How can local government capacity lift the 'resource curse'? A study from the perspective of industrial structure transformation.

Industrial transformation is crucial for sustainable urban development and economic security. Although more studies have analyzed the relationship between resource endowment and urban industrial transformation, they have failed to include the key factor of local government capacity in the analysis. Based on the panel data from 267 cities in China from 2003 to 2018, the study examines the impact of resource endowment on industrial transformation and the role of local government capacity in it by using linear models and panel threshold models. This study finds that resource endowment promotes the development of the secondary industry in urban, but hinders the development of the tertiary industry. There is a moderating effect of local government capacity that mitigates the lock-in effect of resource endowment on industrial transformation. This moderating effect demonstrates heterogeneity among cities with different levels of resource endowment and geographic locations, and the results are robust. Furthermore, this study concludes that under different local government capacity, the moderating effect of local government capacity on the relationship between resource endowment and industrial transformation is nonlinear, and it also finds that the stronger local government capacity is not the better.

Interactions of the CSF3R polymorphism and early stress on future orientation: evidence for the differential model of stress-related growth.

AIMS: This study aims to explore the concept of future orientation, which encompasses individuals' thoughts about the future, goal-setting, planning, response to challenges and behavioural adjustments in evolving situations. Often viewed as a psychological resource, future orientation is believed to be developed from psychological resilience. The study investigates the curvilinear relationship between childhood maltreatment and future orientation while examining the moderating effects of genotype. METHODS: A total of 14,675 Chinese adults self-reported their experiences of childhood maltreatment and their future orientation. The influence of genetic polymorphism was evaluated through genome-wide interaction studies (GWIS; genome-wide association study [GWAS] using gene × environment interaction) and a candidate genes approach. RESULTS: Both GWAS and candidate genes analyses consistently indicated that rs4498771 and its linked single-nucleotide polymorphisms, located in the intergenic area surrounding CSF3R, significantly interacted with early trauma to influence future orientation. Nonlinear regression analyses identified a quadratic or cubic association between future orientation and childhood maltreatment across some genotypes. Specifically, as levels of childhood maltreatment increased, future orientation declined for all genotypes. However, upon reaching a certain threshold, future orientation exhibited a rebound in individuals with specific genotypes. CONCLUSIONS: The findings suggest that individuals with certain genotypes exhibit greater resilience to childhood maltreatment. Based on these results, we propose a new threshold model of stress-related growth.

Thresholds to sustainability: Globalization's impact on the institutional quality-ecological footprint nexus in Africa.

This study explores how globalization influences the relationship between institutional quality and the ecological footprint in Africa. Utilizing dynamic panel threshold models with data from 49 African countries (2002-2022), we investigate how different types of globalization-economic, social, cultural, and political-affect this relationship. Our findings reveal that the impact of institutional quality on the ecological footprint varies significantly depending on globalization thresholds. Specifically, below certain thresholds, improved institutional quality increases the ecological footprint, whereas above these thresholds, it tends to reduce it. For economic globalization, the threshold is 53.510; for social globalization, 48.332; for cultural globalization, 28.446; and for political globalization, 69.663. These results highlight the need for targeted environmental policies that consider the specific effects of each globalization dimension to effectively manage Africa's ecological footprint. The study contributes to the literature by addressing the complex link between institutional quality and globalization and provides practical insights for policymakers to design more effective sustainability strategies in the African context.

A Bivariate Twin Study of Lifetime cannabis Initiation and Lifetime Regular Tobacco Smoking Across Three Different Countries.

Regular cigarette smoking and cannabis consumption are strongly positively related to each other, yet few studies explore their underlying variation and covariation. We evaluated the genetic and environmental decomposition of variance and covariance of these two traits in twin data from three countries with different social norms and legislation. Data from the Netherlands Twin Register, FinnTwin12/16, and the Minnesota Center for Twin Family Research (total N = 21,617) were analyzed in bivariate threshold models of lifetime regular smoking initiation (RSI) and lifetime cannabis initiation (CI). We ran unstratified models and models stratified by sex and country. Prevalence of RSI was lowest in the Netherlands and prevalence of CI was highest in Minnesota. In the unstratified model, genetic (A) and common environmental factors (C) contributed substantially to the liabilities of RSI (A = 0.47, C = 0.34) and CI (A = 0.28, C = 0.51). The two liabilities were significantly phenotypically (rP = 0.56), genetically (rA = 0.74), and environmentally correlated in the unstratified model (rC = 0.47and rE = 0.48, representing correlations between common and unique environmental factors). The magnitude of phenotypic correlation between liabilities varied by country but not sex (Minnesota rP ~ 0.70, Netherlands rP ~ 0.59, Finland rP ~ 0.45). Comparisons of decomposed correlations could not be reliably tested in the stratified models. The prevalence and association of RSI and CI vary by sex and country. These two behaviors are correlated because there is genetic and environmental overlap between their underlying latent liabilities. There is heterogeneity in the genetic architecture of these traits across country.

