The spillover effect of mandatory renewable portfolio standards.

Renewable Portfolio Standards (RPSs) are one of the most prevalent and impactful clean energy policies implemented by states in the United States. This paper investigates the regional spillover effect of RPS policies using a directed dyad panel dataset of renewable electricity generation in US states from 1991 to 2021. Regional spillover effect is measured in two ways: by considering the influence of an RPS enacted in neighboring states and in states in the same regional transmission organization or independent system operator region. We use dyadic fixed effects estimation and conclude that the neighboring state's RPS stringency score is a strong determinant of a state's total renewable electricity generation. For states without an RPS, the positive influence of an RPS in a neighboring state is larger when the non-RPS state has more abundant renewable energy resources than the neighboring RPS state. Our findings suggest that past RPS policy evaluation research using a confined within-state focus may have underestimated the holistic impact of an RPS, as the impacts of an RPS policy can extend beyond the enacting state's borders. Overall, this study contributes to an improved understanding of the holistic impact of state RPS policies.

Pt Single Atoms Supported on Defect Ceria as an Active and Stable Dual-Site Catalyst for Alkaline Hydrogen Evolution.

This work evaluates the feasibility of alkaline hydrogen evolution reaction (HER) using Pt single-atoms (1.0 wt %) on defect-rich ceria (Pt1/CeOx) as an active and stable dual-site catalyst. The catalyst displayed a low overpotential and a small Tafel slope in an alkaline medium. Moreover, Pt1/CeOx presented a high mass activity and excellent durability, competing with those of the commercial Pt/C (20 wt %). In this picture, the defective CeOx is active for water adsorption and dissociation to create H* intermediates, providing the first site where the reaction occurs. The H* intermediate species then migrate to adsorb and react on the Pt2+ isolated atoms, the site where H2 is formed and released. DFT calculations were also performed to obtain mechanistic insight on the Pt1/CeOx catalyst for the HER. The results indicate a new possibility to improve the state-of-the-art alkaline HER catalysts via a combined effect of the O vacancies on the ceria support and Pt2+ single atoms.

Breaking the Pt Electron Symmetry and OH Spillover towards PtIr Active Center for Performance Modulation in Direct Ammonia Fuel Cell.

The growing interest in low-temperature direct ammonia fuel cells (DAFCs) arises from the utilization of a carbon-neutral ammonia source; however, DAFCs encounter significant electrode overpotentials due to the substantial energy barrier of the *NH2 to *NH dehydrogenation, compounded by the facile deactivation by *N on the Pt surface. In this work, a unique catalyst, Pt4Ir@AlOOH/NGr i.e., Pt4Ir/ANGr, is introduced composed of PtIr alloy nanoparticles controllably decorated on the pseudo-boehmite phase of AlOOH-supported nitrogen-doped reduced graphene (AlOOH/NGr) composite, synthesized via the polyol reduction method. The detailed studies on the structural and electronic properties of the catalyst by XAS and VB-XPS reveal the possible electronic modulations. The optimized Pt4Ir/ANGr composition exhibits a significantly improved onset potential and mass activity for AOR. The DFT study confirms the OHad species spillover by AlOOH and Pt4Ir (100) facilitates the conversion of the *NH2 to *NH with minimal energy barriers. Finally, testing of DAFC at the system level using a membrane electrode assembly (MEA) with Pt4Ir/ANGr as the anode catalyst, demonstrating the suitability of the catalyst for its practical applications. This study thus uncovers the potential of the Pt4Ir catalyst in synergy with ANGr, largely addressing the challenges in hydrogen transportation, storage, and safety within DAFCs.

Vibrational stability improvement of a mirror system using active mass damping.

Addressing the demand for high stability of beamline instruments at the SHINE facility, a high stability mirror regulating mechanism has been developed for mirror adjustments. Active mass damping was adopted to attenuate pitch angle vibrations of mirrors caused by structural vibrations. An internal absolute velocity feedback was used to reduce the negative impact of spillover effects and to improve performance. The experiment was conducted on a prototype structure of a mirror regulating mechanism, and results showed that the vibration RMS of the pitch angle was effectively attenuated from 47 nrad to 27 nrad above 1 Hz.

Overall, Direct, Spillover, and Composite Effects of Components of a Peer-Driven Intervention Package on Injection Risk Behavior Among People Who Inject Drugs in the HPTN 037 Study.

