at least in the short run. Evidence in South Africa, Nigeria, and Kenya indicates a moderate but growing spillover effect from cryptocurrency to the financial market. Similarly, we found no evidence of a spillover effect from the African financial market to the cryptocurrency market. The conditional correlation result from the DCC-GARCH revealed a positive low to moderate correlation between cryptocurrency volatility and the African financial market. Specifically, the DCC-GARCH revealed a greater integration in both markets, especially in the long run. The findings have policy implications for financial regulators concerning the dynamics of both markets and for investors interested in portfolio diversification within the two markets.

Spillover Effects between Crude Oil Returns and Uncertainty: New Evidence from Time-Frequency Domain Approaches

This paper examines the extent to which uncertainty in the energy market, the financial market, the commodity market, the economic policy, and the geopolitical events affect crude oil returns. To consider the complex properties of time series, such as nonlinearity, temporal variability, and unit roots, we adopt a two-instrument technique in the time–frequency domain that employs the DCC-GARCH (1.1) model and the Granger causality test in the frequency domain. This allows us to estimate the dynamic transmission of uncertainty from various sources to the oil market in the time and frequency domains. Significant dynamic conditional correlations over time are found between oil returns—commodity uncertainty, oil returns—equity market uncertainty, and oil returns—energy uncertainty. Furthermore, at each frequency, the empirical results demonstrate a significant spillover effect from the commodity, energy, and financial markets to the oil market. Additionally, we discover that sources with high persistence volatility (such as commodities, energy, and financial markets) have more interactions with the oil market than sources with low persistence volatility (economic policy and geopolitical risk events). Our findings have significant ramifications for boosting investor trust in risky energy assets.

Examining the effects of an infant-toddler school readiness intervention in center- and family-based programs: Are results generalizable?

Infants and toddlers frequently participate in either center- or family-based childcare programs. However, little is known about the efficacy of early learning interventions introduced in these two types of programs, in particular family-based programs. The present work builds upon findings of a recent experimental trial demonstrating that a 20-week infant-toddler intervention supporting center- and family-based teachers to be more explicit and intentional in their interactions had a significantly positive effect on targeted child outcomes. In this follow-up paper, we conducted secondary analyses exploring effects of the intervention across the two contexts, center- and family-based programs. Analyses showed that the social validity of the intervention was generally high in both settings, but even higher in family-based than center-based programs. Findings also showed that teachers in both types of programs implemented the intervention at a satisfactory level, but family-based teachers tended to implement more small-group activities and had more conversations with individual children. There were no differential impacts on child outcomes across the two contexts, except for an overall significant spill-over effect on the outcome of empathy within center-based care. Finally, we found that the intervention had positive effects on teachers’ use of counting and math activities in both types of programs.

Cocoa, livelihoods, and deforestation within the Tridom landscape in the Congo Basin: A spatial analysis.

In the context of emerging international trade regulations on deforestation-free commodities, the drivers of households' deforestation in conservation landscapes are of interest. The role of households' livelihood strategies including cocoa production, and the effects of human-elephant conflict are investigated. Using a unique dataset from a survey of 1035 households in the Tridom landscape in the Congo basin, the spatial autoregressive model shows that: (1) Households imitate the deforestation decisions of their neighbors; (2) A marginally higher income from cocoa production-based livelihood portfolios is associated with six to seven times higher deforestation compared to other livelihood strategies with a significant spillover effect on neighboring households' deforestation. The increase in income, mainly from cocoa production-based livelihoods in open-access systems can have a negative effect on forests. Households with a higher share of auto-consumption are associated with lower deforestation. If economic development brings better market access and lower auto-consumption shares, this is likely to positively influence deforestation. Without proper land use planning/zoning associated with incentives, promoting sustainable agriculture, such as complex cocoa agroforestry systems, may lead to forest degradation and deforestation.

