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This study proposes a heterogeneous mediation analysis for survival data that accommodates multiple mediators and sparsity of the predictors. We introduce a joint modeling approach that links the mediation regression and proportional hazards models through Bayesian additive regression trees with shared typologies. The shared tree component is motivated by the fact that confounders and effect modifiers on the causal pathways linked by different mediators often overlap. A sparsity‐inducing prior is incorporated to capture the most relevant confounders and effect modifiers on different causal pathways. The individual‐specific interventional direct and indirect effects are derived on the scale of the logarithm of hazards and survival function. A Bayesian approach with an efficient Markov chain Monte Carlo algorithm is developed to estimate the conditional interventional effects through the Monte Carlo implementation of the mediation formula. Simulation studies are conducted to verify the empirical performance of the proposed method. An application to the ACTG175 study further demonstrates the method's utility in causal discovery and heterogeneity quantification. [ABSTRACT FROM AUTHOR]

As an important means of regulating pollution emissions, environmental regulation is crucial for reducing urban PM2.5. However, previous studies have mainly focused on the emission reduction effect of formal environmental regulations and neglected the role played by informal environmental regulations represented by environmental information disclosure. We employed a multiperiod difference-in-differences (DID) model to assess the effectiveness of EID policies in mitigating PM2.5 emissions and to investigate their abatement mechanism by focusing on green innovation and industrial structure. The findings indicate that the implementation of EID policies significantly reduces PM2.5 emissions. Mechanism tests reveal that EID promotes PM2.5 reductions by fostering green innovation and upgrading industrial structure. In addition, the impact of EID policy is more marked in resource-based cities and those located in interior regions. This study contributes to the reduction in urban haze emissions in China, offering empirical evidence and policy recommendations for the further implementation of environmental information disclosure. [ABSTRACT FROM AUTHOR]

Based on unique firm-level microdata, this study adopts the conditional logit model to empirically evaluate the impact of the environmental tax on the siting of foreign-invested manufacturing enterprises. We also explore the trade-offs of the environmental tax by assessing its economic costs and benefits. This study finds that the environmental tax has a statistically significant and negative impact on the siting of foreign-invested enterprises, as verified by a series of robustness checks. This result implies a trade-off of the environmental tax, reducing pollutant emissions at the expense of damaging economic growth. Heterogeneous analysis finds that the siting is remarkably more sensitive for foreign-invested enterprises that are sole-venture, in high-polluting industries, small-scale, or hosted by developing countries. The other trade-off is outlined: although the environmental tax reduces the number of newly registered foreign-invested enterprises, it brings some economic benefits by making the structure of foreign investment cleaner and more advanced. [ABSTRACT FROM AUTHOR]

Most existing studies have often ignored the fact that the impact of natural disasters on households may vary according to their dependence on agriculture. Moreover, no study has examined how natural disasters affect food consumption and cause economic damage and, more importantly, whether this effect varies across households. This study aims to explore the influence of natural disasters on the likelihood of households migrating, on their food consumption, remittances, and economic damage. In particular, the study analyzes whether the effect differs among rural households according to their dependence on agriculture. Assembled from three surveys in 2012, 2014, and 2016, we use a unique balanced panel dataset of 1929 households to investigate the influence of natural disasters on migration and household well-being in rural Vietnam. To account for unobservable time-invariant factors that may affect both migration and household well-being, we adopt a fixed-effect estimator. Analyzing a year of natural disasters, we discovered that these do, in fact, cause rural household migration. Further investigation reveals a heterogeneous effect. While natural disasters increase the probability of migration for those with average dependence on agriculture, this is not the case for those with low or high dependence. Natural shocks, however, have an increasing effect on remittances for the former group but not for the latter. Natural shocks cause economic damage for those who are moderately or heavily dependent on agriculture, but not for those who are less reliant on it. In addition, it was found that such shocks reduce the food consumption of those who are heavily reliant on agriculture. The findings imply that migrating may be an effective coping strategy for households with a moderate reliance on agriculture. In light of the finding that households with high reliance have a higher risk of falling into poverty after natural disasters, our study suggests that supportive policies should be prioritized for this vulnerable group. Also, a number of households in this group may face obstacles to migrating. Local government policies supporting their migration should be efficiently implemented, especially for those living in regions prone to natural disasters. [ABSTRACT FROM AUTHOR]

Due to the effects of global warming, the vapor pressure deficit (VPD) will inevitably and continuously rise in future, which is a fact that must be faced when discussing the sustainable development of vegetation ecosystems. Understanding the response of vegetation to changes in the atmospheric moisture state is necessary for minimizing the adverse effects of climate change. Using the leaf area index (LAI) and meteorological data in the Yellow River Basin collected over nearly 40 years, we explore the spatiotemporal variations in VPD and vegetation within the growing season and the differences in the effects of VPD on vegetation in different climatic zones. The results show the following: (1) both VPD and LAI in the Yellow River Basin show an increasing trend, in which VPD increases radially outward centered on the arid regions, while the vegetation develops favorably over almost the whole basin; (2) at the whole-basin scale, the area of VPD positively correlated with vegetation growth is greater than the area of negative correlation, and this overall trend is increasing significantly; (3) the VPD exerts heterogeneous effects on different vegetation in different climatic zones, and these heterogeneity findings suggest that the effects of VPD on vegetation are more influenced by differences among the climatic zones of the vegetation than by differences in the vegetation types themselves. Our results provide insights into the effects of atmospheric moisture on vegetation growth and provide references for the sustainable development of vegetation ecosystems and future safeguarding strategies of vegetation over large spatial scales. [ABSTRACT FROM AUTHOR]