We sought to disentangle effects of the components of a peer-education intervention on self-reported injection risk behaviors among people who inject drugs (n = 560) in Philadelphia, US. We examined 226 egocentric groups/networks randomized to receive (or not) the intervention. Peer-education training consisted of two components delivered to the intervention network index individual only: (1) an initial training and (2) "booster" training sessions during 6- and 12-month follow up visits. In this secondary data analysis, using inverse-probability-weighted log-binomial mixed effects models, we estimated the effects of the components of the network-level peer-education intervention upon subsequent risk behaviors. This included contrasting outcome rates if a participant is a network member [non-index] under the network exposure versus under the network control condition (i.e., spillover effects). We found that compared to control networks, among intervention networks, the overall rates of injection risk behaviors were lower in both those recently exposed (i.e., at the prior visit) to a booster (rate ratio [95% confidence interval]: 0.61 [0.46-0.82]) and those not recently exposed to it (0.81 [0.67-0.98]). Only the boosters had statistically significant spillover effects (e.g., 0.59 [0.41-0.86] for recent exposure). Thus, both intervention components reduced injection risk behaviors with evidence of spillover effects for the boosters. Spillover should be assessed for an intervention that has an observable behavioral measure. Efforts to fully understand the impact of peer education should include routine evaluation of spillover effects. To maximize impact, boosters can be provided along with strategies to recruit especially committed peer educators and to increase attendance at trainings. Clinical Trials Registration Clinicaltrials.gov NCT00038688 June 5, 2002.

RESUMEN: Intentamos desenmarañar los efectos de los componentes de una intervención de educación entre pares sobre los comportamientos de inyección de riesgo autorreportados entre personas que se inyectan drogas (n = 560; 226 grupos/redes egocéntricos(as)) aleatorizados(as) a recibir (o no) la intervención en Filadelfia, EUA. Dos componentes fueron administrados a índices de redes de intervención: una capacitación inicial y sesiones de "refuerzo" durante visitas de seguimiento. Usando modelos log-binomial de efectos mixtos ponderados por probabilidad inversa, estimamos los efectos de dichos componentes sobre los comportamientos de riesgo posteriores. Encontramos que en comparación con las redes control, en las redes de intervención, las tasas generales de comportamientos de inyección de riesgo fueron más bajas en ambas aquellas expuestas recientemente a un refuerzo (razón de tasas [intervalo de confianza del 95%]: 0.61 [0.46­0.82]) y aquellas no expuestas recientemente (0.81 [0.67­0.98]). Solamente los refuerzos tuvieron efectos derrame (i.e., contraste de las tasas de resultados si es miembro [no índice] de una red en una red con exposición reciente versus bajo la condición control) significativos (p. ej., 0.59 [0.41­0.86] para la exposición reciente).

Ag modified ZnO nanoflower gas sensitive sensor for selective detection of n-butanol.

Ag modified ZnO nanoflowers were successfully prepared by sunlight induced solvent reduction method. The samples were characterized by x-ray diffractometer, field emission scanning electron microscope, transmission electron microscope and energy dispersive x-ray spectrum, and the results confirmed the presence of Ag nanoparticles on the ZnO nanoflower. The gas sensing performance of the materials was studied at different operating temperatures and different n-butanol concentrations. The results showed that the Ag modified ZnO nanoflower sensor responded to 50 ppm n-butanol up to 147.17 at 280 °C, and the Ag modified ZnO nanoflower sensor exhibited excellent repeatability, stability and response recovery time. In addition, different target gases were employed for the selectivity study of the Ag modified ZnO nanoflower. It can be found that the Ag modified ZnO nanoflower had good selectivity for n-butanol. The improved response of the Ag modified ZnO nanoflower sensor was attributed to the catalytic effect of Ag nanoparticles. The results indicate that the Ag modified ZnO nanoflower will become a very promising sensing material for n-butanol gas detection.

Efficacy of a cognitive training based on inhibitory spillover and attribute conditioning: No weight and food intake reductions in adults with overweight and obesity.

