High Quantiles Research Articles

Does Climate Finance Really Affect Ecological Quality in Developing Countries? Fresh Evidence From the Method of Moments Quantile Regression Approach

ABSTRACTThis study investigated the impact of climate finance on the ecological footprint (EF) of 111 developing countries from 2002 to 2018 to determine its real effects on ecological quality. The study applied the method of moments quantile regression (MMQR) to address nonnormality, individual heterogeneity of the EF and outliers. Additionally, the connection between climate finance and the EF is revisited, considering recipient countries' income diversity and the nature of climate finance. In addition, the analysis is repeated by splitting the sample periods into 2002–2009 and 2010–2018, subject to COP15. The results indicate that climate finance has negative and significant impacts on EFs across all quantiles (Q0.25, Q0.5, Q0.75 and Q0.9), inferring that climate finance robustly improves the ecological quality of developing countries. These findings further imply that mitigation finance has a robust effect on improving ecological quality across all distributions. In addition, adaptation finance has heterogeneous effects on EFs, positively impacting ecological quality at higher quantiles. Moreover, the effects of climate finance on ecological quality depend on income heterogeneity, having a negative effect on the EF of middle‐income countries and an insignificant effect on low‐income countries. The results further showed that the positive effects of climate finance on ecological quality became stronger after COP15. The findings are robust to alternative methods. Policy implications are suggested based on the findings.

Dyslipidemia induced inflammation mediated the association between obesity and Osteoarthritis: a population-based study.

This study aims to evaluate the mediation effect of dyslipidemia induced inflammation on the causal associations between obesity and Osteoarthritis (OA). This cross-sectional study used data from the National Health and Nutrition Examination Survey (1999-2010). The association between general and abdominal obesity (exposure), OA (outcome) and mediators (total cholesterol, high-density lipoprotein, and C-reactive protein) was assessed using multivariate linear and logistic regression models and mediation analysis. A total of 23,308 participants were enrolled in this study, and 2,180 were diagnosed with OA. Participants with obesity were more likely to have OA (general obesity: OR = 2.508, 95%CI: 1.602, 4.197, P < 0.001; abdominal obesity: OR = 3.814, 95%CI: 3.242, 4.509, P < 0.001) than those without the obesity. High quantile of total cholesterol (OR:1.399; 95%CI:1.235, 1.257; P < 0.001), high-density lipoprotein (OR:1.644; 95%CI:1.443, 1.874; P < 0.001) and C-reactive protein (OR:1.952; 95%CI:1.707, 2.237; P < 0.001) increased the risk of OA when compared to lowest quartile. In the linear regression, the betas varied from 0.668 (95%CI: 0.635, 0.741; P < 0.001) to 0.693 (95%CI: 0.674, 0.712; P < 0.001), suggesting that individual with obesity had higher C-reactive protein levels. Additionally, total cholesterol and high-density lipoprotein were associated with C-reactive protein. Mediation analyses showed that the causal association of obesity with OA risk was mediated by high-density lipoprotein and C-reactive protein, with the mediation proportion ranging from 17.216 to 45.058%. Moreover, high-density lipoprotein to C-reactive protein path acting as serial mediators in the associations between obesity and OA (general obesity: β = 0.012; 95%CI: 0.009-0.014; abdominal obesity: β = 0.011; 95%CI: 0.008-0.014). The association between obesity and OA is partially mediated by systemic inflammation caused by dyslipidemia. Our study suggested anti-lipid therapy may be positive for obese individuals with OA.

The Moderating Roles of Economic Complexity in the Entrepreneurship‐Sustainable Environment Nexus for the Gulf Cooperation Council Economies

ABSTRACTThere are conflicting views on the effect of business and entrepreneurial activities on environmental degradation in developing economies. However, none of this study examines whether economic complexity can serve as a policy tool for mitigating the effect of entrepreneurial business activities on a sustainable environment. Economic complexity consists of the structural and economic transformation process from a simple production system to a more complex and innovation‐based one. It predicts the variations in income level and its impact on the choice of goods being produced in an economy. This study examines the moderating effect of economic complexity on the link between entrepreneurship and sustainable environment in Gulf Cooperation Council (GCC) countries from 2006 to 2020. It further examines the validity of the Entrepreneurial Environmental Kuznets Curve (EEKC). The study uses the Driscoll‐Kraay standard error fixed effect, Panels Corrected Standard Errors (PCSE), method of moment quantile regression and Dumitrescu–Hurlin causality that are robust to heteroscedasticity, cross‐sectional dependency and other pitfalls of least square estimating technique. The results validate the inverted U‐shaped EEKC hypothesis across all the quantiles. Economic complexity increases ecological degradation at the lower quantile levels, while it decreases environmental footprint at the upper quantiles. Furthermore, economic complexity moderates the detrimental impact of entrepreneurial activity on the environment at the higher quantiles. A two‐way relationship is established between entrepreneurial activity and the environment, while one one‐way connection from economic complexity to the environment was found. The study recommends that policymakers should encourage innovative rather than necessity entrepreneurs. Entrepreneurs should be encouraged to engage in business activities that are friendly toward preserving the ecological environment, and green innovative activities should be prioritised in their entrepreneurial activities.