Time‐Frequency Connectedness between Green Bonds and Conventional Financial Markets: Evidence from China

This paper examines the dynamic evolution and volatility spillovers between China’s green bond market and conventional financial markets (bond, stock, commodity, and foreign exchange markets) using time and frequency connectedness measures. The empirical findings are as follows: firstly, there is a significant volatility spillover effect between the green bond market and other traditional financial markets, with the spillover effect showing clear time‐varying characteristics. The total spillover effects among all markets increase notably during extreme market conditions. Secondly, the green bond market primarily acts as a net risk spillover transmitter in most periods. Thirdly, compared to the stock, foreign exchange, and commodity markets, the green bond market has a more significant spillover effect on the traditional fixed‐income market. Finally, the volatility spillover effect of the green bond market on other markets exhibits a time‐frequency evolution, predominantly driven by short‐term factors. However, as market maturity increases, the influencing factors of the spillover effect gradually shift from short‐term to medium and long‐term factors. These findings offer insights for portfolio and risk management.

Spatialtemporal evolution characteristics of ozone in China and its response to urbanization.

Based on the background of urbanization in China, we used the dynamic spatial panel Durbin model to study the driving mechanism of ozone pollution empirically. We also analyzed the spatial distribution of ozone driving factors using the GTWR. The results show that: i) The average annual increase of ozone concentration in ambient air in China from 2015 to 2019 was 1.68μg/m3, and 8.39μg/m3 elevated the year 2019 compared with 2015. ii) The Moran's I value of ozone in ambient air was 0.027 in 2015 and 0.209 in 2019, showing the spatial distribution characteristics of "east heavy and west light" and "south low and north high". iii) Per capita GDP industrial structure, population density, land expansion, and urbanization rate have significant spillover effects on ozone concentration, and the regional spillover effect is greater than the local effect. R&D intensity and education level have a significant negative impact on ozone concentration. iv) There is a decreasing trend in the inhibitory effect of educational attainment and R&D intensity on ozone concentration, and an increasing trend in the promotional effect of population urbanization rate, land expansion, and economic development on ozone concentration. Empirical results suggest a twofold policy meaning: i) to explore the causes behind the distribution of ozone from the new perspective of urbanization, and to further the atmospheric environmental protection system and ii) to eliminate the adverse impacts of ozone pollution on nature and harmonious social development.

The Illusion of “Smart” Sanctions: The Russian Case

The 21st century has seen a gradual shift from overwhelming sanctions, mainly trade embargoes, towards targeted or “smart” sanctions. The latter target designated natural and legal persons associated with a country’s government, while ostensibly imposing minimal hardship on its general population. However, many empirical studies prove the existence of significant spillover effects and collateral damage from targeted sanctions. This research aims to determine whether “smart” sanctions are a reality, or a myth created to legitimize their use. The analysis shows that targeted sanctions against Russia have had spillover effects beyond the targets. The authors consider four types of spillover effects—economic, political, legal, and psychological (or reputational) ones—and suggest the criteria that determine how targeted a sanction is.

Spillover effects of government subsidies on agricultural supply chains under risk-sharing mechanisms

This paper focuses on the agricultural supply chain and proposes a new financing model of risk sharing: the collateralized loan. In order to examine the operational effectiveness of the risk-sharing mechanism, we consider the effects of government subsidies and risk aversion factors. In the collateralized loan, the purchaser serves as the leader to provide loans to the farmer when the farmer provides collateral. The simulation results demonstrate that government subsidies can bring significant spillover effects to the whole supply chain. The effect’s extent increases as the subsidy increases. And the spillover effect is more obvious under the collateralized loan than bank financing. The discount factor also generates a spillover effect for the agricultural supply chain through the inversion mechanism. The lower the discount factor, the more obvious the spillover effect. The increase in government subsidies facilitates the operation of risk-sharing mechanisms, while the increase in risk aversion hinders the operation of the mechanisms. This paper provides new insights into the issue of agricultural finance and managerial implication to precisely assist farmers in greater need.

