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This study is the first that aims to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

Multiple spatial weight matrices can capture the contiguity of spatial units from various dimensions, which could be exploited to improve the precision of inference as well as prediction accuracy. To the best of the authors’ knowledge, this is the first study to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

With network structure analysis, this study finds that they contain different information content from the perspective of graphical display, node strength and correlation. Developed and emerging countries all play major roles in trade connection, while only developed countries play major roles in financial linkage. Second, by applying the multidimensional SAR model, only the spatial autocorrelation coefficients for trade and financial linkages are significant during the full sample period, which is in sharp contrast to published studies using the SAR model with a single matrix. Third, the spillover channels that play major roles in various periods are different. Only trade channel plays a role during crisis periods and it is the most important. Fourth, the spatial correlation among countries greatly amplifies the shock’s impacts on one market. And spatial effect for developed countries is larger than those for emerging countries, while the mean spatial effect of a unit shock in the USA on emerging countries is slightly greater than that on developed countries.

Multiple spatial weight matrices can capture the contiguity of spatial units from various dimensions, which could be exploited to improve the precision of inference as well as prediction accuracy. To the best of the authors’ knowledge, this is the first study to investigate international transmission channels of sovereign risk among G20 and explore its influential factors by applying the multidimensional SAR model.

The paper investigates the prevalence of extreme poverty in a panel of 39 sub-Saharan African (SSA) countries over the period 2000–2018 while accounting for spillover effects.

The study adopts the recently developed spatial dependence-consistent, bias-corrected quasi-maximum likelihood (QML) estimators and the linear dynamic panel regression to control for the potential endogeneity in poverty and corruption spillovers.

The spatial model shows. consistently across all the specifications, that there is a substantial spillover effect of corruption and poverty across the region. Additionally, the study also found that investment in health and education is a significant determinant of poverty in the region. However, the effectiveness of these policy variables to reduce poverty declines in the face of corruption spillovers. More importantly, the empirical analysis shows that poverty does not only exhibit spatial spillovers but also has a persistent effect over time. The results, therefore, suggest that to reduce poverty in the region, sub-Saharan African governments must adopt spatially differentiated policies and programmes by working together to reduce unemployment and corruption in the region, and not the widely adopted spatially mute designs currently in place. The research and policy implications are discussed.

The study accounts for spatial dependency and spillover effects in the analysis of poverty and corruption in SSA

By analyzing the mechanisms by which rural infrastructure resilience (RIR) impacted population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

This study considered 213 administrative villages in Longxi County in the Longzhong loess hilly region as the evaluation unit. Based on the construction of a multidimensional RIR evaluation system, the spatial spillover effect of RIR on population loss was determined using the spatial Durbin model (SDM).

The average resilience of each subsystem of rural infrastructure in Longxi County was low, and there were large differences in the spatial distribution. The mean RIR index value was 0.2258, with obvious spatial directivity and agglomeration characteristics. The population loss index of Longxi County had a value of 0.1759, with 26.29 of villages having a high loss level. The population loss was relatively serious and was correlated with the spatial distribution of RIR. The villages with larger RIR index values had lower population loss. The RIR had a significant spatial spillover effect on population loss. Productive infrastructure resilience and living infrastructure resilience (LIR) had negative spillover effects on population loss, and social service infrastructure resilience (SSIR) had a positive spillover effect on population loss.

By analyzing the mechanisms by which RIR impacted on population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

This study aims to identify extensive and intensive margins in exports and imports and examine whether incoming foreign direct investments (FDI) benefit local firms in Indonesia through the export and import channels.

Using Heckman’s two-step selection model to consider the potential of bias of self-selection in export–import participation, this study uses the firm-level data from 2008 to 2015 collected from Statistik Industri and proximate both export and import spillovers.

The authors found that internal factors are critical for a firm to be an exporter, signaling self-selection in exports and imports. Spillover effects from FDI (spatial properties) support export but lower import propensity and intensity.

This study implies that improving human capital (absorptive capacity) is needed to accelerate export intensity and policies supporting FDI inflows in complementary sectors (noncompeting industries) can increase export propensity and intensity and reduce imports.

This study contributes to the literature in several ways. First, the proposed export spillovers model that accounts for impacts through a demonstration channel is applied to the import channel. Moreover, this study extends the model developed by Franco and Sasidharan (2010) and Yasin et al. (2022) by incorporating spatial spillover effects at the provincial level. Subsequently, the authors test whether a firm’s technological intensity determines export–import propensity and intensity. This can indicate whether specific sectors are more likely to participate in international activities based on their use of technology.

By discussing the spatial spillover effect and regional heterogeneity of digital economy and green agricultural development level, this paper aims to provide countermeasures and suggestions for the better development of green agriculture in the contemporary era when digital economy is universally developed and at the same time provide development suggestions suitable for green agriculture's development characteristics and initial conditions for different regions.

