Environmental regulation effect on health poverty in China.

How does government spending on environmental protection benefit people's health? The current paper analyzed 2010 and 2018 data from the China Family Panel Studies (CFPS) database to measure the impact of province-level environmental regulations on the health of local population. The study also applied the Alkire Foster method to develop the multidimensional health poverty (MHP) score, a new index intended to measure the health status of individuals in a holistic manner. Our results indicated that more fiscal spending on environmental regulation could improve health of the local population, especially among low-income population living in the rural areas. Further, the size of health benefit differs by the type of environmental regulation. More specifically, regulations focusing on preventing environmental pollution can achieve more sizable health benefits than remedial ones. Finally, fine inhalable particle (PM2.5) has the largest mediating effect on the relationship between environmental regulation and public health. These results provide several policy implications, which highlight the importance of: scaling up fiscal environmental expenditure and optimizing the structure of environmental expenditure with more emphasis on rural areas where more low-income population are located; shifting from ex-post accountability to ex-ante prevention; and strengthening regional cooperation in environmental protection among local governments, and establishing a cross-regional coordination mechanism.

Bayesian transformation model for spatial partly interval-censored data.

The transformation model with partly interval-censored data offers a highly flexible modeling framework that can simultaneously support multiple common survival models and a wide variety of censored data types. However, the real data may contain unexplained heterogeneity that cannot be entirely explained by covariates and may be brought on by a variety of unmeasured regional characteristics. Due to this, we introduce the conditionally autoregressive prior into the transformation model with partly interval-censored data and take the spatial frailty into account. An efficient Markov chain Monte Carlo method is proposed to handle the posterior sampling and model inference. The approach is simple to use and does not include any challenging Metropolis steps owing to four-stage data augmentation. Through several simulations, the suggested method's empirical performance is assessed and then the method is used in a leukemia study.

Collaborative management of environmental pollution and carbon emissions drives local green growth: An analysis based on spatial effects.

Collaborative management of environmental pollution and carbon emissions (CMPC) has been a major policy instrument to promote Sustainable Development Goals (SDG) in recent years. However, the relationship between the benefits and drawbacks of this environmental management practice for green growth in and around a local area remains to be clarified. Using 30 provinces in China during 2001-2019 as the object of analysis, we assessed the efficiency of local CMPC practices using the nonradial directional distance function (NDDF) model, predicted local green growth using the frontier green complexity index (GCI), and empirically examined the spatial effects, locational heterogeneity, and threshold characteristics of the relationship using the spatial Durbin model and the panel threshold model. Our study finds that although efficient CMPC does drive local green growth, the promotion effect is nonlinear with decreasing marginal effect. This effect is particularly obvious in economically developed regions with higher CMPCs, which will absorb resources from neighboring regions and create a "siphoning" effect. It was found that local financial support and foreign direct investment (FDI) can radiate green growth to neighboring regions; therefore, CMPC practice needs to pay more attention to the effect of joint governance, supplemented by financial and foreign investment policy tools, to better promote the green transformation of local economy.

Unlocking policy effects: Water resources management plans and urban water pollution.

Water resource management, as a foundation for supporting sustainable urban development, has garnered increasing attention from scholars. Developing effective water resource management plans is a major challenge faced by countries worldwide. This study uses the 2015 Water Pollution Control and Prevention Action Plan (WPCAP) in China as a natural experiment and employs a Difference-in-Differences (DID) model to estimate the relationship between WPCAP and urban water pollution from 2010 to 2021. The findings are as follows: 1) WPCAP reduces water pollution. 2) WPCAP decreases water pollution in high-policy-pressure cities but increases water pollution in low-policy-pressure cities within a 60 km radius, particularly having a significantly negative impact on water pollution in low-policy-pressure cities with low altitude. 3) optimizing industrial and domestic water use, as well as enhancing sewage treatment capabilities, are crucial pathways through which WPCAP reduces water pollution. Additionally, WPCAP significantly improves water pollution control capabilities in cities with abundant water resources, large cities, and industrialized cities. 4) although WPCAP's ability to control water pollution increases management costs, it also raises residential income and promotes population growth. These findings have important implications for the sustainable development of water resources in emerging countries, including China.