BACKGROUND: Overeating and obesity have been linked to deficient self-control and recent evidence suggests that the inhibitory spillover effect (ISE) may be an effective means to improve self-control. Specifically, it was shown that the ISE increases self-control by transfer of self-control capacity from one domain to another unrelated domain. Against this backdrop, our aim was to reduce hedonic food intake and body weight in non-dieting participants with overweight and obesity by transferring inhibitory control abilities from a food-unrelated domain to the food domain by means of an attribute conditioning procedure in a novel cognitive training (vs. a placebo training) comprising 8-sessions delivered over four weeks. METHOD: In total, 93 adults with overweight and obesity were included in a two-arm randomized controlled trial and assigned to the computerized cognitive training or a placebo training (active control condition). Food intake in a bogus taste test and body weight were assessed prior to and after the training. Weight was additionally assessed at 3-months follow-up. RESULTS: There was no improvement in food intake and weight reduction. DISCUSSION: The cognitive training based on the ISE and attribute conditioning (ISAC) is not yet ready for application. Future studies need to identify the factors critical for a successful implementation of conditioning procedures aiming to associate food stimuli with self-control in overweight and obesity.

Comparing the EU and Chinese carbon trading market operations and their spillover effects.

A carbon trading market (CTM) policy for trading carbon dioxide emission rights as a commodity was created to reduce greenhouse gas emissions. CTMs operate differently in different countries and regions, and their interactions deserve an in-depth study. This study focused on the world's largest CTM, the European Union (EU), and the CTM of China, largest carbon-emitting country. First, we evaluate the liquidity and volatility of the two CTMs. Subsequently, the VAR model is used to explore the mean spillover effect between the two markets and the BEKK-GARCH model is used to explore the volatility spillover effect between the two markets. The study concludes that: (1) The liquidity of China's CTM is better than that of the EU's CTM. (2) Both the EU and Chinese CTMs are unstable, but the volatility of the Chinese CTM is lower than that of the EU CTM. (3) Price changes in the EU and Hubei CTMs have a mutual influence. (4) There are interactions between the market fluctuations of the EU CTM and the Shanghai CTM and those of the EU CTM and the Hubei CTM. The results of this study have implications for the construction and development of CTMs in the EU and China.

How does the issuance of green bonds impact stock price crash risk: An analysis utilizing the NCSKEW and DUVOL.

China's rapid development in the context of carbon neutrality has positioned it as the global leader in green bond issuance. As the Chinese A-share market continues to slump, adverse shocks are accumulating. Thus, the question arises: How will the issuance of green bonds (GB) impact stock price crash risk (SPCR)? The present study utilizes datasets of Chinese A-share listed firms from 2012 to 2022 and conducts a differences-in-difference analysis to address this inquiry. The findings indicate that issuing GB can significantly reduce SPCR, suggesting that GB plays a stabilizing role in the capital market. This effect remains robust after consideration of parallel trend testing, placebo tests, propensity score matching, replacement of explained variables, and controlling for geographic and industrial factors. The mechanism studies demonstrate that the issuance of GB can effectively alleviate financing constraints faced by companies and reduce SPCR through the financing constraints mechanism. The issuance can also enhance firm exposure and attract investor attention, thereby mitigating SPCR through the investor attention mechanism. The issuance contributes to the formation of a positive reputation image among investors and can diminish SPCR through the investor sentiment mechanism. The heterogeneity analyses show that the depressive effect of issuing GB on SPCR is more pronounced in state-owned enterprises, heavily polluting industries, and regions with a higher degree of marketization. Further discussion suggests that given the influence of externalities, the green signals released when a firm issues GB can spread within the capital market, generating a positive spillover effect on the decrease in SPCR of other firms in the same region and a negative spillover effect on the increase in SPCR of other firms in the same industry. This study not only confirms GB's stabilization role in the capital market, but also offers theoretical insights for improving the institutional design of the green bond market and promoting sustainable green development.

The impact of digital inclusive finance on the collaborative reduction of pollutant and carbon emissions: spatial spillover and mechanism analysis.

In light of the escalating global climate risks threatening human survival, there is a global consensus on the necessity for collaborative reduction of pollutant and carbon emissions (CRPC). Within this context, digital inclusive finance (DIF) is recognized for its unique inclusiveness and digital characteristics as a critical factor in promoting environmentally friendly and sustainable development. DIF provides advantageous channels for environmental governance, thereby making the achievement of CRPC objectives feasible. However, the impact of DIF on CRPC has not been fully explored. This study employs a spatial econometric model to investigate the impact of DIF on CRPC in 278 prefecture-level cities in China from 2011 to 2020. The findings indicate that DIF has a positive impact on CRPC, with significant spatial spillover effects. The analysis highlights the pivotal mediating roles played by technology effect and electrified effect of the energy mix, while environmental regulation effect plays a moderating role. Notably, disparities in the impact of DIF on CRPC are evident, particularly in non-resource-based cities, cities with low carbon intensity, and eastern regions where spatial spillover effects are more pronounced. These experiences enrich the relevant thesis in terms of DIF on CRPC, providing a theoretical basis for formulating CRPC schemes.