Mechanism analysis of rural residents' participation in green energy transition: A community-level case study in Nanjing, China.

Achieving a transition to green energy requires the government to adopt new policies on green industrial products and energy. Throughout this process, rural residents often face various challenges due to economic and other factors. However, some rural residents are motivated to participate in this transition due to the economic benefits of energy usage and rooftop photovoltaic (PV). This study takes a rural community in the outskirts of Nanjing, China, as an example and applies Granovetter's embeddedness theory and a threshold model to analyze the factors influencing rural residents' engagement in a fair transition to green energy. Research hypotheses are proposed accordingly. The results indicate that rural residents are influenced by multiple factors in the adoption process of rooftop PV projects, primarily encompassing economic and trust-related aspects. From an economic perspective, rural residents evaluate the viability of rooftop PV systems by considering the marketing strategies employed by PV enterprises and the governmental pressure to reduce carbon emissions. They make rational calculations to determine the return on investment, and only when the economic threshold is surpassed will they reach the anticipated level of participation. From the perspective of trust, rural residents' participation in rooftop PV projects is also influenced by trust factors. The level of trust that rural residents have in rooftop PV enterprises, governments, and community organizations plays an important role in their willingness to participate in the green energy transition. Based on these findings, the research paper concludes that local government should continue providing tailored public information and services to facilitate the progress of rooftop PV projects.

Converting estimated breeding values from the observed to probability scale for health traits.

Dairy cattle health traits are paramount from a welfare and economic viewpoint; therefore, modern breeding programs prioritize the genetic improvement of these traits. Estimated breeding values for health traits are published as the probability of animals staying healthy. They are obtained using threshold models, which assume that the observed binary phenotype (i.e., healthy or sick) is dictated by an underlying normally distributed liability exceeding or not a threshold. This methodology requires significant computing time and faces convergence challenges as it implies a nonlinear system of equations. Linear models have more straightforward computations and provide a robust approximation to threshold models; thus, they could be used to overcome the mentioned challenges. However, linear models yield estimated breeding values on the observed scale, requiring an approximation to the liability scale analogous to that from threshold models to later obtain the estimated breeding values on the probability scale. In addition, the robustness of the approximation of linear to threshold models depends on the amount of information and the incidence of the trait, with extreme incidence (i.e., ≤ 5%) deviating from optimal approximation. Our objective was to test a transformation from the observed to the liability and then to the probability scale in the genetic evaluation of health traits with moderate and very low (extreme) incidence. Data comprised displaced abomasum (5.1M), ketosis (3.6M), lameness (5M), and mastitis (6.3M) records from a Holstein population with a pedigree of 6M animals, of which 1.7M were genotyped. Univariate threshold and linear models were performed to predict breeding values. The agreement between estimated breeding values on the probability scale derived from threshold and linear models was assessed using Spearman rank correlations and comparison of estimated breeding values distributions. Correlations were at least 0.95, and estimated breeding value distributions almost entirely overlapped for all the traits but displaced abomasum, the trait with the lowest incidence (2%). Computing time was ∼3x longer for threshold than for linear models. In this Holstein population, the approximation was suboptimal for a trait with extreme incidence (2%). However, when the incidence was ≥6%, the approximation was robust, and its use is recommended along with linear models for analyzing categorical traits in large populations to ease the computational burden.

Comparing Sensitivity of Different Bee Species to Pesticides: A TKTD modeling approach.

