Spillover Effects Research Articles

Innovative talent agglomeration, spatial spillover effects and regional innovation performance-Analyzing the threshold effect of government support.

As the primary source of innovation in science and technology, the gathering of creative talent plays a significant role in fostering regional innovation and providing the impetus needed to realize the Chinese people's aspiration of a great national rejuvenation. Using panel data from 31 provinces over a 12-year period between 2009 and 2020, the spatial Durbin model is constructed to examine the spatial spillover impact of talent agglomeration on the advancement of regional innovation performance, and the panel threshold model is identified and set up to consider whether the nonlinear effect between talent agglomeration and regional achievements in innovation is significant. The analysis demonstrates that: talent pooling has a non-linear effect on the level of innovation performance development, within a certain scale, talent pooling produces an increasing marginal contribution to innovation performance, but after exceeding the limit, it produces a diminishing marginal contribution; the double threshold effect of talent pooling on regional innovation performance is more significant, and government support as a moderating variable confirms that there is a structural mutation between talent pooling and innovation capability. The structural mutation, within a certain threshold range, plays the role of efficient promotion, providing reference for improving regional innovation level.

Are carbon costs transmitting to the building materials industry?

IntroductionReconciling economic development and emission reduction of polluting gases requires balancing long-term and short-term goals across various markets. As a new production cost, the price of carbon allowances is assumed to affect the supply and demand of carbon-intensive sectors. Therefore, this study examines the dynamic price spillover effects between China as the largest carbon emission market and the carbon-intensive building materials industry in a unified time-frequency framework.MethodsThis study measures the dynamic overall and directional spillover effects of carbon and building materials markets in three frequency bands, considering eight carbon pilots and the national carbon market in China and four important building materials.ResultsThe empirical results show that the bi-directional spillover between carbon and the building materials market shows pronounced characteristics in the time-frequency domain, especially in the short-term frequency band of one day to one week, with strong connectivity. After the launch of the national carbon market, the information spillover from the building materials market to the carbon pilots become stronger. Both the carbon pilots and the national carbon market have significant short- and long-term impacts on the building materials market. In addition, there are differences in the impact of carbon markets on various types of carbon intensive building materials.DiscussionCompliance cycles in carbon markets are likely to induce sharp fluctuations in spillovers between the two markets. Therefore, balancing industrial development and stabilizing carbon prices requires a refined policy design that considers the diversified impacts of carbon markets on different industries at across frequencies.

Prediction of Energy-Related Carbon Emissions in East China Using a Spatial Reverse-Accumulation Discrete Grey Model

In order to better analyze and predict energy-related carbon emissions in East China to address climate change, this paper enhances the predictive capabilities of grey models in spatial joint prediction by creating the reverse-accumulation spatial discrete grey model RSDGM (1,1,m) and accumulation spatial discrete grey breakpoint model RSDGBM (1,1,m,t), which took the impact of system shocks into consideration. The efficiency of the models is confirmed by calculating the energy-related carbon emissions in East China from 2010 to 2022. Future emissions are predicted, and the spatial spillover effect of emissions in East China is discussed. The conclusions are as follows: (1) The RSDGM (1,1,m) theoretically avoids errors in background values and parameter calculations, reducing computational complexity. Empirically, the model exhibits high performance and reflects the priority of new information in spatial joint analysis. (2) The RSDGBM (1,1,m,t) captures the impact of shocks on system development, improving the reliability of carbon emissions prediction. (3) Jiangsu and Shandong are positively affected by spatial factors in terms of carbon emissions, while Shanghai and Zhejiang are negatively affected. (4) It is estimated that carbon emissions in East China will increase by approximately 23.8% in 2030 compared to the level in 2022, with the levels in Zhejiang and Fujian expected to increase by 45.2% and 39.7%, respectively; additionally, the level in Shanghai is projected to decrease. Overall, East China still faces significant pressure to reduce emissions.