Spatiotemporal drivers of agricultural non-point source pollution: A case study of the Huang-Huai-Hai Plain, China.

Agricultural non-point source pollution (ANPSP) poses a severe threat to ecological environments, especially in China's major grain-producing regions. Despite the increasing attention, existing studies often overlook the spatial heterogeneity and driving mechanisms of ANPSP within different functional regions. This study addresses this research gap by constructing a bottom-up regional inventory of ANPSP for the Huang-Huai-Hai Plain (HHHP) and applying the Logarithmic Mean Divisia Index (LMDI) decomposition method to analyse the spatio-temporal patterns of ANPSP from 2000 to 2020. Spatial econometric models were further applied to examine the spatial spillover effects of driving factors from the perspective of Major Function-oriented Zoning (MFZ). The results show that while ANPSP emissions in the HHHP have generally increased over the past two decades, a slight decrease has been observed since 2015. Grain yield capacity and cropping intensity were identified as the primary drivers of ANPSP growth, particularly in urbanised zones (UZs) and main agricultural production zones (MAPZs). The study also highlights significant spatial heterogeneity in the impact of driving factors on ANPSP across different MFZs, with marked differences in both the direct and spatial spillover effects of these factors. This underlines the need for differentiated environmental protection policies tailored to the functions and characteristics of each region. By integrating the LMDI decomposition method with spatial econometric models, this study offers a new framework for understanding the ANPSP dynamics within the context of MFZs, providing policymakers with valuable insights for designing effective, regionally coordinated governance strategies.

Promoting sustainable development: Revisiting digital economy agglomeration and inclusive green growth through two-tier stochastic frontier model.

In the global wave of digitization, digital economic agglomeration, as an emerging model, profoundly impacts the economy, environment, and society. Countries worldwide are formulating strategies and policies to promote the development of digital economic agglomeration, yet they also face challenges of widening digital divide and environmental sustainability. Existing research primarily focuses on the positive effects of the digital economy, with limited assessment of the dual effects of digital economic agglomeration on sustainable development. This study utilizes panel data from 282 Chinese cities between 2011 and 2021, employing a two-tier stochastic frontier model. It reexamines the dual impacts and intrinsic mechanisms of digital economic agglomeration, attempting to capture regional and temporal variations in the dual effects to address this research gap. The study shows that: (1) The positive effect of digital economy agglomeration is much more than the negative effect, resulting in a positive net effect that shows an overall increasing trend with significant regional disparities. (2) Digital economic agglomeration has a significant negative spatial spillover effect, promoting local inclusive green growth while inhibiting inclusive green growth in neighboring cities. (3) Regarding the mediating mechanisms, industrial structure, technological innovation and resource allocation efficiency have positive indirect effects on inclusive green growth, while environmental regulation intensity has a negative indirect effect, and it has a nonlinear effect under the threshold constraint of the mediating mechanisms. This study provides policy insights for promoting inclusive green growth, emphasizing the need to consider regional differences in resource distribution, ecological environment, and social demands. It advocates for the organic integration of the digital economy across different regions, reducing polarization effects, and enhancing diffusion effects.

Fostering inclusive green growth in China: Identifying the impact of the regional integration strategy of Yangtze River Economic Belt.

Inclusive green growth has garnered significant attention from governments and international organizations worldwide. Utilizing data from 282 cities in China spanning from 2010 to 2020, this study employs the dual machine learning model and the chain mediated effect model to delve into the effects and internal mechanisms of the regional integration of Yangtze River Economic Belt on inclusive green growth. Our findings indicate that the regional integration of Yangtze River Economic Belt has a substantial influence on inclusive green growth, particularly in cities with a higher degree of marketization, non-industrial cities, and cities lacking natural resource advantages. Mechanistic analysis reveals that the regional integration of Yangtze River Economic Belt exerts its influence on inclusive green growth through three parallel development paths including enhancing urban innovation levels, fostering mass entrepreneurship, and promoting the advancement of digital financial inclusion. Furthermore, the chain mediated effect is supported. Additionally, the spatial spillover effect of target policy is observed. These findings offer empirical evidence regarding the impact of the regional integration of Yangtze River Economic Belt on inclusive green growth, and provide valuable insights for optimizing and enhancing inclusive green growth strategies in China and other emerging economies.