Risk assessment for bees is mainly based on data for honey bees; however, risk assessment is intended to protect all bee species. This raises the question of whether data for honey bees are a good proxy for other bee species. This issue is not new and has resulted in several publications in which the sensitivity of bee species is compared based on the values of the 48-h median lethal dose (LD50) from acute test results. When this approach is used, observed differences in sensitivity may result both from differences in kinetics and from inherent differences in species sensitivity. In addition, the physiology of the bee, like its overall size, the size of the honey stomach (for acute oral tests), and the physical appearance (for acute contact tests) also influences the sensitivity of the bee. The recently introduced Toxicokinetic-Toxicodynamic (TKTD) model that was developed for the interpretation of honey bee tests (Bee General Uniform Threshold Model for Survival [BeeGUTS]) could integrate the results of acute oral tests, acute contact tests, and chronic tests within one consistent framework. We show that the BeeGUTS model can be calibrated and validated for other bee species and also that the honey bee is among the more sensitive bee species. In addition, we found that differences in sensitivity between species are smaller than previously published comparisons based on 48-h LD50 values. The time-dependency of the LD50 and the specifics of the bee physiology are the main causes of the wider variation found in the published literature. Environ Toxicol Chem 2024;43:1431-1441. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Heritability of cancers in Japanese population: Estimation from recent cohort data.

Cancers are genetically categorized into common diseases showing a so-called multifactorial inheritance except for rare familial cancers. And as a measure to estimate the strength of genetic factors in the multifactorial diseases, heritability (h2) is generally used. However, there have been few reports on the estimation of heritability for cancers. We calculated the heritability from the incidence in subject population and the familial recurrence rate in first-degree relatives of the affected for cancers quoting the data from a large-scale prospective cohort study by Hidaka et al. published in 2020. This is the first report for heritability of any cancers in Japanese population. The results showed that heritability of overall cancers in Japanese population is 0.064, which is much lower than Nordic population reported by Mucci et al. that was 0.33. For individual cancers, stomach cancer (h2 = 0.14), colorectum cancer (0.006), lung cancer (0.08) and uterine cancer (0.16) accounted for half of the total patients, and each heritability tends to be lower than previously reported for the European descent. The results of this study suggest that heritability of cancers varies greatly by ethnicity. And these results should be important in terms of cancer genetics and in the genetic counseling for cancers.

Describing the impact of psychological safety on risk prevention: A threshold model construction.

BACKGROUND: Like other things, psychological safety has a too-much-of-a-good-thing effect on the risk prevention process. There are warranted systematic and theoretical discussions on both positive and negative influences of psychological safety, which provide useful guides to handling potential risks for workers. OBJECTIVE: This study focuses on the psychological safety analysis of work safety for workers in high-risk industries through the construction of a theoretical model, illustrating that a higher level of psychological safety is not better. METHOD: This study explores the impact of workers' psychological safety on the potential risk of work safety by conducting a comprehensive analysis of relevant literature and employing inductive reasoning and analogy methodology. RESULTS: We systematically reviewed the research background and several hypotheses of psychological safety, described the relationship between psychological safety and risk prevention from three levels, and constructed the threshold initial, special, and extended model of psychological safety to reveal the importance of workers' psychological safety when handling potential risks. CONCLUSION: This research effectively describes the influence of high, moderate, and low levels of psychological safety on the risk prevention of work safety, which provides a psychological model guide to developing measures for the improvement of work safety management.

The Estimation of Genetic Parameters for Chronic Progressive Lymphedema and Body Traits in the Rhenish German Draught Horse.

Chronic progressive lymphedema (CPL) is a prevalent and progressive disease in Rhenish German draught horses. The objective of our follow-up study was to evaluate the heritability of this disease in Rhenish German draught horses using pedigree-based and genomic relationship matrices. We employed linear and threshold animal models. Models included the random animal effect and effects of breeding association, coat colour, sex, and age within sex, and farm-related factors, on CPL scores. In addition, we estimated heritabilities in models assuming censoring for data when horses were below an age of 1-15 years. The heritabilities of CPL scores across all ages were 0.595 ± 0.131 and 0.482 ± 0.105 in the threshold and linear animal model with pedigree-based relationship matrices, respectively. The restriction of data to horses with a minimum age at examination or accounting for censored data in younger animals showed an increase in heritabilities of CPL scores up to 0.788 ± 0.168 (threshold model) and 0.752 ± 0.153 (linear model) at an age of 7-8 years. Analyses including genomic relationship matrices yielded very similar estimates, but with smaller standard errors than pedigree-based analyses. Heritabilities in threshold models for CPL prevalence (CPL-bin-score) and the number of affected limbs (CPL-bin-sum) were 0.176-0.189 ± 0.061-0.064 and 0.375-0.433 ± 0.164-0.170, respectively. We were able to show moderately to highly positive genetic correlations between the CPL score and cannon bone circumference (0.529-0.825), height at withers (0.338-0.555), and skinfold thickness (0.241-0.517). Using the dichotomous trait for the CPL score and the genomic relationship matrix resulted in corresponding estimates of 0.868, 0.793, and 0.784, respectively. This study showed the great importance of additive genetic variation influencing the expression of chronic progressive lymphedema in Rhenish German draught horses. Therefore, further research is warranted to implement breeding programmes in a small breeding population that exploit the potential of additive genetic differences among animals for reducing the prevalence and severity of lesions of this incurable disease.

