Explore the vast range of titles available.

How large economic stimuli generate individual and aggregate responses is a central question in economics, but has not been studied experimentally. We provided one-time cash transfers of about USD 1000 to over 10,500 poor households across 653 randomized villages in rural Kenya. The implied fiscal shock was over 15 percent of local GDP. We find large impacts on consumption and assets for recipients. Importantly, we document large positive spillovers on non-recipient households and firms, and minimal price inflation. We estimate a local transfer multiplier of 2.5. We interpret welfare implications through the lens of a simple household optimization framework.

This paper investigates the presence and extent of missing links that prevent the transmission and condition the flow of knowledge spillover effects (KSE) across space and time. Findings using a comprehensive database composed of 9242 innovative startups from Italy covering the period 2008–2018 and all 20 geographic regions as well as all economic sectors at the 2-digit level of aggregation indicate that missing links related to observed differences in industry structures and availability of pools of skilled human capital amount for large and persistent differences in terms of firm intensity differential across neighboring regions. More specifically, we observe that regions with initial existent high firm intensity are more likely to continue enhancing their labor pools by both endogenously increasing high-skilled human capital and by attracting high-skilled human capital from neighboring regions. Intra- and inter-industry spillovers are marked by high levels of heterogeneity. Consequently, we find that missing links related to KSE create directional effects, and these effects are neither symmetric nor reciprocal in adjacent geographical regions. Invisible barriers to KSE transmission, imposed by the presence of missing links, prevent the work of the invisible hand.Plain English SummaryThe main result of this research is that the evidence using a large sample of Innovative Startups in Italy conclusively indicates that missing links of knowledge spillover effects account for a large proportion of the observed differences in new firm formation and entrepreneurial development. The presence of missing links in the transmission of knowledge spillovers appears to be a relevant element when explaining observed differences across time and space. Efforts to counter the presence of missing links of knowledge, namely, investment in human capital formation, and the development of institutional policy changes, appear to yield mixed results. On the one hand, entrepreneurial activity is fostered, but in a non-homogenous fashion across the entire country.Thus, the principal implication of this study is that in order for policy changes directed to promote economic growth and development via entrepreneurial activity, they need to account for the presence of missing links in the transmission of knowledge spillover effects across sectors of economic activity and across geographic regions given the large presence of heterogeneity across sectors and regions.

Air pollution is an important factor affecting the quality and sustainability of the development of China’s economy, and urban sprawl is also a typical by-product of the non-intensive development of urban land. At the same time, Chinese-style fiscal decentralization promotes urban sprawl through top-down yardstick competition, which has a serious impact on air pollution. Therefore, exploring the effect of fiscal decentralization and urban sprawl on air pollution is of great significance for regulating local government behavior, curbing urban sprawl, and accurately identifying the causes of air pollution. The dynamic spatial Durbin model with economic geography weight matrix is employed to analyze the direct and moderating effects of fiscal decentralization and urban sprawl on air pollution on the basis of 269 prefecture-level cities in China from 2004 to 2018. The results show that air pollution has a significant retarded time effect and space spillover effect. Both fiscal decentralization and urban sprawl have contributed significantly to air pollution. The moderating effect of urban sprawl and fiscal decentralization on air pollution is significantly positive. From the short-term effects, the coefficients of the total spillover effect, direct spillover effect, and indirect spillover effect of urban sprawl and fiscal decentralization on air pollution are significantly positive, respectively. In terms of long-term effects, the total spatial spillover effect of urban sprawl and fiscal decentralization on air pollution is significantly negative, while the direct and indirect effects of those are negative but not significant. Further research finds that there is significant regional heterogeneity in the influence of urban sprawl and fiscal decentralization on air pollution.

Many platform strategies focus on indirect network effects between sellers through platform expansion. In this paper, we show sellers on the console video game platform generate a positive intertemporal spillover effect and expand the demand for other sellers, holding the set of platform adopters fixed. We propose a novel identification strategy that leverages exogenous variation in the release timing of games exclusively available on a console platform, and examine how this variation affects the sales of games available on both platforms. We find a sizable intertemporal demand spillover effect between games: A 1% increase in total copies sold on a platform leads to a 0.153% increase in the sales of other games in the next month (i.e., an elasticity of 0.153). Additional analysis suggests this demand spillover effect is reminiscent of habit formation on the consumer side, in that past purchases keep end users active on the platform. Our finding provides a potential explanation for recent platform sales events and subscription services that provide free games to consumers every month. This paper was accepted by Eric Anderson, marketing .