This paper discusses the theoretical foundation of the digital economy and green agriculture development and utilizes panel data from 30 provinces in China from 2011 to 2018. By employing the Super-Efficiency Slack-based Measure and Malmquist-Luenberger (SBM-ML) model based on unexpected output to measure the total factor productivity of green agriculture and employing the spatial panel Durbin model to empirically test the spatiotemporal effects of the digital economy on green agriculture development from both temporal and spatial dimensions. Finally, the model is tested for robustness as well as heterogeneity.

The research findings are as follows: First, from the perspective of time effect, digital economy has a continuous driving effect on the development of green agriculture and with the passage of time, this effect becomes more and more prominent; second, from the perspective of spatial effect, digital economy has a significant positive impact on the development of local green agriculture, while digital economy has a significant negative impact on the development of surrounding green agriculture. Finally, the impact of digital economy on the development of green agriculture shows significant differences in different dimensions and regions.

As an important driver of economic growth, the digital economy has injected new impetus into agricultural and rural development. Along with the intensifying environmental pollution problems, how to influence the green development of agriculture through the digital economy is a proposition worthy of attention nowadays. This paper analyzes the relationship between the digital economy and agricultural green development in multiple dimensions by exploring the temporal and spatial spillover effects of the digital economy on agricultural green development, as well as the heterogeneity in different dimensions and in different regions and derives policy insights accordingly in order to improve relevant policies.

Examine the effects of sudden environmental disasters on the advancement of both renewable and conventional energy technologies.

Utilizing panel data from 31 Chinese provinces spanning 2011 to 2022, the SEM (Spatial Error Model) dual fixed model is utilized to examine the impact of sudden environmental disasters on energy technologies.

The findings reveal that: (1) Sudden environmental disasters exert a markedly positive influence on the Innovation of Renewable Energy Technologies (IRET), while their impact on conventional energy technologies is positively non-significant. (2) Sudden environmental disasters not only significantly enhance innovation in local renewable energy technologies but also extend this positive influence to neighboring regions, demonstrating a spatial spillover phenomenon. (3) Research and Development (R&D) funding serves as a partial mediator in the relationship between sudden environmental disasters and renewable ETI. In contrast, Foreign Direct Investment (FDI) exhibits a masking effect.

Consequently, the study advocates for intensified efforts in post-disaster reconstruction following abrupt environmental events, an elevation in the quality of foreign direct investments, and leveraging research funding to catalyze innovation in renewable energy technologies amid unforeseen environmental crises.

Stock markets are highly sensitive to foreign and domestic events. Stock exchange markets react promptly to news and are known as an indicator of good and bad trading conditions. Terrorist attacks leave adverse effects on the economy and cause stock price volatility and, consequently, stock return volatility. Therefore, this paper aims to analyze the spatial effects of terrorism on stock market returns in the Middle East from 2008 to 2019.

This paper uses analytical research design and estimates spatial model. Before estimating the spatial model, the spillover effects were confirmed for the spatial autoregressive model using Moran’s diagnostic test for spatial dependence, Geary’s C test and Akaike statistic.

The results of this study on spatial panel data and based on spatial autoregressive estimator indicated that terrorism and associated neighborhood effects had a negative impact on stock returns in Middle East countries. Also, the corruption index and oil price negatively affected stock market return in these countries, while the democracy index had a positive effect on stock market returns. According to the results, to achieve a high and stable stock market return, it is recommended that high-level consultation is pursued with leaders of involved countries to reduce the devastating effects of terrorist activities, increase political and economic stability, attract stockholders to stock markets and spend corresponding incomes developing the infrastructures in this sector in countries of this region.

Most of the studies have investigated the impact of terrorism on the stock market returns at the national or provincial level. However, the effect of terrorism on the stock market index in the tense region of the Middle East, which is the center of terrorist attacks in the world, has not been dealt with by considering the spatial econometric effects. Thus, to the best of the authors’ knowledge, this research is a first attempt to study the impact of terrorism on the stock market returns in Middle East countries using the spatial econometric approach.

The interaction between the culture and tourism industries is naturally concentrated in cities. However, the effect of their co-agglomeration on urban tourism development depends on their level of integration. This study aims to answer the following questions: Can culture–tourism co-agglomeration promote the development of the tourism economy? Is the effect of culture–tourism co-agglomeration on tourism development moderated by culture–tourism integration? Does culture–tourism co-agglomeration have spatial spillover effects?

Taking 262 prefecture-level cities in China from 2009 to 2019 as the research sample, this study measures the degree of culture–tourism co-agglomeration using a co-agglomeration index and measured culture–tourism integration using a coupling coordination degree model. Using a threshold model and a spatial econometric model, this study examined the effect of culture–tourism co-agglomeration on urban tourism development.