Is renewable energy development endangering power supply reliability?

The development of renewable energy is indispensable to promoting the low-carbon transition of power systems. Nevertheless, it also brings uncertainty to the reliability of power systems. Herein, the panel model and panel threshold model are established based on the provincial data in China from 2012 to 2020. The results reveal that the negative effect of renewable energy development (RED) on power supply reliability (PSR) is gradually lessening. If the development of renewable energy is a rational way, power supply reliability can be improved. Additionally, energy-exporting regions bear more risks of RED than energy-importing regions. If the coal prices are stable and natural disasters are manageable, the RED can enhance the PSR. However, if they are not stable or controllable, a high proportion of renewable energy in the power system could cause even more severe problems with PSR. Based on these critical results, some suggestions are made to promote the formation of a new power system.

Impacts of digital finance on energy efficiency: does environmental regulation matter?

The paper examines how digital finance affects energy efficiency in China using a dynamic panel model and data from 282 cities between 2011 and 2019. The study is based on the hypothesis which is related with digital finance, environmental regulation, and energy efficiency. The results indicate that: (1) Digital finance significantly improves energy efficiency, and this finding is consistent after several tests; (2) Digital finance has a positive effect on energy efficiency in non-resource-based cities, recession and regeneration resource-based cities, and old industrial base cities, but no significant effect on energy efficiency in growth and maturity resource-based cities and non-old industrial base cities; (3) Environmental regulation positively influences how digital finance affects energy efficiency; (4) The impact of digital finance on energy efficiency depends on the degree and tools of environmental regulation. This research offers valuable insights to local governments in China for promoting financial digitization and enhancing energy efficiency.

A dynamic panel threshold model analysis on heterogeneous environmental regulation, R&D investment, and enterprise green total factor productivity.

Environmental regulations are important means to influence manufacturing enterprise green development. However, there are two completely different conclusions both in theoretical and in empirical research, namely the "Follow Cost" theory and the "Porter Hypothesis". The nonlinear mechanism needs to be considered. Therefore, this study aims to explain the threshold impact of heterogeneous environmental regulations on enterprise green total factor productivity. Environmental regulations are divided into different sub-categories, then based on the panel data of 1220 Chinese manufacturing listed companies from 2011 to 2020, this paper uses threshold regression model to examine the impact of heterogeneous environmental regulations on Chinese manufacturing enterprise Green Total Factor Productivity. The empirical results show that: (1) Command-controlled, market-incentive and voluntary-agreement environmental regulation all have a significant nonlinear impact on enterprise Green Total Factor Productivity. (2) Enterprise R&D investment plays a threshold role in the impact. (3) There are industry and equity type differences in the impact process. This study focuses on the micro level of enterprises and tests the threshold mechanism, which make some theoretical complement to previous researches. The research results are not only beneficial for the government to propose appropriate environmental regulatory policies, but also for enterprises to achieve green growth through heterogeneous R&D investment.

Do institutions contribute to environmental sustainability? A global analysis using the dynamic spatial Durbin and threshold models.

There has been a recent surge in attention to the potential involvement of institutions in enhancing environmental quality. This research contributes to the ongoing debate by analyzing the spillover and nonlinear effects of institutions on the load capacity factor (LCF) in a sample of 100 countries between 2000 and 2019. The spillover effects are analyzed using the dynamic spatial Durbin model (DSDM), while the dynamic threshold model is implemented to estimate the nonlinear impacts of institutions. The Moran's I and Geary's C tests reveal a positive spatial autocorrelation for the LCF. The DSDM indicates the existence of positive direct and indirect (spillover) effects of political stability, control of corruption, and the rule of law on the LCF. Moreover, control of corruption has the highest positive influence on the environment. When conducting the threshold analysis, the locally weighted scatterplot smoothing curve indicates a nonlinear relationship between institutions and LCF, while the threshold test suggests a single threshold and two regimes. The dynamic panel threshold model reveals that government effectiveness and the rule of law positively affect the environment under both regimes. On the contrary, the positive effects of control of corruption, regulatory quality, and political stability are only observed under the upper regime. Furthermore, control of corruption has the highest positive environmental impact, albeit it needs more time to be achieved. The research emphasizes the importance of international collaboration and the design of both short- and long-term strategies to enhance institutional quality and, consequently, safeguard the environment.