In precision oncology, integrating multiple cancer patient subgroups into a single master protocol allows for the simultaneous assessment of treatment effects in these subgroups and promotes the sharing of information between them, ultimately reducing sample sizes and costs and enhancing scientific validity. However, the safety and efficacy of these therapies may vary across different subgroups, resulting in heterogeneous outcomes. Therefore, identifying subgroup-specific optimal doses in early-phase clinical trials is crucial for the development of future trials. In this article, we review various innovative Bayesian information-borrowing strategies that aim to determine and optimize subgroup-specific doses. Specifically, we discuss Bayesian hierarchical modeling, Bayesian clustering, Bayesian model averaging or selection, pairwise borrowing, and other relevant approaches. By employing these Bayesian information-borrowing methods, investigators can gain a better understanding of the intricate relationships between dose, toxicity, and efficacy in each subgroup. This increased understanding significantly improves the chances of identifying an optimal dose tailored to each specific subgroup. Furthermore, we present several practical recommendations to guide the design of future early-phase oncology trials involving multiple subgroups when using the Bayesian information-borrowing methods. [ABSTRACT FROM AUTHOR]

[Display omitted] The zinc-air battery (ZAB) performance and stability strongly depend on the structure of bifunctional electrocatalyst for oxygen reduction/evolution reaction (ORR/OER). In this work, we combine the tip and heterogeneous effects to construct cobalt/cobalt oxide heterostructure nanoarrays (Co/CoO-NAs). Due to the formed heterostructure, more oxygen vacancies are found for Co/CoO-NAs resulting in a 1.4-fold higher ORR intrinsic activity than commercial carbon supported platinum electrocatalyst (Pt/C) at 0.8 V versus reversible hydrogen electrode (vs. RHE). Moreover, a fast surface reconstruction is observed for Co/CoO-NAs during OER catalysis evidenced by in-situ electrochemical impedance spectroscopy and Raman tests. In addition, the tip effect efficiently lowers the mass transfer resistance triggering a low overpotential of 347 mV at 200 mA cm−2 for Co/CoO-NAs. The strong electronic interplay between cobalt (Co) and cobalt oxide (CoO) contributes to a stable battery performance during 1200 h galvanostatic charge–discharge test at 5 mA cm−2. This work offers a new avenue to construct high-performance and stable oxygen electrocatalyst for rechargeable ZAB. [ABSTRACT FROM AUTHOR]

Since 1978, China's rapid urbanization and industrialization have significantly increased carbon emissions. This study employs spatial autocorrelation, kernel density estimation, and spatiotemporal geographically weighted regression (GTWR) methods to analyze the spatiotemporal evolution characteristics of carbon emissions across 336 Chinese cities from 1978 to 2020. It also explores the dominant influencing factors for different cities at various stages of development. The findings reveal that carbon emissions in Chinese cities exhibit a stepwise growth pattern: “slow growth (1978–1995) - low-level stability (1996–2000) - rapid growth (2001–2012) - high-level stability (2013–2020).'' The gap between cities has widened rapidly, and spatially, the distribution follows a “core-periphery” pattern. The increase in carbon emissions in core cities has transformed the urban hierarchy from a “generally low-carbon” structure to a “pyramid” structure. Compared to 1995, the influence of population size on carbon emissions decreased in 2020 (0.54–0.38), while the impact of infrastructure development and technological advances increased (0.02–0.25, 0.09 to 0.19). Due to the varying stages of urban development across regions, the influencing factors of carbon emissions exhibit spatial heterogeneity. Specifically, population size has a stronger positive impact on carbon emissions in the Southeast, technological advances in East and North China, and industrial structure in the Yangtze River Basin region. Infrastructure construction and investment levels show a dampening effect on carbon emissions in the Yangtze River Basin. Finally, the study proposes policy recommendations focusing on implementing regional “gradient” carbon reduction and promoting regional collaborative carbon reduction driven by core cities.

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Previous studies have fully discussed the relationship between family socioeconomic status (SES) and achievement, but few of them regarded urban–rural differences as the moderating factor, which is an essential issue in urban–rural educational equalization in terms of educational outcomes. This study discusses the urban–rural heterogeneous effect of family SES on achievement and manifests the mediating role of education-related cultural factors. Based on the China Education Panel Survey data of 18,672 junior high school students, this study found the following: (1) family SES had a weaker positive effect among rural children than among urban children; (2) the urban–rural heterogeneous effect could be mediated by education-related cultural factors, i.e., learning environments and beliefs; and (3) in this regard, contemporary China is experiencing cultural reproduction rather than a cultural mobility mode. In Conclusion, although the urban–rural achievement gap will be maintained or even expanded in China, improving rural children's learning environments and beliefs opens up the possibility of alleviating disadvantages in achievement resulting from family socioeconomic disadvantages. Therefore, narrowing down the urban–rural achievement gap from a cultural perspective provides policy implications for educational development in rural areas. [ABSTRACT FROM AUTHOR]

Given the great importance attached to ecological civilization and green development, exploring the heterogeneous effects of environmental regulation policy synergy on ecological resilience holds significance for improving environmental protection and the design of environmental policies. Based on the policy synergy perspective, this paper uses 30 provinces (municipalities and autonomous) in China as the research sample. Bayesian quantile regression is employed to explore the heterogeneous effects of environmental regulation policy synergy on ecological resilience from 2007 to 2021, and the moderating effect of the industrial structure is examined. The results indicate the following: (1) there is significant heterogeneity and variability in the effect of environmental regulation policy synergy on ecological resilience. Specifically, the effects of policy mixes 12, 13, and 23 on ecological resilience shows a U-shaped trend, while the impact of policy mix 123 on ecological resilience shows a positive effect. (2) There are significant differences in the effects of environmental regulation policy synergy under different quantiles of ecological resilience. Taking policy mix 12 as an example, we find that the effect of policy synergy on ecological resilience tends to decrease and then increase at a lower quantile. Additionally, the effect of policy synergy on ecological resilience tends to be positive at a higher quantile. (3) There are significant differences in the moderating effects of the industrial structure. Policy mix 12 can effectively enhance ecological resilience through industrial structure upgrading, while the moderating effects of alternative policy combinations are deemed insufficient. Finally, relevant policy recommendations are proposed to effectively improve ecological resilience. [ABSTRACT FROM AUTHOR]

Central bank digital currency (CBDC) signals affect the volatility of stock indices in different sectors differently. This paper aims to examine whether the CBDC signal plays a role on the volatility of different stock indices. First, we employ a text analysis to compile the CBDC signal index, which spans from January 4, 2013 to March 16, 2023. Then, based on the mixing frequency data, we construct generalized autoregressive conditional heteroskedasticity mixed data sampling (GARCH-MIDAS) models to explore the various impacts of CBDC signal on the volatility of stock indices in different sectors. The findings show the heterogeneous effect of CBDC signals on the volatility of stock indices across different sectors. Furthermore, CBDC signals have a heterogeneous effect on the volatility of stock indices in different sectors for different lag periods.