Digital financial inclusion and upgrading of consumption structure: Evidence from rural China.

Based on the perspective of spatial economy, this paper focuses on the primary effects and spatial characteristics of Digital Financial Inclusion (DFI) on the upgrading of rural consumption structure (URCS) in China, conducting a literature review and theoretical analysis. It then uses statistical data collected over the years and the Digital Financial Inclusion Index (DFII) of Peking University to prepare panel data for 31 provinces in China (aside from Hong Kong, Macao, and Taiwan) from 2011 to 2020 for empirical testing. The results are as follows: DFI can considerably boost URCS, and there is a strong spatial neighbor impact, that is, it is affected by random shocks in surrounding provinces via its spatial effect; DFI has nonlinear characteristics in the process of fostering URCS, with the threshold variables of income level and family sizes; the impact of DFI on URCS is spatially heterogeneous, and the promotion of the eastern region is better than other zones. These results can inform policymakers about rural development and provide valuable references to push forward rural vitalization.

Carbon emissions changes of animal husbandry in China: Trends, attributions, and solutions: A spatial shift-share analysis.

China is a major livestock producer confronting the dual challenges of rising demand for animal-based food consumption and decreasing carbon emissions. To effectively address these issues, it is crucial to understand the trends of carbon emissions from animal husbandry and the competitive advantages of carbon emission reduction in different regions. This study uses panel data from 31 provinces from 2004 to 2020 to investigate the contributing factors to carbon emissions and explore ways to reduce carbon intensity in animal husbandry. The analysis employs spatial shift-share analysis and the spatial Durbin model. Our findings indicate that life-cycle carbon emissions associated with animal husbandry in China decreased from 572.411 Mt CO2eq to 520.413 Mt CO2eq over time, with an average annual decline of 0.568 %. The annual contribution of output value and internal industry-mix adjustment to carbon emission growth is 22.639 MT CO2eq and 6.226 MT CO2eq, respectively. On the other hand, the annual contribution of carbon efficiency improvement to carbon emission reduction is much higher, at 36.316 MT CO2eq. However, there is significant regional heterogeneity in the spatial decomposition of the carbon efficiency change component. The Northeastern region, Northwest and along the Great Wall demonstrate neighborhood advantages in enhancing carbon efficiency. In contrast, the South China and Southwest regions rely more on local carbon efficiency advantages to reduce the carbon intensity of animal husbandry. Furthermore, the carbon intensity in local and neighboring areas can be reduced through environmental regulations and industrial agglomeration. While technical progress significantly negatively impacts carbon intensity in neighboring regions, it does not contribute to reducing the carbon intensity of local animal husbandry. The findings provide valuable insights for local governments, aiding them in recognizing the pros and cons of carbon reduction in animal husbandry and strengthening regional cooperation in emission reduction management.

Can the digitalization level of agriculture improve its ecological efficiency under carbon constraints: Evidence from China.

The interplay between digitalization and economic development constitutes a pivotal global issue, yet empirical research on agricultural ecological efficiency in developing countries remains limited. This study initially establishes a measurement system and a comprehensive index for the level of agricultural digitalization. Subsequently, it delineates the relationship between agricultural digitalization level and agroecological efficiency using the spatial Durbin model, and ultimately explores the enhancing effect of agricultural digitalization level on agroecological efficiency using China as a case study. Research reveals that the agricultural ecological efficiency across the 31 mainland Chinese provinces demonstrates a generally linear upward trajectory, embodying both agglomeration and heterogeneity. The level of agricultural digitization exerts a significant, positive direct impact and facilitates a spatial spillover effect on agricultural ecological efficiency. Other control variables, such as financial support for agriculture and local economic development, impart a positive direct impact on regional agricultural ecological efficiency, while rural household operating income propels a positive spatial spillover effect on adjacent areas. The findings furnish guidance for developing countries to adeptly execute digital rural construction, aiming to enhance agricultural ecological efficiency amidst carbon constraints.