Culture–tourism co-agglomeration had a positive effect on the urban tourism economy, and the effect differed according to geographical location and city grade. Moreover, culture–tourism co-agglomeration’s effect on the urban tourism economy was affected by the level of culture–tourism integration. When the level of culture–tourism integration crossed the threshold, the positive effect of culture–tourism co-agglomeration on the urban tourism economy will be enhanced. Finally, culture–tourism co-agglomeration had positive spatial spillover effects on surrounding cities.

This study integrated culture–tourism co-agglomeration, culture–tourism integration and urban tourism economy into the same research framework and innovatively analyzed the effect of the scale and quality of culture–tourism interaction on the urban tourism economy.

文化产业和旅游产业之间的互动性使其天然地在城市中集聚发展。然而, 文化和旅游协同集聚对城市旅游发展的影响取决于它们的融合发展水平。本研究旨在回答以下问题：文化和旅游协同集聚能否促进旅游经济的发展？文化和旅游协同集聚对城市旅游发展的作用是否受到文化和旅游融合发展水平的调节影响？文化和旅游协同集聚对城市旅游发展的影响是否具有空间溢出效应？

本文以2009-2019年中国262个地级及以上城市为研究样本, 采用协同集聚指数测度城市文化和旅游集聚水平, 采用耦合协调度模型测度城市文化和旅游融合发展水平, 并通过构建面板门槛模型和空间计量模型, 检验文化和旅游协同集聚对城市旅游发展的影响。

文化和旅游协同集聚对城市旅游发展具有正向的促进作用, 而且这种影响会因为地理位置和城市等级的不同而存在差异。此外, 文化和旅游协同集聚对城市旅游发展的促进作用还受到文旅融合发展水平的影响, 当文旅融合发展水平跨越发展门槛后, 文化和旅游协同集聚对城市旅游发展的正向影响得到增强。最后, 文化和旅游协同集聚对周边城市具有积极正向的空间溢出效应。

本文将文化和旅游协同集聚、文化和旅游融合发展、城市旅游发展纳入统一框架, 创新性地分析了文化和旅游互动发展的规模和质量对城市旅游发展的影响。

The research objective of this paper is to investigate the direct and indirect impacts of green finance on agricultural carbon total factor productivity (ACTFP) within the framework of the carbon peaking and carbon neutrality (dual carbon) goals, while also identifying the driving factors through an exponential decomposition of ACTFP, aiming to provide policy recommendations to enhance financial support for low-carbon agricultural development.

In this paper, the Global Malmquist Luenberger (GML) Index method was employed to analyze and decompose the ACTFP, while the direct and spillover effects of China’s green finance pilot policy (GFPP) on ACTFP were assessed using the difference-in-differences (DID) method and the spatial differences-in-differences (SDID) method, respectively.

After the implementation of the GFPP, the ACTFP in the pilot area has experienced significant improvement, with the enhancement of technical efficiency serving as the main driving force. In addition, the GFPP exhibits a positive low-carbon spatial spillover effect, indicating it benefits ACTFP in both the pilot and adjacent areas.

Within the framework of the dual carbon goals, the paper highlights agriculture as a significant carbon emitter. ACTFP is assessed by considering the agricultural carbon emission factor as the sole non-desired output, and the impact of the GFPP on ACTFP is investigated through the DID method, thereby providing substantial validation of the hypotheses inferred from the mathematical model. Subsequently, the spillover effects of GFPP on ACTFP are analyzed in conjunction with the spatial econometric model.

Micro-regeneration can effectively enhance a neighborhood’s commercial vitality and serve as a viable approach to boost economic benefits. However, the small scale of micro-regeneration efforts and the fragmented nature of information currently limit the availability of strong empirical evidence demonstrating its impact on neighborhood commercial vitality. The aim of the study was to examine the link between micro-regeneration and neighborhood commercial vitality, focusing on the average, time-lag, spatial spillover, and spatial heterogeneity effects.

Using the panel data set of 1,755 neighborhoods in Chongqing from 2016 to 2021 as the research sample, the difference-in-differences (DID) method was employed in this study to explore the impact micro-regeneration has on neighborhood commercial vitality.

The results illustrate that: (1) micro-regeneration can promote neighborhood commercial vitality in terms of the number and types of local consumption amenities by 27.76 and 5.89%, respectively, with no time-lag effect; (2) the positive spillovers can exist within the range of 5,000 meters–5,500 meters of regenerated neighborhoods; and (3) the effect of micro-regeneration on neighborhood commercial vitality can be greater in peripheral areas than in core areas of the city.

The findings fill the knowledge gap on the relationship between micro-regeneration and neighborhood commercial vitality. Additionally, the results on the time-lag effect, spatial spillover effects, and spatial heterogeneity provide practical implications that can support the government and private sector in developing temporal and spatial arrangements for micro-regeneration projects.