Impact of treatment management on the hospital stay in patients with acute coronary syndrome

BackgroundThe length of hospital stay in patients with acute coronary syndrome (ACS) is crucial for determining clinical outcomes, managing healthcare resources, controlling costs, and ensuring patient well-being. This study aimed to explore the impact of treatment approaches on the length of stay (LOS) for ACS patients.MethodsA total of 7109 ACS cases were retrospectively recruited from a hospital between 2018 and 2023. Demographical baseline data, laboratory examinations, and diagnostic and treatment information of the included subjects were extracted from electronic medical records to investigate the factors contributing to extended hospitalization and further explore the impact of treatment management on the LOS.ResultsAdvanced age, female sex, and elevated levels of B-type natriuretic peptide, C-reactive protein and higher low-density lipoprotein cholesterol were identified as risk factors for extended hospitalization. At the 0.2–0.9 quantile of LOS, compared with the non-invasive group, the percutaneous transluminal coronary angioplasty group and the stent implantation group exhibited decreases in LOS of 0.37–2.37 days and 0.12–2.28 days, respectively. Stratified analysis based on diagnosis showed that percutaneous coronary intervention decreased hospitalization time in the high quantile of LOS but conversely increased it in the low quantile.ConclusionPercutaneous coronary intervention is important for reducing hospitalization duration, particularly for patients susceptible to prolonged stays. Early and assertive management intervention, incorporating elements such as lipid-lowering therapy, and anti-inflammatory agents, is essential for improving outcomes within high-risk groups.

Environmental technology to stimulate life expectancy: A deep dive into the role of PM2.5 and carbon emission

As the Latin American economies contend with improving public health while simultaneously dealing with ecological issues, understanding the determinant of life expectancy becomes imperative. This study explores the interaction among environmental technology, economic development, cleaner energy transitions, industrial growth, particulate Matter 2.5 (PM2.5), carbon emission, and their collective impact on life expectancy across Latin American nations. The research incorporates advanced econometric approaches comprising Mean Group (MG), Pooled Mean Group (PMG), and Method of Moments Quantile Regression (MMQR). The study’s outcome established that cleaner energy transitions, Gross Domestic Product (GDP), industrialization and environmental technologies significantly improve life expectancy, especially at higher quantiles. However, the outcome highlighted that PM2.5 and carbon emissions reduce life expectancy. Additionally, this study supports the unidirectional connection between environmental technology, economic development, cleaner energy transitions, industrial growth, life expectancy, and the bidirectional connection flowing from carbon emission PM2.5 to life expectancy. The study offers a roadmap for Latin America and global economies to invest in technology, cleaner power supply and industrialization to provide a route toward sustainable development and better public health that will eventually improve their citizens’ life expectancy.

Artificial Intelligence: Intensifying or Mitigating Unemployment?

The rapid development of Artificial Intelligence (AI) is simultaneously fostering a proliferation of novel job opportunities while rendering some traditional roles obsolete and specific skills outdated. Previous research has failed to consider the short-, medium-, and long-term variations in AI’s impact on unemployment, which may lead to an incomplete understanding of the AI-employment relationship. This paper examines daily data from January 4, 2013, to August 12, 2024, utilising advanced wavelet-based Quantile on Quantile Regression (QQR) methodology to assess AI’s impact on the Unemployment Index (UI) across quantiles and time scales, with a sample size of 2820 drawn from a larger dataset totalling 4241 observations. The conclusions reveal that AI generally positively impacts UI in the short term, especially with AI at 0.6-0.7 quantiles, as automation replaces workers faster than new job roles emerge and skills transform. However, in the medium term, positive and negative effects balance as new jobs and skills emerge through continuous industrial restructuring. In the long run, AI predominantly mitigates UI by further enhancing economic development, fostering skill upgrading, and facilitating market adjustments, but this result does not hold during AI at 0.7 quantiles and UI at the highest quantiles, such as Coronavirus Disease 2019 (COVID-19). Under new technological revolution and industrial transformation, we formulate China-specific suggestions to avert potential AI-induced unemployment crisis from short-term, medium-term, long-term, and sector-specific perspectives.