The spatial effects of the household's food insecurity levels in Ethiopia: by ordinal geo-additive model.

Background: Food insecurity and vulnerability in Ethiopia are historical problems due to natural- and human-made disasters, which affect a wide range of areas at a higher magnitude with adverse effects on the overall health of households. In Ethiopia, the problem is wider with higher magnitude. Moreover, this geographical distribution of this challenge remains unexplored regarding the effects of cultures and shocks, despite previous case studies suggesting the effects of shocks and other factors. Hence, this study aims to assess the geographic distribution of corrected-food insecurity levels (FCSL) across zones and explore the comprehensive effects of diverse factors on each level of a household's food insecurity. Method: This study analyzes three-term household-based panel data for years 2012, 2014, and 2016 with a total sample size of 11505 covering the all regional states of the country. An extended additive model, with empirical Bayes estimation by modeling both structured spatial effects using Markov random field or tensor product and unstructured effects using Gaussian, was adopted to assess the spatial distribution of FCSL across zones and to further explore the comprehensive effect of geographic, environmental, and socioeconomic factors on the locally adjusted measure. Result: Despite a chronological decline, a substantial portion of Ethiopian households remains food insecure (25%) and vulnerable (27.08%). The Markov random field (MRF) model is the best fit based on GVC, revealing that 90.04% of the total variation is explained by the spatial effects. Most of the northern and south-western areas and south-east and north-west areas are hot spot zones of food insecurity and vulnerability in the country. Moreover, factors such as education, urbanization, having a job, fertilizer usage in cropping, sanitation, and farming livestock and crops have a significant influence on reducing a household's probability of being at higher food insecurity levels (insecurity and vulnerability), whereas shocks occurrence and small land size ownership have worsened it. Conclusion: Chronically food insecure zones showed a strong cluster in the northern and south-western areas of the country, even though higher levels of household food insecurity in Ethiopia have shown a declining trend over the years. Therefore, in these areas, interventions addressing spatial structure factors, particularly urbanization, education, early marriage control, and job creation, along with controlling conflict and drought effect by food aid and selected coping strategies, and performing integrated farming by conserving land and the environment of zones can help to reduce a household's probability of being at higher food insecurity levels.

Exploring steric and electronic effects in tailoring lithium-ion solvation using engineered ether solvents through molecular dynamics simulations.

Lithium-metal batteries, owing to their remarkable energy density, represent a promising solution for future energy storage needs. However, the widespread adoption of lithium-metal batteries has been impeded by the inherent instability that exists between lithium metal and traditional liquid lithium electrolytes, initially designed for graphite anodes in lithium-ion batteries. Recent insights underscore the efficacy of electrolyte engineering as a strategic avenue to realize the potential of lithium-metal batteries. A notable approach involves the fluorination of solvent molecules, particularly those of the ether class. Nonetheless, a comprehensive understanding of the various factors governing solvent molecular design remains elusive. Here, we examine four solvents derived from 1,2-dimethoxylethane (DME) via molecular dynamics simulation. These solvents are engineered with the introduction of additional alkyl groups or through fluorination. We particularly scrutinize two critical facets: steric effects, arising from the incorporation of bulkier alkyl chains, and electronic effects, originating from fluorination. Our inquiry delves deeply into the stability, ion transport characteristics, and solvation behavior exhibited by these five distinct solvents. Our study underscores the profound impact of adjusting the steric and electronic attributes of solvent molecules on Li+solvation behavior. This, in turn, influences the coordination strength and the mode of association between Li+and solvation sites within the first solvation shell, providing key insights into the disparities in ion transport properties within electrolytes.