The Impact of Renewable Energy Development on Regional Carbon Emission Reduction: Based on the Spatio-Temporal Analysis of 30 Provinces in China.

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.

WO3 -Assisted Synergetic Effect Catalyzes Efficient and CO-Tolerant Hydrogen Oxidation for PEMFCs.

Developing anode catalysts with substantially enhanced activity for hydrogen oxidation reaction (HOR) and CO tolerance performance is of great importance for the commercial applications of proton exchange membrane fuel cells (PEMFCs). Herein, an excellent CO-tolerant catalyst (Pd-WO3 /C) has been fabricated by loading Pd nanoparticles on WO3 via an immersion-reduction route. A remarkably high power density of 1.33 W cm-2 at 80 °C is obtained by using the optimized 3Pd-WO3 /C as the anode catalyst of PEMFCs, and the moderately reduced power density (73% remained) in CO/H2 mixed gas can quickly recover after removal of CO-contamination from hydrogen fuel, which is not possible by using Pt/C or Pd/C as anode catalyst. The prominent HOR activity of 3Pd-WO3 /C is attributed to the optimized interfacial electron interaction, in which the activated H* adsorbed on Pd species can be effectively transferred to WO3 species through hydrogen spillover effect and then oxidized through the H species insert/output effect during the formation of Hx WO3 in acid electrolyte. More importantly, a novel synergetic catalytic mechanism about excellent CO tolerance is proposed, in which Pd and WO3 respectively absorbs/activates CO and H2 O, thus achieving the CO electrooxidation and re-exposure of Pd active sites for CO-tolerant HOR.

Assessing intervention effects in a randomized trial within a social network.

Studies of social networks provide unique opportunities to assess the causal effects of interventions that may impact more of the population than just those intervened on directly. Such effects are sometimes called peer or spillover effects, and may exist in the presence of interference, that is, when one individual's treatment affects another individual's outcome. Randomization-based inference (RI) methods provide a theoretical basis for causal inference in randomized studies, even in the presence of interference. In this article, we consider RI of the intervention effect in the eX-FLU trial, a randomized study designed to assess the effect of a social distancing intervention on influenza-like-illness transmission in a connected network of college students. The approach considered enables inference about the effect of the social distancing intervention on the per-contact probability of influenza-like-illness transmission in the observed network. The methods allow for interference between connected individuals and for heterogeneous treatment effects. The proposed methods are evaluated empirically via simulation studies, and then applied to data from the eX-FLU trial.

Impact of a diabetes pay-for-performance program on nonincentivized mental disorders: a panel study based on claims database analysis.

BACKGROUND: Diabetes is one of the most prevalent chronic diseases with subsequent complications. The positive effects of diabetes pay-for-performance (P4P) programs on treatment outcomes have been reported. The program provides financial incentives based on physiological care indicators, but common mental disorder complications such as depression are not covered. METHODS: This study employed a natural experimental design to examine the spillover effects of diabetes P4P program on patients with nonincentivized depressive symptoms. The intervention group consisted of diabetes patients enrolled in the DM P4P program from 2010 to 2015. Unenrolled patients were selected by propensity score matching to form the comparison group. Difference-in-differences analyses were conducted to evaluate the effects of P4P programs. We employed generalized estimating equation (GEE) models, difference-in-differences analyses and difference-in-difference-in-differences analyses to evaluate the net effect of diabetes P4P programs. Changes in medical expenses (outpatient and total health care costs) over time were analysed for the treatment and comparison groups. RESULTS: The results showed that enrolled patients had a higher incidence of depressive symptoms than unenrolled patients. The outpatient and total care expenses of diabetes patients with depressive symptoms were lower in the intervention group than in the comparison group. Diabetes patients with depressive symptoms enrolled in the DM P4P program had lower expenses for depression-related care than those not enrolled in the program. CONCLUSIONS: The DM P4P program benefits diabetes patients by screening for depressive symptoms and lowering accompanying health care expenses. These positive spillover effects may be an important aspect of physical and mental health in patients with chronic disease enrolled in disease management programs while contributing to the control of health care expenses for chronic diseases.

Measuring the cross-border spillover effects and telecoupling processes of ecosystem services in Western China.