Identification of Key Determinants Influencing Spatiotemporal Heterogeneity of Urban Resilience

The identification of spatiotemporal heterogeneity, its key determinants, and the interaction effects between the driving factors of urban resilience (UR) within and between subregions is fundamental for understanding its underlying mechanisms. A resilience evaluation model was applied to analyze the temporal and spatial differences in UR in Hunan Province, China. A hot spot analysis identified clusters of cold and hot spots. The contributions of spatiotemporal differences in UR within and between subregions were assessed using the Theil index. A geodetector analysis determined the factors influencing UR and their interactions. There was an increasing trend in UR from 0.2692 in 2014 to 0.3422 in 2022. The number of cities with a high resilience gradually increased from 2014 to 2022, while there was a decreasing gradient in UR from northeast to southwest across the province. High-resilience cities had positive spillover effects on the surrounding area. Hot spots were predominantly located in the northeast, while cold spots were concentrated in the southwest. The barycenter of UR shifted from northeast to southwest by 2018, before moving southeast by 2022. The Theil index values declined over time both within and between subregions. Per capita GDP, the average wages of on-the-job employees, per capita social consumption, and doctor density were found to enhance UR. Two-factor interactions had a greater influence on the spatiotemporal heterogeneity of UR than single factors. Two-factor and nonlinear enhancements were identified as the primary mode of influence.

Beyond the Stereotype: Exploring Monetary Donations and Volunteerism Among People With Disabilities

This study aims to provide empirical evidence supporting the perception of people with disabilities as givers and to explore their giving behaviors. Utilizing data from 2019 Social Survey by Statistics Korea, the study combined resource theory and selective optimization with compensation (SOC) theory to compare monetary donations and volunteer behaviors between people with disabilities and people without disabilities while identifying factors that influence giving behavior among people with disabilities. The study findings revealed that people with disabilities participate in giving behaviors despite resource scarcity, and disability had no significant effect on volunteer hours. Social and cultural resources were significant factors that influenced the amount of donations and hours of volunteering among people with disabilities. In addition, a mutual spillover effect was observed between donation amounts and volunteer hours. Such findings highlight the importance of lowering the barriers and connecting people with disabilities to giving behaviors.

Performance Assessment of Three Living Shorelines in Cedar Key, Florida, USA

A community-driven effort in Cedar Key, Florida, USA, resulted in the construction of three living shoreline retrofits intended to bolster failing coastal infrastructure and restore habitat functions in Daughtry Bayou. A multi-year monitoring program tracked changes in elevation and vegetation communities across the entire shoreline profile from lower-intertidal to upland/transitional zones and measured wave attenuation during typical and extreme (hurricane) conditions. Overall, these living shoreline retrofits served to soften more than 30% of the bayou’s shoreline, dramatically reducing the extent of armored shoreline in direct contact with tidal influence. The extent of vegetated habitat area has increased at all three sites, despite sediment export from higher elevation zones driven largely by repeated impacts from hurricanes and tropical storms. These living shorelines reduced wave energy by 33 to 79% in typical conditions and by up to 28% in hurricane conditions, consistently outperforming armored shorelines, even during an extreme event (Hurricane Idalia). Our monitoring efforts were sufficient to capture project trajectories and assess performance relative to project goals, but our program had limitations that could have been overcome with additional resources and increased focus on capturing spillover effects. The living shoreline retrofit projects assessed here have persisted through and shown signs of recovery after multiple tropical storms and hurricanes, while providing important energy reduction services. Thus, living shoreline retrofits continue to be a cost-effective shoreline management strategy in the short term for this area. However, our analyses suggest that persistence of these shorelines could be threatened by the combination of sea-level rise (by 2040), upland armoring, and an increasing risk of more intense tropical systems. Therefore, future interventions should more carefully consider these threats in conjunction with habitat enhancement goals.