Modified basalt fibers boost performance of constructed wetlands: Comparison between surface coating and chemical grafting.

Modified basalt fiber (MBF) is a potential material that has been applied in wastewater treatment fields. In this study, superior performances of MBFs by calcium (Ca-MBF) and polyethyleneimine modification (PEI-MBF) were compared in constructed wetlands (CWs). Via chemical grafting, higher biofilm contents were observed on the surface of PEI-MBF, compared to Ca-MBF. Moreover, MBF increased key enzyme activities particularly in lower substrate layer, contributing to positive responses of microbial community in CWs. For instance, PEI-MBF boosted microbial richness and diversity and improved the abundances of denitrifying functional bacteria and biomarkers like Thauera, Vulcanibacillus, and Maritimimonas, probably promoting nitrate removal compared with Ca-MBF group. By contrast, Ca-MBF enriched more functional genera involved in nutrients removal, with the highest removal of ammonium (43.9 %), total nitrogen (66.2 %), and total phosphorus (37.1 %). Overall, this work provided new findings on improved performance of CWs with MBF.

The impact of structural upgrading of the service industry on regional ecologicalization efficiency of Industry: Empirical evidence from 30 Chinese provinces.

With the wave of the digital economy and industrial ecological construction, it is more essential for developing countries to focus on improving the structural quality of the service industry rather than just the quantitative aspect of the service industry. This study utilizes panel data from 30 provinces in China and spatial Dubin models to estimate the impact of service industry structure upgrading on industrial ecologicalization efficiency and its spatial effect. Our results reveal that productive and high-end service industries play a vital role in promoting industrial ecological efficiency. At the level of spatial effect, the productive service industry has a negative spatial correlation with the adjacent area, while the effect of the high-end service industry on the adjacent area is not highlighted. This study focuses on clarifying the spatial role of service industry structure upgrading on the improvement of industrial ecological efficiency, further expanding the theory of industrial structure adjustment, and providing insights for developing countries on how to optimize the structure of the service industry and achieve high-quality development of industrial ecologicalization.

Spatial Effect on the Performance of Carboxylate Anode Materials in Na-Ion Batteries.

Developing low-voltage carboxylate anode materials is critical for achieving low-cost, high-performance, and sustainable Na-ion batteries (NIBs). However, the structure design rationale and structure-performance correlation for organic carboxylates in NIBs remains elusive. Herein, the spatial effect on the performance of carboxylate anode materials is studied by introducing heteroatoms in the conjugation structure and manipulating the positions of carboxylate groups in the aromatic rings. Planar and twisted organic carboxylates are designed and synthesized to gain insight into the impact of geometric structures to the electrochemical performance of carboxylate anodes in NIBs. Among the carboxylates, disodium 2,2'-bipyridine-5,5'-dicarboxylate (2255-Na) with a planar structure outperforms the others in terms of highest specific capacity (210 mAh g-1), longest cycle life (2000 cycles), and best rate capability (up to 5 A g-1). The cyclic stability and redox mechanism of 2255-Na in NIBs are exploited by various characterization techniques. Moreover, high-temperature (up to 100 °C) and all-organic batteries based on a 2255-Na anode, a polyaniline (PANI) cathode, and an ether-based electrolyte are achieved and exhibited exceptional electrochemical performance. Therefore, this work demonstrates that designing organic carboxylates with extended planar conjugation structures is an effective strategy to achieve high-performance and sustainable NIBs.

Digital development and the improvement of urban economic resilience: Evidence from China.