Purpose – This study aims to investigate whether temperature affects the product quality of exporters and whether the effect is non-linear. More specifically, whether the impact of high temperatures differs from the impact of low temperatures, and whether different types of companies or industries are affected differently. Design/methodology/approach – The paper uses detailed data covering all Chinese exporters from 2000 to 2016 to estimate the effects of temperature on the product quality of export firms. To clarify the relationship between them, the authors use a semi-parametric regression method, trying to test whether there is a non-linear relationship between temperature and the export quality of firms. Findings – The increase in the number of high temperature days significantly reduces the quality of exported products, and this negative effect increases as the temperature rises. High temperature has the most significant negative impact on export quality for firms with low technical complexity, private firms and firms with no intermediate imports and located in historical hot cities. Product quality of both labor-intensive and capital-intensive firms will be affected by heat. High temperatures have the greatest negative impact on the export quality of newly entering products, followed by exiting products, with the least negative impact on persisting product. Originality/value – To the best of the authors’ knowledge, this paper is the first to examine the impact of temperature on the quality of economic development. The findings of this paper again show that the potential economic impacts of global warming are huge. In addition to some potentially devastating impacts in the future, global warming is already causing imperceptible impacts in the present. Public and economic agents need to fully understand the possible adverse impacts of climate change and take corresponding adaptation measures to cope with global warming.

This study explored the impact of mobile broadband use on smallholders' entrepreneurial engagement and willingness using data from a household survey collected from three provinces in China. We used an endogenous switching probit model to account for the potential selection bias associated with mobile broadband use. The empirical results indicated that mobile broadband use exerted positive and statistically significant impacts on smallholders' entrepreneurial engagement and willingness. In particular, we found that mobile broadband use increased the probability of smallholders' entrepreneurial engagement and willingness by 15.1 and 50.9% points, respectively. Further analysis revealed that the effects of mobile broadband use on smallholder entrepreneurship were heterogeneous across regions. Additionally, we found that while the impact of mobile broadband use on entrepreneurial engagement was the largest for smallholders with high income, its impact on entrepreneurial willingness appeared to be the greatest for smallholders with low income. This study extended the literature by analysing smallholder entrepreneurship and provided evidence on the effect of mobile ICT on smallholder entrepreneurship. [ABSTRACT FROM AUTHOR]

s t r i n g U t i l s. c o n v e r t A b s t r a c t M a t h H t m l (formulaUtilTools.convertMathHtml( s t r i n g U t i l s. c o n v e r t M m l (!article.abstractinfoEn))) Central bank digital currency (CBDC) signals affect the volatility of stock indices in different sectors differently. This paper aims to examine whether the CBDC signal plays a role on the volatility of different stock indices. First, we employ a text analysis to compile the CBDC signal index, which spans from January 4, 2013 to March 16, 2023. Then, based on the mixing frequency data, we construct generalized autoregressive conditional heteroskedasticity mixed data sampling (GARCH-MIDAS) models to explore the various impacts of CBDC signal on the volatility of stock indices in different sectors. The findings show the heterogeneous effect of CBDC signals on the volatility of stock indices across different sectors. Furthermore, CBDC signals have a heterogeneous effect on the volatility of stock indices in different sectors for different lag periods. [ABSTRACT FROM AUTHOR]

The digital economy has been considered a powerful weapon in addressing global warming. However, the "win-win" effect of the digital economy on economic development and carbon reduction is still unclear. With China's provincial panel data from 2012 to 2019, this paper intends to explore the direct and spatial effects of the digital economy on total factor carbon productivity (TFCP), further revealing the influencing mechanism from the perspective of energy intensity. The results show that the digital economy contributes to boosting TFCP and this conclusion is robust after adopting some robustness tests and solving the endogeneity problem. Moreover, the impact of the digital economy on TFCP has significant positive spillovers. Finally, the digital economy can significantly boost TFCP through reducing the energy intensity. Considering the regional heterogeneity, the impact of the digital economy on TFCP is significantly positive in Mid-Eastern China, however, the impact is not significant in other areas. The above findings provide strong policy guidance for the region to boost the digital economy and TFCP comprehensively, thus stimulating the green transition of the economy. [ABSTRACT FROM AUTHOR]

Air pollution has been a severe issue in China. Exposure to PM2.5 has adverse health effects and causes economic losses. This study investigated the economic impact of exposure to PM2.5 pollution using monthly city-level data covering 88.5 million urban employees in 2016 and 2017. This study mainly focused on three expenditure indicators to measure the economic impact considering lower respiratory infections (LRIs), coronary heart disease (CHD), and stroke. The results show that a 10 µg/m3 increase in PM2.5 would cause total monthly expenses of LRIs, CHD, and stroke to increase by 0.226%, 0.237%, and 0.374%, respectively. We also found that LRI, CHD, and stroke hospital admissions increased significantly by 10%, 8.42%, and 5.64%, respectively. Furthermore, the total hospital stays of LRIs, CHDs, and strokes increased by 2.49%, 2. 51%, and 1.64%, respectively. Our findings also suggest heterogeneous impacts of PM2.5 exposures by sex and across regions, but no statistical evidence shows significant differences between the older and younger adult subgroups. Our results provide several policy implications for reducing unequal public health expenditures in overpolluted countries. [ABSTRACT FROM AUTHOR]

The impact of population aging on economic growth is a very important issue in the process of population structure change. This paper first proposes research hypotheses based on a systematic literature review and theoretical analysis of the negative and positive effects of population aging on economic growth. Then, based on the data of 30 provinces in the Chinese Mainland from 2000 to 2019, this paper empirically tests the impact of population aging on economic growth and its impact mechanism using a static panel data model, a dynamic panel data model and a mediating effect model. Our empirical analysis leads to the following conclusions. First, population aging has a significant inhibitory effect on economic growth. Second, the industrial structure upgrading plays a mediating role in the process of population aging affecting economic growth; that is, population aging inhibits economic growth by affecting the overall upgrading of the industrial structure as well as the industrial rationalization and optimization. Last, some policy implications are proposed based on the research conclusions.