Analysis of Spatiotemporal Disparities and Spatial Spillover Effect of a Low-Carbon Economy in Chinese Provinces Under Green Technology Innovation

This research, set against the backdrop of rapid global advancements in green technology innovation and aligned with China’s sustainable development strategy, conducts an in-depth analysis of the spatiotemporal disparities and spatial spillover effect of a low-carbon economy in Chinese provinces. Following empirical analysis and data testing, the study draws the following conclusions: (1) China’s low-carbon economy is subject to significant regional differences. Over time, the development level has improved annually, with the number of provinces above the middle level of low-carbon economy rising from 11 in 2010 to 22 in 2022. However, regional differences persist. The eastern region has shown the most significant progress, while the central area encountered its initial challenges first, and the development of the western area has unfolded in a more segmented manner. (2) In this paper, the low-carbon economy in China shows notable characteristics of spatiotemporal agglomeration, with the number of high–high agglomeration provinces rising from four in 2010 to seven in 2022, an increase of 78% year-on-year. The number of provinces and provinces in the low–low agglomeration mode increased from two in 2010 to six in 2022, a year-on-year increase of 200%. (3) China’s low-carbon economy demonstrates notable spatiotemporal evolution. The development process tends to remain stable during transitions, with a high likelihood of sustaining the current state while gradually advancing, avoiding abrupt changes across levels. (4) Innovations in green technology exert a positive influence on the advancement of the low-carbon economy, with a clear spatial spillover effect. In light of these findings, the research offers targeted recommendations for society, enterprises, and government stakeholders.

The perceptions of brand coappearance in product placement: cooperation, competition or coopetition?

Purpose Brands increasingly coappear in television programs while research in product placement has primarily focused on the placements of a single brand. Building on research related to product placement and cobranding, this study aims to systematically examine the roles of product competitiveness and brand competitiveness on the effectiveness of brand coappearance on television programs. Design/methodology/approach Extensive pretesting and four experimental studies were conducted. Real stimuli that had been digitally manipulated with fictitious brands were used in Study 1 (laboratory experiment involved student samples) and Study 2 (online experiment with a national sample) to examine the short- and long-term impacts of product competitiveness on brand coappearance. Real stimuli incorporated actual brands were used in Study 3 (involved advertisers’ key demographic) and Study 4 (alterative television program with a national sample) to examine the impacts of brand competitiveness and its interaction effect with product competitiveness. Findings The study found that coappearing with a product of high competitiveness significantly enhanced attitudes and purchase intention toward the coappearing products both in the short and long term. Product competitiveness further interacts with brand competitiveness to influence attitudes and purchase intention toward the coappearing brands suggesting a coopetition pattern for brand coappearances. The effect of brand coappearances did not vary substantially for low or high involvement products with or without character interaction. Research limitations/implications The study develops a useful framework for explaining and understanding the potential spillover effects in brand coappearances. It contributes to the existing literature on product placement and cobranding, while also paving the way for future research opportunities. Practical implications When introducing new brands, marketers are advised to consider coappearance deals with more competitive brands in highly competitive product categories. Conversely, coappearance deals with less competitive brands in less competitive product categories should be adopted to promote well-known brands. Advertisers may also consider product or brand exclusivity arrangements with broadcasters to enhance the effectiveness of the product placement. Originality/value Although brand coappearance in media content is likely to continue to proliferate, little is known about the phenomenon and its effects. To the best of the authors’ knowledge, this research is the first to systematically examine the perceptions toward brands coappeared in television programs.

Transportation Network Density, Domestic Market Integration and Excess Sensitivity of Household Consumption

Abstract From the perspective of domestic market integration, this paper systematically examines the impact of transportation infrastructure conditions on excess sensitivity of household consumption based on the China Family Panel Survey (CFPS) and multi-level matching panel data of transportation network density. The results show that the fast-growing development of the transportation infrastructure network has a significant alleviating effect on excess sensitivity of household consumption along the route, and the conclusion is still robust after the use of the multi-dimensional instrumental variable method and a series of robustness tests. According to the heterogeneity tests, in terms of the alleviating effect of transportation infrastructure, railroads rank the first, highways the second, substandard roads the third, waterways the fourth, and roads of other grades at the bottom. The mechanism test reveals that the improvement of domestic market integration is an important channel for transportation infrastructure to alleviate excess sensitivity of household consumption. This paper confirms that improving the transportation infrustructure system is conducive to the construction of a unified national market, alleviating excess sensitivity of consumption and stimulating consumption.This paper provides suggestions for implementing the strategy of boosting domestic demand, and helps the government understand households’ consumption decision-making from a broader perspective. This study also provides a theoretical basis for the economic spillover effect of transportation infrastructure.