Digital technologies are empowering economic and social development, which attracts scholars' attention to the relationship between digitalization and economic resilience, However, the empirical analysis for different countries and stages of development are inconsistent, and the influencing mechanism need to be further explored. Using panel data for 284 prefecture-level cities in China from 2007 to 2020, this study examines the impact of urban digital development on economic resilience. The findings are as follows: (1) The increased digitalization significantly enhances the urban economic resilience, and this effect was more pronounced in eastern regions and large-scale cities. (2) The relationship between digitalization and economic resilience follows an inverted U-shape as population density increases. (3) The spatial effects show that increased digitalization has a significant positive effect on local economic resilience, but weakens the resilience of the surrounding areas. (4) The analysis of mechanism reveals that the positive impact of digitalization on the urban economic resilience is mainly achieved by improving the quality of the regional labor force and total factor productivity. The study provides theoretical and empirical evidence for accelerating the digital construction, fully releasing the digital dividend in order to strengthen economic resilience.

Ecological footprint, natural resource rent, and industrial production in MENA region: Empirical evidence using the SDM model.

Based on a spatial approach, this study aims to test and appreciate the relationship between natural resource rents, industrial production, and ecological footprint (EFP) for 17 countries in the MENA region over the period 2000-2018. Findings demonstrate the existence of (i) statical significant direct effects between environmental degradation, the level of local development, the resource rent, and the rate of industrialization. (ii) a significant positive spatial autocorrelation in EFP levels with a clear trajectory dependence characteristic in their geographic distribution. (iii) a positive interdependence between economic development, the level of industrialization, and resource rent with neighboring countries; (iv) only renewable energy conception has a negative interdependence with neighboring countries. Based on our result, regional planning can be dressed to maintain environmental quality in the region by defining the adequate compensation process between countries in the region. Developing a bio-economy seems to be a collective-collaborative process to maintain economic growth and industrial production without destroying the environment.

Driving impact and spatial effect of the digital economy development on carbon emissions in typical cities: a case study of Zhejiang, China.

The digital economy (DE) not only drives economic innovation and development but also has significant environmental effects by promoting lower carbon emissions. To investigate the spatial effects of DE on urban carbon emissions, this study comprehensively measures the level of DE development based on the panel data from 11 typical cities in Zhejiang Province from 2011 to 2020, by comparing analysis using different regression models. The following conclusions are obtained: (1) The total carbon emissions (TC) of Zhejiang cities in general show a fluctuating change trend of first increasing and then slowly decreasing, while carbon emission intensity and carbon emission per capita in general show a fluctuating change trend of decreasing. Cities with high TC are primarily concentrated in the Hangzhou Bay city cluster, accounted for 62 ~ 65% of the province's carbon emissions. The development of the DE in Zhejiang cities shows steady growth, but there are large differences among cities, with Hangzhou and Ningbo standing out as particularly prominent. (2) There is a significant inverted U-shaped relationship between the DE and the level of carbon emissions in Zhejiang Province. The influence coefficient of the DE on the primary term of TC is 0.613, and the influence coefficient of the quadratic term of TC is - 1.008. (3) In terms of the spatial spillover effect of the DE on carbon emissions, the study finds that compared to the direct effect, the spatial spillover effect is not significant. However, the allocation of transport resources shows a positive spatial spillover effect (increasing carbon emissions, coefficient value is 0.138), while technological progress shows a somewhat negative spatial spillover effect (decreasing carbon emissions, coefficient value is - 0.035). (4) The study also finds that the smart city pilot policy significantly reduces urban carbon emissions. Moreover, the effect of the DE on carbon emissions is confirmed through the significance test of the quadratic term when replacing the geographical and economic distance weight matrices. This indicates that the empirical findings are robust to these tests. Finally, several countermeasures to reduce carbon emissions are proposed from the perspective of DE development.

Analysis of the Impact of Public Services on Residents' Health: A Spatial Econometric Analysis of Chinese Provinces.