In order to test the effect of information and communication technology (ICT) level on financial inclusion, based on the sample data of countries around the world in 2011, 2014, and 2017, this paper firstly uses the coefficient of variation method and the Euclidean distance method to construct the ICT level index and the financial inclusion index, and then conducts empirical analysis through a linear regression model. Further, a mediating effect model is employed to explore the impact mechanism of the ICT level on financial inclusion. Finally, the impact heterogeneity is explored based on the internal and external characteristics of each country. The empirical results show that: first, the ICT level can effectively improve financial inclusion, but its effects on the width and the depth of financial inclusion are different; second, the ICT level improves a country's financial inclusion by promoting the improvement and development of the digital payment system; third, the impact of the ICT level on financial inclusion shows significant heterogeneity among different countries or regions with differences in banking structure, economic development level and international financial environment. Last but not least, the conclusions of this paper can help countries or regions to improve financial inclusion in a targeted manner through information and communication technology.

The limited nature of land supply determines that improving land use efficiency is an inherent requirement for economic development. The aim of this study was to quantitatively examine its impact. Most current studies have explored the quantitative relationship between urban land use efficiency (ULUE) and economic development, but less attention has been given to the mechanism of action of both. In this study, we construct an analysis framework for the mechanism of ULUE in promoting economic development from three aspects: economic scale, economic structure, and economic quality, and we quantitatively investigate its impact on economic development and intermediate action mechanism through a mediating effect model on the basis of measuring ULUE by using a super-efficiency SBM-undesirable model. Based on the analysis of the panel data of 56 cities in the Yellow River Basin (YRB), the results show that, first, ULUE has formed an ideal positive driving effect on economic development, and its influence mechanism has obvious heterogeneity in cities with different geographical locations and resource endowments. Second, ULUE affects economic development through three channels: economic scale-up effect, economic structure optimization effect, and economic quality enhancement effect, and there are two different mechanisms of mediating effect and suppressing effect. Finally, variables such as investment intensity of urban construction land and social benefit act as suppressing effects, while variables such as economic output density of urban land, industrial structure, employment structure, economic benefit, and environmental benefit play partial mediating effects. These evidence-based findings can provide practical guidance for solving the dilemma of a lack of economic development momentum and inefficient land use in a country or region. [ABSTRACT FROM AUTHOR]

Previous studies have fully discussed the relationship between family socioeconomic status (SES) and achievement, but few of them regarded urban–rural differences as the moderating factor, which is an essential issue in urban–rural educational equalization in terms of educational outcomes. This study discusses the urban–rural heterogeneous effect of family SES on achievement and manifests the mediating role of education-related cultural factors. Based on the China Education Panel Survey data of 18,672 junior high school students, this study found the following: (1) family SES had a weaker positive effect among rural children than among urban children; (2) the urban–rural heterogeneous effect could be mediated by education-related cultural factors, i.e., learning environments and beliefs; and (3) in this regard, contemporary China is experiencing cultural reproduction rather than a cultural mobility mode. In Conclusion, although the urban–rural achievement gap will be maintained or even expanded in China, improving rural children’s learning environments and beliefs opens up the possibility of alleviating disadvantages in achievement resulting from family socioeconomic disadvantages. Therefore, narrowing down the urban–rural achievement gap from a cultural perspective provides policy implications for educational development in rural areas.

Understanding the effect of freight structure (FS) on carbon dioxide (CO2) emissions is significant for policymakers in the transport sector. However, few studies have investigated fully how the freight structure influences transport CO2 emissions. In the paper, a comprehensive freight structure index is proposed to assess the freight structure in 16 provinces of China during 2005–2019. Then, the heterogeneous effect of the freight structure and other factors on CO2 emissions are quantified by the quantile regression model developed. The mediating effect between freight structure and CO2 emissions is further examined. And the panel causality test is used to explore the directions of causality among variables. The main results indicate that (1) the level of freight structure shows a distribution of increase from western and central regions to eastern regions in 16 provinces. (2) Freight structure has a positive effect on transport CO2 emissions, and its effect is significantly heterogeneous in all quantiles. (3) Freight structure has an indirect impact on CO2 emissions through the scale effect. (4) The bidirectional causality is confirmed between economic growth, industrial structure, and information and communication technology with carbon emissions. A unidirectional causality from CO2 emissions to freight structure is also found. Finally, some policy recommendations are proposed for sustainable transport development in China. The results facilitate the formulation of the regionally tailored carbon emission reduction strategy in the transport sector. [ABSTRACT FROM AUTHOR]

Previous research has examined moderation effects with traditional analyses such as ANOVA, ANCOVA, moderated regression analysis (MRA), or a combination of MRA and subgroup analysis. However, there exists some confusion in such analyses, because the analyses do not separately consider two possible effects of a moderator on the form and strength of relationship between a focal predictor and a dependent variable. The effect on the form is measured with the interaction effect between the focal predictor and the moderator whereas the effect on the strength is measured with the effect of the moderator on predictability of the focal predictor on the dependent variable. This paper proposes a heterogeneous MRA that allows the moderation effect to be heterogeneous in the population, and shows that it allows one to examine the two possible moderation effects separately. Furthermore, this paper shows that previous research based on the traditional analyses might have incorrectly led to conclusions that there did not exist moderation effects even though the moderation effects were strongly supported by theories. The heterogeneous MRA can examine moderation effects with a data set collected for the traditional analyses. Thus, this paper recommends one to use the heterogeneous MRA together with the traditional analyses. [ABSTRACT FROM AUTHOR]