Identifying and Predicting Delayed Mortality with Toxicokinetic-Toxicodynamic Models.

The prevalence of standardized toxicity testing in ecotoxicology has largely obscured the notion that toxicity is a function of time as well. The necessity of considering time is vividly demonstrated by observations of delayed mortality, that is, deaths continue to occur even when animals are no longer exposed to a toxicant. In this contribution, I explore to what extent toxicokinetic-toxicodynamic (TKTD) models from the framework of the General Unified Threshold model for Survival (GUTS) can capture delayed mortality, and to what extent this phenomenon can be predicted from short-term standard tests. I use a previously published data set for fluoroquinolones in Daphnia magna that shows strongly delayed mortality (using immobilization as a proxy for death). The model analysis shows that the GUTS stochastic death models can capture delayed mortality in the complete data set with a long recovery phase, but that the delayed effects would not have been predicted from a 2-day standard test. The study underlines the limited information content of standard acute test designs. Toxicokinetic-toxicodynamic modeling offers a handle on the time aspects of toxicity but cannot always be relied on to provide accurate extrapolations based on severely limited standard tests. The phenomenon of delayed toxicity requires more structured study to clarify its prevalence and impact; I discuss several avenues for further investigation. Environ Toxicol Chem 2024;43:1030-1035. © 2024 SETAC.

Economic growth effects of public health expenditure in OECD countries: An empirical study using the dynamic panel threshold model.

Background: Member countries of the Organization for Economic Co-operation and Development (OECD) have experienced a downward trend in capital and macro investment returns. Countries rely on investments in healthcare and health-related sectors to ensure continuous input and an efficient labor market. Public healthcare coverage is a social welfare policy implemented by governments, which contributes to improving human capital quality and ensuring stable economic growth. Methods: This study employs a method that combines theoretical modeling and empirical testing examining 33 OECD countries from 2001 to 2017. We first construct a nonlinear dynamic panel threshold model to examine the impact of public health spending on economic growth. We then employ the model to empirically analyze the threshold effect of public health expenditure on economic growth, validating the effectiveness of our theoretical model. Results: When the level of household consumption is below the 9.63 threshold, the effect of public health expenditure on economic growth is significantly negative (p < 0.1); however, when consumption exceeds the 9.63 threshold, the effect becomes significantly positive (p < 0.05). Similarly, when employee wages are below the 10.57 threshold, the effect of public health expenditure on economic growth is significantly negative (p > 0.1), and it becomes significantly positive when it exceeds 10.57 (p < 0.5). Finally, when the level of physical capital investment falls below the 8.73 threshold, the effect of public health expenditure on economic growth is significantly negative (p < 0.5), and it becomes significantly positive when it exceeds 8.73 (p < 0.5). The positive impact of public health expenditure on economic growth gradually strengthens as household consumption, employee wages, and per capita physical capital investment continue to rise. Conclusions: In an economic environment with higher household consumption, employee wages, and physical capital investment, public health expenditure will significantly promote economic growth.

Mechanistic analysis of the sub chronic toxicity of La and Gd in Daphnia magna based on TKTD modelling and synchrotron X-ray fluorescence imaging.

The release of lanthanides (Ln) into the environment has increased in recent decades due to their expanding applications in society. Studying their toxicity in aquatic ecosystems is urgent and challenging, with contradictory evidence presented in the literature. This study compared the biodistribution of La and Gd in Daphnia magna exposed to sub-chronic conditions and developed the first Toxicokinetic-Toxicodynamic (TKTD) model for these lanthanides with this model crustacean. D. magna were initially exposed for 7 days to concentrations close to the LC50 of La (2.10 mg L-1) and Gd (1.70 mg L-1). After exposure, half of the live daphnids were introduced in a clean media to allow depuration over 24 h, while the other organisms were directly prepared for synchrotron imaging measurements. Synchrotron X-ray fluorescence analysis revealed that metal distribution in the organisms was similar for both La and Gd, predominantly localized in the intestinal tract, even after the depuration process. These results indicate that ingested metal can adversely affect organisms under sub-chronic exposure conditions, highlighting the importance of using nominal concentrations as a more suitable indicator of metal bioavailability for risk assessment. The General Unified Threshold Model of Survival (GUTS) TKTD framework, in its reduced form (GUTS-RED), was developed for La and Gd using dissolved and nominal concentrations. D. magna were exposed for 7 days to concentrations from 0.5 to 5 mg L-1 of La or Gd and mortality monitored daily. The mechanistic model revealed a faster toxicokinetics for La than Gd and a higher toxicity for Gd than La in the organism. This study confirmed, despite similar chemical properties, the variation in both toxicity and toxicokinetics between these two metals.