Objectives: The aim of this study was to explore the mechanism between public services and residents' health, focusing on the role of spatial geographical factors. Methods: Leveraging a comprehensive panel dataset encompassing 30 mainland Chinese provinces from 2007 to 2019, this study engineered a spatial Durbin model furnished with dual fixed effects through the application of the Lagrange multiplier, Hausman, and likelihood ratio tests. The primary objective was to delve into the repercussions of varying public service levels on residents' health outcomes. Results: The empirical findings reveal a palpable spatial autocorrelation between residents' health outcomes and the public services levels dispensed across Chinese provinces. Intriguingly, an elevation in the public service level in a given province not only ameliorates its residents' health outcomes but also triggers a spatial spillover effect, thereby positively influencing residents' health in neighboring provinces. The rigorous endogeneity and robustness checks affirm the reliability of the principal outcomes. Conclusion: Due to the increase in social uncertainty, all regions should break free of the administrative monopoly, enhance regional integration and development, and improve residents' health status by clustering public service supply.

Impact of logistics agglomeration on environmental quality in China: aggravating pollution effect or emission reduction effect?

Whether logistics agglomeration and pollution reduction can form a perfect combination in space is one of the important breakthroughs for the successful green transformation of the logistics industry in the future. This paper attempts to clarify the nonlinear change law of logistics agglomeration evolution on environmental quality in China and further clarify the interpretation of informatization and legalization factors on macro-regulatory functions. Based on the panel data of 31 provincial-level administrative regions in China from 2010 to 2020, the empirical verification is carried out by means of two-way fixed effects, quantile regression, instrumental variables, and spatial econometrics. The research finds that (1) there is an inverted U-shaped change trend between logistics agglomeration and environmental quality and the low-level logistics agglomeration period has a blocking effect on pollution emission reduction. However, from the starting point of the sample interval, representative regions such as Beijing and Shanghai gradually break through the bottleneck of logistics agglomeration in the form of a pyramid, which has an incentive effect on pollution emission reduction. The above conclusions are supported by robustness tests in six ways, including eliminating extreme data disturbance, eliminating the impact of the COVID-19, controlling the impact of other factors, pollutant sensitivity testing, avoiding the interference of pollution prevention and control, and correcting the endogenous bias of the model. (2) Further analysis of superimposed spatial effects and regulatory effects shows that regional spillover pollution has spatial dependence in both geographical and economic distribution. The effect of logistics agglomeration also produces an inverted U-shaped spatial spillover effect on the environmental quality of adjacent areas. Both informatization and legalization factors help alleviate the pollution increasing effect in the low-level logistics agglomeration stage. Under the regulatory effect of informatization, the arrival of the critical point for logistics agglomeration and emission reduction will be relatively delayed. Under the regulatory effect of legalization, the arrival of the critical point for logistics agglomeration and emission reduction will be relatively accelerated. (3) There is significant regional heterogeneity in the environmental effects of logistics agglomeration. Each region needs to "suit the remedy to the case" in combination with its own situation to break through the threshold of pollution reduction as soon as possible.

The spatial effects of rural toilet retrofitting investment on farmers' medical and health expenditure in China.

Background: China stretches across a vast area, and different geographical environments and economic and social development conditions, along with learning imitation and factor flow among participants can lead to two major spatial characteristics of toilet retrofitting investment: spatial heterogeneity and spatial correlation. Methods: This study contributes to explore this topic by assessing the spatial heterogeneity and spatial correlation of toilet retrofitting investment on farmers' medical and health expenditure based on the spatial econometric model. Results: (1) There are significant spatial agglomeration characteristics of both the toilet retrofitting investment and farmers' medical and health expenditure in China. (2) At the national level, the rural toilet retrofitting investment will influence the farmers' medical and health expenditure, and the effect on the local area is greater than on the surrounding areas. (3) After taking into account the differences in natural geographical environment and social and economic development, China is divided into four regions: east, central, west and northeast. In terms of spatial effects within different regions, the intensity of the impact of toilet retrofitting investment on local farmers' medical and health expenditure is in the order of central > eastern > western > northeast. The improvement of people's livelihood in the eastern and central regions by toilet retrofitting investment would lead to imitation by surrounding regions, thus reflecting spillover effects, while in the western region, toilet retrofitting investment would trigger fierce competition in related industries and factor markets, manifesting the competition effect. (4) As for the spatial effects across different regions, the toilet retrofitting investment produces spillover effects in all four regions, among which the intensity of the influence effect is the greatest in the central-western region, followed by the west-northeast, and the influence effect in the east-west is not significant. Discussion: The comprehensive promotion of rural toilet retrofitting should not only focus on investment in the western and northeastern regions, but also strengthen regional communication and cooperation to improve rural residents' health and quality of life.