Assessing and gauging the carbon emission efficiency in China in accordance with the sustainable development goals

In light of the growing urgency of climate change, carbon emissions reduction has emerged as a pivotal concern within global governance. In this paper, we take carbon emission efficiency (CEE) as the research object to characterize the relationship between economic, social, and environmental development in the context of the Sustainable Development Goals (SDGs). According to the regional division standard of eight comprehensive economic zones in China, this paper analyzed the spatial differences, evolutionary characteristics, and influencing factors of CEE in 257 Chinese cities over the period 2003–2019. The analysis conducted the Dagum Gini Coefficient, Markov Transition Probability Matrix, and geographically and temporally weighted regression model (GTWR). The results demonstrate that: (1) The CEE of Chinese cities exhibits an upward trajectory. (2) The inter-differences among the eight comprehensive economic zones represent the primary spatial source of CEE divergence. (3) The CEE of Chinese cities is a staged process of gradual enhancement with spatial spillover effects. (4) Environmental regulation, energy consumption intensity, and green finances are significant factors affecting CEE, and the direction and intensity of their influence have distinct spatial heterogeneity. Ultimately, this paper proposes measures to narrow the development gap between regions and enhance the CEE across the region. Meanwhile, implementing regional refinement management and formulating differentiated regional sustainable development planning.

Non-locality and spillover effects of residential flood damage on community recovery: Insights from high-resolution flood claim and mobility data

Examining the relationship between vulnerability of the built environment and community recovery is crucial for understanding disaster resilience. Yet, this relationship is rather neglected in the existing literature due to limitations in the availability of empirical datasets needed for such analysis. In this study, we combined fine-resolution flood damage claim data (composed of both insured and uninsured losses) and human mobility data (composed of millions of movement trajectories) during the 2017 Hurricane Harvey in Harris County, Texas, to specify the extent to which vulnerability of the built environment (i.e., residential flood damage) affects community recovery (based on the speed of human mobility recovery) locally and regionally. We examined such relationship using spatial lag, spatial reach, and spatial decay models to measure the extent of spillover effects of residential flood damage on community recovery. The results indicate that: first, the severity of residential flood damage significantly affects the speed of community recovery. A greater extent of residential flood damage suppresses community recovery not only locally but also in the surrounding areas; second, the spillover effects of residential flood damage on community recovery decay with distance from the highly damaged areas with a spatial reach of up to 31.2 miles (49.92 Km); third, areas display heterogeneous spatial decay coefficients, which are associated with urban form and structure features such as the density of facilities and roads. These findings provide a novel data-driven characterization of the spatial spillover effects of residential flood damage on community recovery and move us closer to a better understanding of complex spatial diffusion processes that shape community resilience to hazards. This study also provides valuable insights for emergency managers and public officials seeking to mitigate the non-local effects of flood damage.

The effect of the digital economy on carbon emissions in China's construction industry: evidence from spatial econometric analysis.

Carbon emission reduction in the construction industry is vital for realizing sustainable development, and the development of the digital economy plays an important role in this process. The impact of the digital economy on reducing carbon emissions in the construction industry is empirically explored through econometric analyses on a sample of panel data from 30 provinces in China from 2012 to 2021. The empirical results show that developing a digital economy can significantly reduce the construction industry's carbon emission intensity. Additionally, this impact has a significant spatial spillover effect and can benefit the neighboring regions. The mechanism test shows that the digital economy can reduce carbon emissions by improving the technological level of the construction industry. Moreover, the inhibiting effects of the digital economy on carbon emissions in the construction industry vary across different regions. They are more pronounced in the eastern and western regions of low coal-consuming regions. These findings offer valuable insights for policymakers to help drive the deeper integration of the digital economy with the construction industry and facilitate its transition to low-carbon development.