The impact of FDI on energy conservation and emission reduction performance: A FDI quality perspective.

According to the climate emission reduction commitment of the Paris Agreement, all countries are actively seeking a new path of energy conservation and emission reduction, and trying to "bend downward" the global greenhouse gas emission curve. For China's carbon peak before 2030 and carbon neutral target before 2060, explore whether FDI can reduce China's energy consumption and carbon emissions. From the new research perspective of FDI quality, this paper explores the potential ways to improve regional energy-carbon emission performance (ECEP), and applied dynamic threshold effect and two-stage least squares for validation. The specific results are as follows: FDI quality improvement can have a significant positive impact on regional ECEP.The development level of renewable energy, the optimization of industrial structure and the enhancement of green innovation ability can positively regulate the impact of FDI on energy-carbon emission performance. At the same time, the results of the dynamic panel threshold model demonstrate that with the economic growth pressure of local governments decreases and the fiscal decentralization increases, the role of FDI quality in promoting the ECEP could be stronger. The influence of FDI quality on ECEP has regional heterogeneity, and the influence of FDI quality on ECEP is regional heterogeneous, and the influence of FDI quality on ECEP is more significant in inland and midwestern regions than in coastal and eastern regions. This study provides experience for FDI to formulate the quality assessment system and formulate foreign investment policy.

Economic level, environmental regulation, and new energy industry development.

Using panel data of 30 provinces and new energy (NE)-listed enterprises in China from 2011 to 2020, this paper uses basic model to research the impact of various environmental policies in China on NE industry development firstly. Then, using economic level as a threshold variable, a threshold model was constructed to research the impact of economic level on the relationship between environmental regulation and NE industry development. The research results show that firstly, various environmental policies in China have significantly promoted the development of the NE industry. This is mainly manifested in two aspects. One is environmental regulations significantly increased the NE industry output value and profit, the other is environmental regulations enhanced the NE industry growth potential. Secondly, the regional economic level has a significant impact on the relationship between environmental regulations and NE industry development. The promotion effect of environmental regulations on NE industry development depends on the regional economic level. When the regional economic level exceeds the threshold, the promoting effect of environmental regulations on NE industry development significantly increases. The reason is that a weak economic foundation will affect investment in the NE industry. Insufficient capital investment will inevitably seriously hinder the development of the NE industry. Thirdly, residents' education status, financial support, and NE industry agglomeration degree have a positive impact on the development of the NE industry, while population size has no significant impact on NE industry development.

Can digitalization effectively promote green energy efficiency? The linear and nonlinear relationship analysis.

In light of the integration of digitalization and the energy revolution, digitalization can be integrated into the energy industry to develop energy-saving technologies and improve resource allocation efficiency. On the basis of 2013-2019 Chinese provincial panel data, this paper measures the level of green energy efficiency based on the super-EBM-DEA model and analyzes the linear relationship, nonlinear relationship, and potential mechanism between digitalization and green energy efficiency. The findings indicate that (1) overall, both China's digitalization and green energy efficiency formed a steady upward trajectory during the sample period. Digitalization showed a spatial characteristic of extending and spreading from the eastern region to the central and western regions. Green energy efficiency was characterized by obvious regional heterogeneity. (2) Progress in digitalization has a significant driving effect on green energy efficiency. Subdimensional analysis shows that this driving effect mainly comes from digital development and digital transactions. (3) The impact of digitalization on green energy efficiency presents a threshold effect of economic agglomeration (with a threshold of 0.0257 and a marginally increasing, positive driving trend) and population agglomeration (with a threshold of 4.2750 and a marginally decreasing, positive driving trend). (4) Decomposing changes in green energy efficiency into scale efficiency and pure technical efficiency, this study shows that pure technical efficiency gains due to digitalization are the main driver of green energy efficiency improvements. Finally, some specific policy recommendations are proposed.