By employing time–frequency-domain frameworks, this study analyzes the spillover effects of news-based economic uncertainty caused by the pandemic on three renewable energy stock indices in the USA, Europe, and the world. The empirical results reveal that the total spillover from economic uncertainty to the three renewable energy stock returns was concentrated at a high frequency, whereas those to volatilities appeared at low frequencies. Utilizing a rolling-window method, we observed that the impact of uncertainty caused by COVID-19 on three renewable energy stock returns and volatilities is more significant than that resulting from the global financial crisis (GFC). During COVID-19, the majority of the spillover effects from economic uncertainty to returns and volatilities of the three indices focused on the long term.

The digital economy has emerged as a new trend in economic development and has profoundly influenced the process of achieving common prosperity. However, current research on the correlation between the digital economy and common prosperity from the perspective of a river basin still needs to be strengthened. Based on this, the present study first theoretically elaborates the conceptual meanings of “digital economy” and “common prosperity”, as well as the mechanism by which the digital economy empowers common prosperity. Subsequently, a scientifically-constructed performance evaluation index system for the digital economy and common prosperity is established. Considering the Yellow River Basin as an empirical case study area, this study investigates the mechanism and spatial spillover effects of the digital economy in empowering common prosperity from 2005 to 2020. The research findings reveal that: (1) The Yellow River Basin exhibits a basin characteristic with downstream > midstream > upstream areas regarding the level of common prosperity and digital economy. It indicates that a distinct spatial correlation exists between the two factors. However, the ongoing decrease in both high-level and very high-level areas reflects the lengthy and challenging journey of enhancing the quality and efficiency of the digital economy in empowering common prosperity. (2) The digital economy not only directly impacts common prosperity, but also fosters its development through spatial spillover effects. Among the control factors, informatization and housing levels have a major stimulating effect. (3) There exists a clear regional heterogeneity in how the digital economy affects common prosperity in the Yellow River Basin. Specifically, common prosperity of downstream cities is significantly impacted by the digital economy. The spatial spillover effects of the digital economy on common prosperity exhibit a pronounced “neighborhood as a moat” characteristic. (4) The digital economy facilitates the achievement of shared prosperity through the implementation of mechanisms centered on sharing, affluence, and sustainability. These research findings illuminate the empowering mechanisms and spatial spillover pathways of the digital economy in promoting shared prosperity, aligning with national strategies for ecological conservation and high-quality development in the Yellow River Basin.

Based on the perspective of government-dominated and market-driven industrial co-agglomeration mode, the effect of producer services and manufacturing industrial co-agglomeration on the ecological environment pollution control is explored by using spatial Durbin model, and the mediating effect of technological innovation is further tested. The results show that: (1) At the national level, the government-dominated industrial co-agglomeration only significantly promotes the local ecological environment pollution control, while the market-driven industrial co-agglomeration also can promote the ecological environment pollution control in the surrounding region through its spatial spillover effect. Moreover, there is a significant inverted “U-shaped” curve relationship between the economic development level and ecological environment pollution. Additionally, the environment regulation is also conducive to promoting the ecological environment pollution control, while the industrial structure and foreign direct investment will lead to more serious ecological environment pollution; (2) In the east region, the government-dominated and market-driven industrial co-agglomeration can promote the ecological environment pollution control in the local and surrounding regions, and the promotion effect and spatial spillover effect of market-driven industrial co-agglomeration are greater. However, in the central and west regions, the government-dominated industrial co-agglomeration and market-driven industrial co-agglomeration only promote the local ecological environment pollution control. (3) Technological innovation has partial mediating effect in the impact of government-dominated and market-driven industrial co-agglomeration on the ecological environment pollution control, namely that the government-dominated and market-driven industrial co-agglomeration not only can directly promote the ecological environment pollution control, but also can indirectly promote the ecological environment pollution control through the mediating effect of technological innovation.