Four decades of rapid economic growth have enabled the Chinese government to dedicate more resources to research and development. China is the world's second largest spender on food and agricultural research in terms of absolute expenditures and the largest investor on a purchasing power parity basis. Using a unique panel dataset collected in 2019 in China's seed company and fixed effect models, this study analyzes the heterogeneous effects of central subsidies and local subsidies. Specifically, this study first tests whether government subsidies have a positive impact on firms' innovation. Then, this study answers whether the impact of local subsidies differs from that of central subsidies. The estimation results show that the central subsidies positively contribute to firm's innovation, while the impact of local subsidies on firms' innovation has not been confirmed. Further analysis shows that local subsidies positively affect firms' economic performance. That is, rather than focusing on research capacity, local governments are more concerned about firms' current economic performance due to the performance-based promotion scheme in China. Based on this study, local governments should implement similar methods to those of the central government in research project funding and criteria for selecting research projects to promote firms' innovation. [ABSTRACT FROM AUTHOR]

With the emergence of digital transformation, China confronts the dual challenge of fostering sustainable economic and social development while fulfilling its "dual-carbon" commitments. Is the digital-real economy integration a blessing or a curse for inclusive green development? The study was conducted under this backdrop. This paper explores the impacts and mechanisms of digital-real economy integration on carbon emission efficiency, utilizing panel data from 274 Chinese cities over the period from 2011 to 2021. The results indicate that this profound integration significantly enhances urban carbon emission efficiency, although this relationship is partially mediated by industrial structure upgrading. Additionally, natural resources dependence may compromise efficiency gains, exhibiting varying effects across different contexts. The impact of digital-real economy integration on carbon efficiency (Cee) manifests as a non-linear U-shaped relationship that intensifies with increased integration. Heterogeneity analysis reveals that major, eastern, coastal, and resource-scarce cities experience the most profound benefits. These findings highlight the urgency of advancing digital carbon neutrality and offer strategies for emerging economies to transcend traditional constraints, thereby achieving green economic recovery and inclusive development. • The impact of digital-real economy intergration on carbon emission efficiency in China is explored. • The baseline results are robust under multiple econometric analyses. • The non-linear effect and the heterogeneity are supported. • The mediating channel and the moderating mechanism are identified. [ABSTRACT FROM AUTHOR]

The control rod assembly is an important part of the fast reactor control system and safety protection system. The accurate solution of the fast reactor control rod worth is very important. The direct volume homogenization method is used in the calculation of the fast reactor few�group homogenization constants based on the PASC�5 code, which will lead to a serious overestimation of the control rod worth, and the heterogeneous effects of the control rod assembly must be corrected. Based on the idea of group constant correction, the applications of three methods including volume�flux weight, reaction rate ratio preservation, and reactivity preservation were studied in the correction of heterogeneous effects of fast reactor control rod assembly in the paper. Based on the two�dimensional characteristic line code, the calculation code named FRHP for the group constant correction was developed. Tested and verified by the China Experimental Fast Reactor case, the corrected control rod worth calculation results are in good agreement with the MCNP calculation reference results, indicating that the three methods can effectively correct the heterogeneous effects of the control rod assembly, among which the reactivity preservation method has the best correction effect.

The concept and theory of ecological compensation (EC) have been widely studied in the past 20 years, but its practical effects have not yet been agreed upon. Based on a panel data from 281 prefecture-level cities in China from 2009 to 2018, this paper examines the impact of air ecological compensation (AEC) policy on air pollutant emissions and its mechanism with time-varying DID model. The study found that AEC will reduce the emissions of sulfur dioxide, PM2.5, industrial smoke and dust, which remained significant after a series of robustness test. Mechanism analysis concluded that AEC can reduce air pollutant emissions mainly by promoting green technology innovation, strengthening pollution treatment intensity and improving energy efficiency. The effect of AEC varied with city characteristics, in cities with high proportion of Industrial, low environmental regulation intensity and high fiscal pressure, AEC have significant or better policy effects, while, AEC does not have significant policy effects in cities with high environmental regulations intensity and low financial pressure. China should consider further promoting the pilot scope of AEC, but it also needs to improve the compensation standard and compensation mechanism to achieve better policy effects. [ABSTRACT FROM AUTHOR]

With the huge dividends released by the vigorous development of the digital economy, China urgently demand a major strategic transformation from extensive development to green development. The 14th five-year plan period will require China’s green development to firmly create new advantages in the growth of the digital economy. In order to investigate the impact of the digital economy on the green economy, this paper has utilized a panel data model to analyze data from 30 Chinese provinces between 2015 and 2020. Findings from the research have suggested that the digital economy is helpful for advancing the green economy, with the Eastern region having a bigger influence than the central region and the center region having a greater influence than the Western region. Industrial structure and technological innovation are important channels for digital economy to promote green development. According to the aforementioned conclusion, we have proposed the following suggestion: China should actively advance the digital economy, encourage regional coordination in growth, continuously improve the industrial structure and boost technical innovation.

This paper examines the effects and mechanism of the financialization of manufacturing enterprises on total factor productivity (TFP). Thus, it provides evidence of the economic consequences of corporate financialization from the perspective of productivity. Using the panel data of China's listed manufacturing companies from 2007 to 2018, the level of corporate financialization is measured using the proportion of financial assets in the total assets. The results show that the deepening of the financialization of manufacturing enterprises significantly reduces TFP and the magnitude of the impacts of different types of financial assets variates. In addition, the effects of corporate financialization on TFP are heterogeneous in terms of their significance and degrees in different types of enterprises as well as in different levels of enterprises' TFP. The further analysis of the influencing mechanism shows that corporate financialization has different effects on the TFP of manufacturing enterprises through technological innovation and resource allocation efficiency.