Business Confidence in the Sustainable Manufacturing Sector in the Context of Production, Production Prices, and Interest Rates

Business confidence can be a very important predictor of future development and sustainability in a selected industry. It is one of the economic sentiment indicators belonging to the most important indicators of the health of the economy. This paper examines the relationships between the Business Confidence Indicator (BCI) of the manufacturing sector and the production, production prices, and interest rates of two neighbouring countries, the Slovak Republic and Hungary. These relationships are examined within the manufacturing sector because it has long been the driving force of sustainable economic development and has significant spill-over effects on the other sectors of the economy. A cluster analysis is performed with the aim of positioning the selected countries into clusters within the OECD countries in relation to the examined variables. Multiple regression models were used to verify the mentioned relationships between variables, separately for each of the two analysed countries. The coefficients of determination are not too high (Slovakia 0.5 and Hungary 0.38), but in the case of sentiment, they reach higher values than in comparable research. Data from the freely available OECD database was used. It can be concluded that the results show positive relationships between the BCI and the production and long-term interest rates, and negative relationships between the BCI and the Producer Prices Index (PPI) and short-term interest rates. The relationship with the short-term interest rates cannot be confirmed in the case of Hungary. Other differences are also shown in that a higher PPI can negatively affect the BCI more intensively in Hungary (regression coefficient 0.18), and that in the case of the Slovak Republic, it appears that the level of influence of the long-term interest rates on the BCI is higher than that in Hungary (the difference between the regression coefficients is 0.27). Practical implications are stated for relevant institutions in the country in three areas: (1) in support of increasing production; (2) in the regulation and subsidization of input production costs; (3) in the stabilization of the lending behaviour of financial institutions.

Assessing financial risks of foreign agricultural investment in belt and road countries: A risk index approach and VHSD-EM model analysis.

This study establishes a risk index system to evaluate the financial risks of foreign agricultural investment in Belt and Road countries. Agricultural foreign investment risk prevention has emerged as a crucial concern across various sectors globally. We assess the four key dimensions such as political and military risk, economic market risk, social and cultural risk, and resource and environmental risk. We employ the Vertical and Horizontal Leveling Method and Entropy Weighting Method (VHSD-EM) for measuring and analyzing foreign agricultural investment risk levels in Belt and Road countries from 2014 to 2021. Moreover, we used spatial correlation analysis, the Getis-Ord Gi* statistic, to identify hot and cold spots of agricultural foreign investment risks. First political & military, and environmental risks are the main influencing factors of agricultural foreign investment risk. The average AFDI level exceeded in Southeast and South Asia, and certain spillover effects were found in Southeast Asia. Second, the Belt and Road" initiative effectively reduces the risk of AFDI and helps to weaken the spillover effect among fellow countries. A significant spillover effect in AFDI from neighboring countries can lead to high-risk areas for sustained AFDI formation. Third to address such challenges, the Chinese government has prerequisites to enhance foreign agricultural investments in Belt and Road countries and establish a measurement index for agricultural investment risks. Government needs to establish a public service system to enhance the development of large-scale multinational agricultural enterprises. Foreign cooperation is essential for multi and bilateral investment negotiation and optimizing the financial tools to mitigate agricultural foreign direct investment risk in Belt and Road countries.

The Effect of International Tourist Arrivals on Regional Development in East Nusa Tenggara (NTT) Province

The government of Indonesia has established Komodo National Park as one of the priority tourist destinations since 2015 to stimulate the number of international tourist arrivals to Komodo National Park, located in West Manggarai Regency, East Nusa Tenggara Province (NTT). This study aims to analyze the spillover effect of the surge of international tourists in Komodo National Park and its impact on the regional economy in NTT. This study used the Spatial Autoregressive (SAR) and Spatial Durbin Model (SDM) methods on district-level data from 2012 to 2018 and found that the surge of international tourists visiting Komodo National Park had a positive and significant spillover effect on the increase of tourism activities in other tourist destinations in NTT. The rise of tourism activity impacted regional economic growth significantly in West Manggarai Regency and other districts in NTT, and the tourism growth positively influenced the regional economic convergence in NTT.