The development of renewable energy has become an important means for the world to cope with climate change, ensure energy security, and protect the ecological environment. Using the panel data of 30 provinces in China from 2013 to 2021, this study used the mediating effect model and the spatial Durbin model (SDM) to explore the mechanism and spatial effects of renewable energy development on China’s regional carbon emission reduction. The results show that: (1) Renewable energy development can help to reduce carbon emission intensity. (2) The results of mechanism analysis show that renewable energy development reduces carbon intensity by improving energy structure, promoting industrial structure optimization, and industrial structure upgrading. (3) The development of renewable energy can not only reduce the local carbon intensity but also have a positive spillover effect on the carbon intensity of neighboring regions. (4) Further analysis shows that the long-term effect of renewable energy development on carbon emissions is greater than the short-term effect. At the same time, the heterogeneity analysis shows that compared with the Yellow River basin, the development of renewable energy has a significant carbon emission reduction effect in the Yangtze River Economic Belt region. Energy-rich areas fall into the “resource curse”, which makes the carbon emission reduction effect of renewable energy development not significant. This paper has certain reference significance for promoting reasonable decomposition between regions and formulating renewable energy development policies.

IntroductionAs China advances its dual carbon targets, the carbon market has become a key policy instrument. However, climate policy uncertainty (CPU) can disrupt expectations and amplify risks in carbon trading prices (CTP), creating challenges for market stability and policy effectiveness.MethodsTo address this issue, this study constructs a weekly China-specific CPU (CCPU) index using text analysis of domestic newspapers and employs the Quantile Vector Autoregression–Diebold-Yilmaz (QVAR-DY) framework to assess its spillover effects on returns and volatility across six regional carbon markets. The quantile Granger-causality test is also applied to further validate the direction and significance of spillovers under different market conditions.ResultsThe analysis shows that spillovers remain moderate under normal conditions but intensify considerably under extreme states, particularly at higher quantiles, as confirmed by the quantile Granger-causality tests. The most striking finding is that spillovers from CCPU to volatility are consistently stronger than to returns, indicating that systemic risk contagion is more pronounced through volatility channels.DiscussionBy integrating a quantile perspective with dynamic spillover analysis, this study reveals the asymmetric transmission of policy uncertainty in China’s carbon markets and provides new insights for risk monitoring and policy design in the low-carbon transition.

Purpose This study aims to examine the spillover effects of the mean and volatility between oil prices and stock indices of six Gulf Cooperation Council (GCC) countries (UAE, Kuwait, Saudi Arabia, Qatar, Oman and Bahrain). Design/methodology/approach Over the period 2008–2019, a bivariate VARMA-GARCH-ADCC model was combined with the maximal overlap discrete wavelet transform technique filter to shed light on a wide range of possible spillover effects in the mean and variances of level prices at various time horizons. Findings The authors find that the spillover effects between oil prices and the GCC stock markets are time-varying and spread across various time horizons. Besides, oil prices and stock market indices are directly impacted by their own shocks and variations and indirectly influenced by other price volatilities and wavelet scales. The linkages in volatility spillovers between oil prices and the GCC stock markets occur in the short-term, midterm and long-term horizons. More specifically, the results also show that the asymmetric estimates are statistically significant for the associations between oil prices and each stock market in the GCC countries. This implies that negative shocks play a more vital role than positive shocks in driving the dynamic condition correlations between oil and stock markets under study. Practical implications The significant interrelatedness between oil prices and each stock market in the GCC countries has important implications for investors, portfolio managers, and other market participants. They can use the findings of this research to create the best oil-GCC stock portfolios and predict more precisely the volatility spillover patterns in constructing their hedging strategies. Originality/value In several ways, this study differs from previous research. First, while previous empirical studies of the dynamic link between oil prices and stock markets have focused primarily on developed or emerging markets, the focus of this is on six GCC countries. Second, the linkage between oil prices and stock markets is typically studied at the original data level in the time domain in relevant literature, while frequency information is overlooked. Therefore, the current study examines this relationship from a multiscale perspective. Third, in this paper, to capture a wide range of possible spillover effects in the mean and variance of level prices at multiple wavelet scales, the authors use a VARMA-GARCH-ADCC model in conjunction with wavelet multiresolution analysis. Additionally, this article also applies wavelet hedge ratio and wavelet hedge portfolio analysis at various time horizons.