The limited nature of land supply determines that improving land use efficiency is an inherent requirement for economic development. The aim of this study was to quantitatively examine its impact. Most current studies have explored the quantitative relationship between urban land use efficiency (ULUE) and economic development, but less attention has been given to the mechanism of action of both. In this study, we construct an analysis framework for the mechanism of ULUE in promoting economic development from three aspects: economic scale, economic structure, and economic quality, and we quantitatively investigate its impact on economic development and intermediate action mechanism through a mediating effect model on the basis of measuring ULUE by using a super-efficiency SBM-undesirable model. Based on the analysis of the panel data of 56 cities in the Yellow River Basin (YRB), the results show that, first, ULUE has formed an ideal positive driving effect on economic development, and its influence mechanism has obvious heterogeneity in cities with different geographical locations and resource endowments. Second, ULUE affects economic development through three channels: economic scale-up effect, economic structure optimization effect, and economic quality enhancement effect, and there are two different mechanisms of mediating effect and suppressing effect. Finally, variables such as investment intensity of urban construction land and social benefit act as suppressing effects, while variables such as economic output density of urban land, industrial structure, employment structure, economic benefit, and environmental benefit play partial mediating effects. These evidence-based findings can provide practical guidance for solving the dilemma of a lack of economic development momentum and inefficient land use in a country or region.

We conduct theoretical and empirical study on the impact of economic policy uncertainty on PM2.5 pollution. Economic policy uncertainty has important impact on PM2.5 pollution through investment channel and innovation channel. Specifically, according to real option theory, increase in economic policy uncertainty can reduce investment, thereby reducing PM2.5 pollution. However, increase in economic policy uncertainty can hinder corporate's innovation activities, which in turn make PM2.5 pollution increase. Therefore, the impact of economic policy uncertainty on PM2.5 pollution depends on the combination effect of these two different effects. Furthermore, using 25 countries' unbalanced panel data and fixed effects estimation methods, we empirically test the impact of economic policy uncertainty on PM2.5 pollution. The results show that, with the increase of economic policy uncertainty, countries' PM2.5 pollution has significantly decreased. In addition, economic policy uncertainty has heterogeneous effect on countries' PM2.5 pollution. Compared with countries who have higher R&D input, increase in economic policy uncertainty makes the reduction of PM2.5 pollution in countries with relatively lower R&D input higher. By changing the measurement methods of economic policy uncertainty and PM2.5 pollution indicators, and using 2SLS methods to estimate the models, the conclusions of the paper are robust. Finally, we put forward corresponding policy implications. [ABSTRACT FROM AUTHOR]

The authors examined cocoa farmers' participation in Farmer Business Schools (FBS) in Ghana, impacts of livelihood outcomes (human, physical, financial, and social capitals) on participation, and implications of participation on productivity and per capita expenditure. We used cross-sectional data from 150 cocoa farmers. Data was analyzed with descriptive statistics, heteroskedastic probit, and doubly robust augmented inverse probability weighted regression adjustment model (AIPW). More than half of cocoa farmers participated in FBS. Financial capital (income and loan accessibility) and social capital (farmer group membership) positively influenced participation in FBS. Nevertheless, human capital (ability to pay medical bills) and physical capital (number of sleeping rooms) negatively influenced participation in FBS. Knowledge and skills cocoa farmers obtained from FBS are new farming methods, creativity in solving farming problems, record keeping, and managerial skills. Participation in FBS had a positive impact and a heterogeneous effect on cocoa farmers' productivity and per capita expenditure. Given that the impact of FBS was heterogeneous, the FBS curriculum and approach should be segmented for different types of farmers to the generic FBS approaches currently practiced. [ABSTRACT FROM AUTHOR]

Abstract Background The association between poverty and health has been widely assessed. However, whether the association between poverty and health-related quality of life (HRQOL) holds among different groups is unknown. This study aimed to 1) assess the association between poverty and HRQOL among rural residents in China and 2) examine whether the association holds among different populations, thereby supporting policy-making and implementation. Methods A multistage, stratified, random household survey was conducted with self-administered questionnaires. Matched samples were generated by the censored exact matching method to reduce selection bias between the poverty and comparison groups. We applied Tobit and ordinal logit regression models to evaluate the association between poverty and HRQOL measured by the EQ-5D-3 L among different groups. Results The health utility score of the poverty group was 6.1% lower than that of comparison group (95% CI = − 0.085, − 0.037), with anxiety/depression being most common (95% CI = 1.220, 1.791). The association between poverty and HRQOL was significantly stronger among residents from central China, males, people who were middle-aged, elderly, highly educated, married, or widowed, those living far from healthcare facilities, and those without chronic disease. Male and highly educated subjects reported worse mobility, self-care, usual activities, pain/discomfort and anxiety/depression dimensions than the other respondents. Middle-aged (95% CI = 1.692, 2.851) and married respondents (95% CI = 1.692, 2.509) and respondents with chronic diseases (95% CI = 1.770, 2.849) were most affected in the anxiety/depression. Conclusions The HRQOL of individuals living in poverty is lower than that of the general population, and the mental health dimension is most affected by poverty among respondents who are middle-aged or married and respondents with chronic diseases. The identification of populations that are more affected by poverty is critical to improve their HRQOL. Various associations have indicated the need for integrated policies and specific decision-making.