Ecosystem services provide the basic elements for global economic development. In the context of the deepening global integration process, countries and regions are increasingly connected, resulting in a series of cross-country, cross-regional, multi-scale socio-economic-environmental impacts, these new situations and changes require a multi-site, two-way, and cross-temporal and spatial scale comprehensive study of "the relationship between ecosystem services and humans". Based on this, we apply a telecoupling synthesis framework to explore the socio-economic and eco-environmental interactions of ecosystem service spillover effects. Results show that (1) the spillover effect of ecosystem services in western China is significant. More than 66% of ecosystem services spillover to eastern China provinces, and more than 40% of ecosystem services spillover to countries in Southeast Asia, South Asia, and Central Asia, resulting in a total of 679 million people benefiting from the spillover effect. (2) There are also multiple telecoupling processes between the ecosystem service spillovers in the ecologically fragile areas in western China and the rest of the world. In combination with the scenario simulation of the InVEST model, the services such as water supply, soil retention, flood mitigation, and food supply have significant impacts on sustainable development and human well-being in Asia and even the world. (3) The positive feedback effect of telecoupling is critical to the protection of the ecological environment as well as the improvement of people's livelihood and well-being in Western China's ecologically fragile areas. Therefore, we propose strengthening ecological compensation cooperation between local governments and implementing compensatory transfer payments between upstream and downstream. Simultaneously, international cooperation must be strengthened, and an ecological compensation transfer mechanism with beneficiary countries must be established, while the cross-regional flow of ecosystem services must be maintained. This study provides an example for the "ecosystem services and human relations" in multiple places, two directions and across time and space scales, and also practical reference significance for China implementation of projects such as the "the Belt and Road" initiative and transnational and cross regional resource allocation.

Can urban land market reform mitigate industrial emissions? Environmental evidence from 257 prefecture-level cities in China.

In the period of planned economy, China used low-cost land investment to drive economic development for a long time, which brought problems such as low efficient use of natural resources and environmental pollution. Under the dual pressure of economic development and environmental protection, Chinese government has begun to implement the urban land market reform, hoping to gradually change the extensive economic development model with high input and low output through the market mechanism. In order to investigate whether the urban land market reform can reduce industrial emissions and promote the transformation of socioeconomic, this paper constructs industrial land transactions and socioeconomic panel data of 257 prefecture-level cities in China from 2007 to 2020. The research results show that (1) The urban land market reform has reduced industrial emissions through changing the behavior of local governments in fiscal decentralization and the behavior of industrial enterprises. (2) The regional competition and cooperation brought by urban land market reform have regional heterogeneity in the emission reduction effect of industrial emissions. (3) The emission reduction effect of urban land market reform has a spatial spillover effect, which not only affects the local area, but also affects neighboring cities. We suggest that Chinese government needs to continue to carry out ULMR and increase scientific investment and technological innovation, promote the transformation of the industrial economy, and promote healthy competition among local governments. The findings not only provide valuable insights for the future reform of China's market economy, but also provide practical reference for social changes for other countries in the transition period of the world.

Spatial spillover impact of determinants on child mortality in Pakistan: evidence from Spatial Durbin Model.

BACKGROUND: Child mortality is a major challenge to public health in Pakistan and other developing countries. Reduction of the child mortality rate would improve public health and enhance human well-being and prosperity. This study recognizes the spatial clusters of child mortality across districts of Pakistan and identifies the direct and spatial spillover effects of determinants on the Child Mortality Rate (CMR). METHOD: Data of the multiple indicators cluster survey (MICS) conducted by the United Nations International Children's Emergency Fund (UNICEF) was used to study the CMR. We used spatial univariate autocorrelation to test the spatial dependence between contiguous districts concerning CMR. We also applied the Spatial Durbin Model (SDM) to measure the spatial spillover effects of factors on CMR. RESULTS: The study results showed 31% significant spatial association across the districts and identified a cluster of hot spots characterized by the high-high CMR in the districts of Punjab province. The empirical analysis of the SDM confirmed that the direct and spatial spillover effect of the poorest wealth quintile and MPI vulnerability on CMR is positive whereas access to postnatal care to the newly born child and improved drinking water has negatively (directly and indirectly) determined the CMR in Pakistan. CONCLUSION: The instant results concluded that spatial dependence and significant spatial spillover effects concerning CMR exist across districts. Prioritization of the hot spot districts characterized by higher CMR can significantly reduce the CMR with improvement in financial statuses of households from the poorest quintile and MPI vulnerability as well as improvement in accessibility to postnatal care services and safe drinking water.