Geographical disparities and determinants of infant mortality in Ethiopia: mapping and spatial analysis using EDHS data.

BACKGROUND: Infant mortality remains a public health challenge in Ethiopia. Exploring infant mortality will aid in tracking the progress toward achieving sustainable development goals. OBJECTIVE: The study aimed to explore the geographical variations and associated factors of infant mortality in Ethiopia. METHOD: A total of 11,023 infants from the 2016 Ethiopian Demographic and Health Survey (EDHS) data were extracted and included in the analysis. EDHS used a two-stage cluster sampling design with a census enumeration area as the primary sampling unit and households as the secondary sampling unit. Arc GIS software was used for spatial analysis using clusters for exploring geographical variations in infant mortality. A binary logistic regression was employed using R software to identify the significant determinants of infant mortality. RESULTS: The study revealed that the spatial distribution of infant mortality was non-random in the country. Infants whose mothers not receiving ANC (AOR = 1.45; 95%CI: 1.17, 1.79), not breastfed status (AOR = 3.94; 95%CI: 3.19, 4.81), poor wealth index (AOR = 1.36; 95%CI: 1.04, 1.77), male infants (AOR = 1.59; 95%CI: 1.29, 1.95), birth order of six or above (AOR = 3.11; 95%CI: 2.08, 4.62), small birth size (AOR = 1.27; 95%CI: 1.26, 1.60), birth spacing [(≤ 24 months (AOR = 2.29; 95%CI: 1.79, 2.92), 25-36 months (AOR = 1.16; 95%CI: 1.12, 1.49)], multiple births (AOR = 6.82; 95%CI: 4.76, 10.81), rural residence (AOR = 1.63; 95%CI: 1.05, 2.77) and regions [Afar (AOR = 1.54; 95%CI: 1.01, 2.36), Harari (AOR = 1.56; 95%CI: 1.04, 2.56), and Somali (AOR = 1.52; 95%CI: 1.03, 2.39)] were the determinants of infant death in Ethiopia. CONCLUSIONS: There is a great geographical disparity in infant mortality rates across regions. Afar, Harari, and Somali regions were verified as hot spot areas. ANC usage, breastfed status, wealth index, sex of the infant, birth order, birth size, birth spacing, birth type, residence, and region were the determinants of infant death in Ethiopia. Therefore, appropriate interventions need to be implemented in the hot spots to alleviate the risk factors for infant mortality.

Assessing the digital economy and its effect on carbon performance: the case of China.

With China's carbon neutrality target and the rapid growth of the digital economy, it is critical to understand how the digital economy can decouple economic growth from carbon emissions. This paper innovatively calculates the digital economy index in China from 2004 to 2019 and explores how the digital economy affects total factor carbon productivity (TFCP) and its spatial spillover effect. The empirical results indicate that (1) the development level of digital economy in eastern provinces is significantly higher than that in other provinces. (2) The digital economy positively promotes TFCP. Interestingly, digital industrialization has a more substantial effect on improving TFCP, while industry digitization has a weaker effect. (3) The digital economy not only helps improve the local TFCP but also has spatial spillovers to the surrounding areas and has the most prominent effect on the TFCP of the northern. (4) The digital economy affects TFCP through four channels industrial digital upgrading, human capital, market integration, and resource allocation. (5) The effects of the digital economy on TFCP exhibit significant heterogeneity in terms of time, region, and pollution degree. The findings of this study have important policy implications for promoting the transition to the digital economy and low-carbon development.