Since 1978, China's rapid urbanization and industrialization have significantly increased carbon emissions. This study employs spatial autocorrelation, kernel density estimation, and spatiotemporal geographically weighted regression (GTWR) methods to analyze the spatiotemporal evolution characteristics of carbon emissions across 336 Chinese cities from 1978 to 2020. It also explores the dominant influencing factors for different cities at various stages of development. The findings reveal that carbon emissions in Chinese cities exhibit a stepwise growth pattern: "slow growth (1978-1995) - low-level stability (1996-2000) - rapid growth (2001-2012) - high-level stability (2013-2020)." The gap between cities has widened rapidly, and spatially, the distribution follows a "core-periphery" pattern. The increase in carbon emissions in core cities has transformed the urban hierarchy from a "generally low-carbon" structure to a "pyramid" structure. Compared to 1995, the influence of population size on carbon emissions decreased in 2020 (0.54-0.38), while the impact of infrastructure development and technological advances increased (0.02-0.25, 0.09 to 0.19). Due to the varying stages of urban development across regions, the influencing factors of carbon emissions exhibit spatial heterogeneity. Specifically, population size has a stronger positive impact on carbon emissions in the Southeast, technological advances in East and North China, and industrial structure in the Yangtze River Basin region. Infrastructure construction and investment levels show a dampening effect on carbon emissions in the Yangtze River Basin. Finally, the study proposes policy recommendations focusing on implementing regional "gradient" carbon reduction and promoting regional collaborative carbon reduction driven by core cities., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Although reducing poverty has become an important issue for rural development in China, few studies have analyzed the role of mobile Internet use in multidimensional poverty. To fill this gap, this study investigated the impact of mobile Internet use on multidimensional poverty, using data collected from a household survey in rural China. Because households generally decide whether to use mobile Internet by themselves, an endogenous switching regression model was employed to control for potential selection bias. In total, 9.63% of the households were identified as multidimensionally poor and the adjusted multidimensional poverty incidence was 5.47%. The results also showed that mobile Internet use has a significant negative impact on multidimensional poverty. Further, we provide evidence of heterogeneity in the effect of mobile Internet use across regions. These findings highlight the importance of mobile Internet use in multidimensional poverty reduction strategies for rural households. [ABSTRACT FROM AUTHOR]

Aim: The adverse impacts of exposure to work intensity on mental health have been widely studied. However, there is a lack of research examining who is most vulnerable in terms of position on the mental health distribution. The current study aims to: (a) initially estimate the average impacts of work intensity on workers' mental health in Australia, and then (b) estimate the extent to which this effect varies across the mental health distribution. Materials and methods: The current study uses data from waves 2005-–2017 of the Household Income and Labour Dynamics in Australia (HILDA) survey. It first employs Average Treatment Effect (ATE) to provide a baseline/average treatment effect for the whole population, and then applies Quantile Regression fixed effects models for various quantiles on the mental health distribution. Discussion and conclusion: The baseline estimates show that there are significantly negative effects of work intensity on mental health for the whole population, but importantly the quantile fixed effect estimates show that these adverse effects are substantially stronger for those with the poorest mental health (i.e. at the bottom of the distribution). When ATE alone is estimated, the significant effect is averaged over the mental health distribution, missing important information regarding the heterogeneity of the effect. The findings have important implications for understanding and reducing mental health inequality, particularly inequality driven by workplace stress. First, they align with existing research demonstrating the importance of reducing psychosocial job stressors. Second, given workers with mental health problems were most susceptible to the adverse effects of work intensity, there is a need to offer additional support (and be sensitive of workloads) for this group in particular. [ABSTRACT FROM AUTHOR]

There have been consistent efforts to assess treatment effect heterogeneity (TEH) of Head Start using the data from the Head Start Impact Study (HSIS), a randomized controlled trial of a federally funded child development program for a nationally representative sample of low-income parents and their 3- and 4-year-old children in the United States. Including 28 studies on TEH of Head Start, this review found that multiple high-risk subgroups (e.g., children with lower cognitive abilities, Spanish-speaking dual language learners) experienced larger gains across a range of developmental and parental outcomes, but mixed results for several subgroups. Most studies focused on subgroup analyses, cognitive and social-emotional outcomes, and short-term effects. Further studies on distributional effects, health and parental outcomes, and long-term effects are warranted. Finally, suggestions for future research on TEH of Head Start are discussed, which are applicable to other child development programs and policy evaluations.

Given an endogenous/confounded binary treatment D, a response Y with its potential versions (Y0, Y1) and covariates X, finding the treatment effect is difficult if Y is not continuous, even when a binary instrumental variable (IV) Z is available. We show that, for any form of Y (continuous, binary, mixed,...), there exists a decomposition Y = μ0(X) + μ1(X)D + error with E(error|Z,X) = 0, where μ1(X)≡E(Y1‐Y0|complier,X) and 'compliers' are those who get treated if and only if Z = 1. First, using the decomposition, instrumental variable estimator (IVE) is applicable with polynomial approximations for μ0(X) and μ1(X) to obtain a linear model for Y. Second, better yet, an 'instrumental residual estimator (IRE)' with Z−E(Z|X) as an IV for D can be applied, and IRE is consistent for the 'E(Z|X)‐overlap' weighted average of μ1(X), which becomes E(Y1‐Y0|complier) for randomized Z. Third, going further, a 'weighted IRE' can be done which is consistent for E{μ1(X)}. Empirical analyses as well as a simulation study are provided to illustrate our approaches. [ABSTRACT FROM AUTHOR]

This paper estimates the mortality impacts of ozone pollution in China and the moderating effects of two possible adaptation strategies. Using an instrument variable constructed from ozone concentrations of nearby upwind cities, we find that ozone pollution significantly increases all-cause, cardiovascular, and respiratory mortality. Healthcare service provision significantly decreases the impacts of ozone pollution on all-cause and cardiovascular mortality, but does not moderate the impact on respiratory mortality. The impact of ozone on RES mortality declines after COVID-19. Healthcare service provision also reduces the distributional impact of ozone across the elderly and younger groups. Projection shows that climate change would induce mortality costs of 0.08% of China's GDP through increasing ozone pollution. [ABSTRACT FROM AUTHOR]