Industrial agglomeration, environmental regulation, and high‐quality development in rural China: From the perspective of spatial effect

AbstractExplore the interaction and spatial spillover effects between industrial agglomeration, environmental regulation, and high‐quality development of agriculture and rural areas, formulate appropriate industrial and environmental policies for different regions, guide the orderly agglomeration of agricultural sectors, and adjust the intensity of environmental regulation, which will help achieve high‐quality development. This manuscript firstly deconstructs the internal logic among industrial agglomeration, environmental regulation, and high‐quality development. Secondly, the Super‐SBM model is used to calculate the high‐quality development efficiency in rural China from 2000 to 2020. Finally, the Spatial Dubin Model (SDM) is used to analyze the spatial spillover effects and regional differences of industrial agglomeration, environmental regulation, and their integration impact on high‐quality development in rural China. The results show that: ① From 2000 to 2020, the high‐quality development efficiency shows a downward trend in fluctuation, and high‐quality development needs to be improved. ② There are significant regional differences in the effects of industrial agglomeration and environmental regulation on the high‐quality development efficiency. Industrial specialization agglomeration can effectively improve the high‐quality development efficiency, while industrial diversification agglomeration has uncertain effects. ③ The integration of environmental regulation and diversification agglomeration inhibits the high‐quality development efficiency, while the integration with specialization agglomeration has a stronger effect on improving high‐quality development efficiency. It is necessary to further enhance the effect of diversification agglomeration.

Analyzing risk contagion and volatility spillover across multi-market capital flow using EVT theory and C-vine Copula

There exists a potential interdependence among the United States markets, alongside an exceptional dependence on the East Asian stock markets. This transmission of risks is similarly evident in funds that are traded within markets. The current study seeks to uncover the pathways of risk contagion among various financial markets. This study examines how risks of funds spread across borders among China, the United States, and East Asia using Extreme Value Theory (EVT) and C vine copula quantile regression. It uses models such as AR (1), EGARCH (1, 1), Peak over Threshold (POT), and Copula methods to predict volatility events and correlation patterns during times of high volatility versus regular periods. Notably, the United States exhibits a risk transmission effect on the East Asian market compared to China. Furthermore, the findings indicate that, in times of high volatility, the risk spillover effect is comparatively weak, which is contrary to the situation of the US market. The study suggests that China's financial impact could progressively rise due to initiatives aimed at sector integration and enhancing financial independence. These findings have enlightening consequences for macro-prudential regulatory agencies, emphasizing the necessity of effective regulation to address cross-border risk spillovers. International investors can benefit from these results by incorporating risk-hedging strategies, accurately evaluating derivatives, and making wise investment decisions.

Beyond party and the pocketbook: racial resentment, hostile sexism, and perceptions of corporate political activity

Abstract Recent controversies over “woke” businesses have challenged traditional partisan political alignments, leading to increased criticism on the right of corporate political activity. This paper explores how the public evaluates corporate political activity, focusing specifically on whether individuals believe corporations are doing too much (or too little) to advance social and political goals. We are especially interested in how social identities and pocketbook considerations shape perceptions of corporate political activities not explicitly tied to social issues. Does racial resentment, for example, influence perceptions of corporate political activity designed to increase worker wages or improve health care? Or are the effects limited to efforts to achieve racial equality? We find that racial resentment and hostile sexism have spillover effects, affecting perceptions of corporate political activity across issue areas. Partisan affiliation, political ideology, and personal pocketbook considerations, in contrast, play a more limited role. Previous research has demonstrated the effect of racial resentment and sexism on support for welfare policies. We add to this literature by showing that racist and sexist opposition extends to corporate political activities that might not be explicitly identified as socially progressive.

A Study on the Impact and Mechanisms of Digital Economy Development on the Formation of New Productive Forces

This study investigates the impact of digital economy development on the formation of new productive forces in Guangdong Province. Utilizing key indicators such as GDP, education, and technology data, the research employs data cleaning and spline interpolation for preprocessing. Hypotheses P1 through P4 were proposed based on literature and regional policies. An evaluation system for new productive forces was established using the entropy weight method. Empirical analysis via STATA software confirmed a significant positive effect of the digital economy on new productive forces, supporting hypothesis P1. Mechanisms including technological breakthroughs, human capital, and industrial transformation were validated, confirming hypotheses P2, P3, and P4. The study highlights the spatial agglomeration effect between digital economy and new productive forces, suggesting mutual enhancement and significant spillover effects across regions.