Simulating fast neutron reactor cores for comparing experimental and calculated data on the reactor neutronics characteristics is performed using zero power test stands. The BFS test facilities in operation in Russia (Obninsk) are discussed in the present paper. The geometrical arrangement of materials in the cores of the simulated reactors (fuel pins, fuel assemblies, coolant geometry) differs from the simulation assembly on the BFS. This can cause differences between the experimental results obtained at the BFS and theoretical calculations even in the case when homogenized concentrations of all materials of the reactor are thoroughly observed. The resulting differences in neutronics parameters due to the geometry of arrangement of materials with the same homogeneous concentrations are referred to as the heterogeneous effect. Heterogeneous effects tend to increase with increasing reactor power and its size, mainly due to changes in the neutron spectra. Calculations of a number of functional values were carried out for assessing the heterogeneous effects for different spatial arrangements of the reactor materials. The calculations were performed for the following cases: a) heterogeneous distribution of materials in accordance with the design of a fast reactor; b) heterogeneous arrangement of materials in accordance with the capabilities and design features of the BFS test facility; c) homogeneous representation of materials in the reactor core and breeding blankets. The configuration of materials in accordance with the design data for fast reactors of the BN-1200 type was accepted as the basic calculation option, relative to which the effect called the heterogeneous shift of the functional value (HSF) was calculated. The effect of neutron leakage on the HSF obtained as the result of calculations using different boundary conditions was estimated. All calculations were carried out for the same homogeneous concentrations of all materials for all the above three configurations. Calculations were carried out as well for the case when plutonium metal fuel was used in the BFS. The values of the following functionals were calculated for different cases of arrangement of materials: the effective multiplication factor (reactivity), the sodium void reactivity effect, the average energy of fission-inducing neutrons, and the ratios of radioactive capture cross-sections to fission cross-sections for 239Pu. The calculations were performed using the Serpent 2.1.30 (VTT, Finland) Monte Carlo software package for neutronics simulations and ENDF/B-VII.0 and JEFF-3.1.1 evaluated nuclear data libraries. The effects of various options of material arrangement on the values of keff were found to be the greatest (about 1.6%) for the case when fissile material in the form of dioxide is replaced with metal fissile material. Homogenization of the composition reduces the keff value by about 0.4%. The average energy of fission-inducing neutrons depends to a significant extent on the leakage of neutrons and the presence of sodium (the average energy of neutrons increases and reaches in the presence of sodium about 100 keV, that is, it increases by about 11–13%). Replacing fissile material metal with its dioxide in the BFS test facility (while maintaining homogeneous concentrations, including that of oxygen) allows reducing the average energy of fission-inducing neutrons by about 60 keV. The highest values of HSF, reaching 65%, are observed when calculation of sodium void reactivity effect is performed with materials distributed homogeneously; however, HSF is equal to 1.5% when calculation of the reactor mock-up assembled on the BFS is performed. In the absence of neutron leakage (infinitely extended medium), the sodium void reactivity effect becomes positive and the HSF is equal to 4–7%. The heterogeneous effect of α for 239Pu noticeably (6–8%) depends only on the replacement of metallic plutonium with its dioxide (maintaining, of course, the homogeneous concentrations).

In general, private supplementary tutoring is considered an effective means of improving academic achievement by parents. However, previous studies have produced partial or inconclusive results regarding its effectiveness. Thus, the present study conducted a comprehensive analysis based on a specially designed longitudinal survey of private supplementary mathematics tutoring among middle school students in China. The hierarchical linear analysis did not show a considerably significant positive effect of regular private tutoring, even when such tutoring continued throughout the summer vacation and school semester. The data also allowed a deeper inquiry into the role of the quality, quantity, and applicability of private tutoring. In addition, the heterogeneous effect of private supplementary tutoring across students with different mathematics achievement levels was explored, with possible explanations including the different learning styles of students from different groups, the ceiling effect of the testing tool, and the different learning needs of different groups of students. These results suggest that parents should carefully select private tutoring for their children, and that the government should provide more comprehensive professional guidelines to regulate the industry. [ABSTRACT FROM AUTHOR]

In 2017, Airbnb launched a pilot integrated social function (i.e., Stories) in China. This study focuses on the Stories feature where users in China locales can share experience and recommend accommodations via stories, exploring the effects of this feature on guests' booking behavior and hosts' performance. This study draws three findings. First, accommodations recommended by stories are more likely to attract bookings. Second, for multi-listing hosts, once one of their properties has been recommended by a story, the rest listings will also benefit from the story. Third, the story's effectiveness is heterogeneous, significantly depending on the attractiveness of its content. [ABSTRACT FROM AUTHOR]

In this article, the propagation of nonlinear shear horizontal waves for some comparisons between the heterogeneous and homogeneous plates is considered. It is assumed that one plate is made of up hyper-elastic, heterogeneous, isotropic, and generalized neo-Hookean materials, and the other consists of hyper-elastic, homogeneous, isotropic, and generalized neo-Hookean materials. Using the known solitary wave solutions, called bright and dark solitary wave solutions, to the nonlinear Schrödinger equation, these comparisons are made in terms of the heterogeneous and nonlinear effects. All numerical results, based on the asymptotic analyses in which the method of multiple scales is used, are graphically presented for the lowest dispersive symmetric branch of both dispersion relations. [ABSTRACT FROM AUTHOR]

This paper aims to make some comparative studies between heterogeneous and homogeneous layers for nonlinear shear horizontal (SH) waves in terms of the heterogeneous and nonlinear effects. Therefore, with this aim, two layers are defined as follows: on the one hand, one layer consists of hyperelastic, isotropic, heterogeneous, and generalized neo-Hookean materials; on the other hand, another layer is made up of hyperelastic, isotropic, homogeneous, and generalized neo-Hookean materials. Moreover, it is assumed that upper boundaries are stress-free and lower boundaries are rigidly fixed. The method of multiple scales is used in both analyses, in addition to using the known solutions of the nonlinear Schrödinger (NLS) equation, called bright and dark solitary wave solutions; these comparisons are made, numerically, and then all results are given for the lowest branch of both dispersion relations, graphically. Moreover, these comparisons are observed both on a large scale and on a small scale, not only in terms of the bright and dark solitary wave solutions but also in terms of the heterogeneous and nonlinear effects. [ABSTRACT FROM AUTHOR]