Fiscal Policy, International Spillovers, and Endogenous Productivity

AbstractThe paper presents empirical evidence on the international effects of U.S. fiscal policy from structural vector autoregressions identified through external instruments in a panel setting for the G7 countries. An exogenous increase in U.S. government spending is estimated to produce sizable positive responses of output and consumption in the rest of the G7 countries, both about half as large as their domestic U.S. counterparts, while strongly depreciating the U.S. terms of trade and lowering the U.S. trade balance and short‐run real interest rates. Moreover, fiscal shocks are estimated to have a strongly positive impact on hourly labor productivity in the private sector. We solve a two‐country New Keynesian model in closed form and show that a low cost elasticity of varying technology utilization can simultaneously explain the positive productivity, consumption, and international spillover effects as well as the real depreciation resulting from expansionary U.S. government spending shocks.

The Spatial Impact of Innovative Human Capital on Green Total Factor Productivity in Chinese Regions Based on Quantity and Quality Dimensions

Green total factor productivity (GTFP) is a key driver of China’s green development, and innovative human capital (IHC) plays a pivotal role in enhancing GTFP. This study examines the impact of the quantity and quality dimensions of IHC on regional GTFP in China. Using panel data from 30 Chinese provinces from 2004 to 2018, this study constructs a spatial Durbin model (SDM) to empirically analyze the role of IHC in regional GTFP. Three main conclusions are obtained: (1) both the quantity and quality of IHC can significantly and directly improve regional GTFP, yet regional heterogeneity exists. In the eastern region, both IHCA and IHCQ have a significant impact, while in the middle-western region, only IHCA has a significant effect on GTFP; (2) IHC can boost the enhancement of regional GTFP through technological progress; and (3) the quantity of IHC (IHCA) produces a spatial spillover effect on regional GTFP, whereas the quality of IHC (IHCQ) does not exhibit this effect. Based on these conclusions, strategies for the green development of China and the coordinated development of the eastern and middle-western regions are proposed. The Chinese government should integrate IHC development into its environmental policies to improve environmental awareness and optimize the efficiency of human capital, taking regional differences into account.

Cultural, Economic, or Transport Link: Does Carbon Emissions Trading Promote “Good Neighbor” Carbon Emission Reduction?

Carbon emission reduction was a crucial objective for China’s green transformation, yet establishing regional cooperation with neighboring areas posed a significant challenge in carbon governance. We investigated the spillover effects of carbon emissions trading (CET) on carbon emissions among Chinese cities, employing spatial difference-in-differences (DID), Callaway and Sant’Anna DID (CSDID), and other methodologies. Our paper integrated datasets on high-speed rails, dialects, and carbon emissions at the prefecture-level city scale. The findings revealed that (1) CET reduces emissions by 11.55% in pilot regions, although the impact of the second policy pilot was not significant. (2) In terms of spillover effects, CET increased emissions in neighboring cities with economic and geographic ties, creating a “beggar-thy-neighbor” reduction model. Conversely, it reduced emissions in cities with shared cultural ties, fostering a “good neighbor” reduction model. (3) The policy spillover effect exhibited an “inverted N” curve, first decreasing, then increasing, and finally decreasing as economic and geographic distance increased. (4) Technological advancement was identified as the primary mechanism driving the spillover effects of CET. To achieve the dual-carbon goal, avoiding harmful economic competition and promoting low-carbon cultural exchanges were essential.

Industry return volatility and spillover effects in stock market under climate risk perception

ABSTRACT Utilizing alternative dimension reduction methods, this study constructs three Climate Risk Perception Indices (CRPIs) to quantify the impact of investor climate change sentiment on industry return volatility in the Chinese stock market. There are several findings in this study including (1) the CRPIs effectively capture the trend of climate change in China over the past decade. (2) The investor’s attention to climate change positively influences short-term stock market returns, exhibiting seasonal characteristics and industry heterogeneity. (3) The attention serves as an information sender for stocks in Telecommunication, Oil & Petrochemicals, and Environmental Protection. (4) The total spillover effect among climate-sensitive industries is significantly higher during extreme climate events. These conclusions provide empirical evidence for the stock market to respond effectively to climate risks.