Unraveling the Nexus of Industrialization, Human Development, Democracy, Trade Openness, and Renewable Energy in EU Environmental Degradation

This study aims to unveil the effects of industrialization, human development, compliance with the rule of law, and renewable energy on CO2 emissions and the ecological footprint of consumption in EU countries over the 1990-2022 period. The empirical findings, based on the MMQR analysis, reveal that the magnitudes of coefficients between factors affecting CO2 emissions and the ecological footprint vary. Industrialization and human development are the main contributors to environmental degradation, while renewable energy use consistently mitigates environmental degradation across all quantiles. Trade openness also mitigates CO2 emissions in all quantiles with a diminishing trend, but the same correlation is only observed in the lowest quantile for the model with ecological footprint. Compliance with the rule of law has a statistically insignificant effect on the ecological footprint; however, in the lowest quantile of CO2 (0.1), the rule of law exacerbates CO2 emissions, whereas in the highest quantile, it has a mitigating effect. While industrialization and human development contribute to both dimensions of environmental degradation, the different impacts of trade openness and the compliance with the rule of law underscore the need for specific strategies in designing policies to mitigate CO2 and ecological footprints from a policy perspective.

Exploring the drivers of ecological footprint: Impacts of road transportation infrastructure, transport tax, and environment technologies

This study explores the dynamic effects of road transportation infrastructure, transport taxes, economic growth, trade openness, and environmental technologies on the ecological footprint using three quantile regression techniques: Simultaneous, Powell, and Method of Moments Quantile Regression (MMQR). These variables are selected for their significant influence on both economic outcomes and environmental sustainability, reflecting the interconnectedness of transportation systems, government policies, and technological advancements in shaping ecological impacts. Based on panel data from 19 European countries between 1995 and 2020, the results reveal that investments in road infrastructure and higher transport taxes contribute to reducing ecological footprint. At the middle and high quantiles, advancements in environment-related technologies further decrease the ecological footprint, whereas trade openness tends to worsen ecological quality. Importantly, the relationship between GDP and the ecological footprint follows an inverted U-shape, confirming the Environmental Kuznets Curve (EKC) hypothesis across all quantiles, which suggests that economic growth can support environmental sustainability in the long run. These findings are validated by robustness checks using fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and canonical cointegration regression (CCR) models. Key policy implications include the need for targeted investments in road infrastructure and transport tax strategies, tailored to national contexts, along with technology-driven strategies to curb environmental degradation. Lastly, the panel causality test reveals unidirectional causality from economic growth, road transportation infrastructure, and environment-related technologies to ecological footprint, highlighting their significance as short-term contributors to environmental improvement.

Elite university bachelor’s degree salary premium for master’s graduates: empirical evidence from China

ABSTRACT The labor market’s response to the signaling value of multiple qualifications (bachelor’s and master’s degrees) held by master’s graduates influences labor market efficiency and individual decisions to invest in education. Using data from the ‘Sample Survey of Chinese Higher Education Institutions’ conducted in 2017 and 2019, this study analyzes whether master’s graduates with bachelor’s degrees from elite universities earn salary premiums. The findings indicate that bachelor’s degrees from elite universities provide approximately a 12% salary premium for master’s graduates, attributable to both human capital and labor market signaling mechanisms. When accounting for individual human capital differences, the salary premium is approximately 9.1%. Furthermore, the empirical results show that these premiums are statistically significant only for master’s graduates from elite universities. The distribution of salary premiums exhibits a U-shaped trend, increasing from low to high salary quantiles. The signaling/screening mechanism’s salary premiums rise with starting salaries, while negative signaling effects are observed at lower quantiles.

Nurses' Perceptions and Behaviours Regarding Climate Change and Health: A Quantile Regression Analysis.

The aim of this study is to identify the factors associated with nurses' perceptions and behaviours related to climate change and health (PBCH) according to their PBCH levels. A cross-sectional study was used. This study included a sample of 499 Korean nurses and adhered to the STROBE checklist. Data were collected from March 23 to May 10, 2023. Quantile regression analysis was performed, and PBCH levels were measured using the Korean version of the Climate Health and Nursing Tool. Across all quantile groups, the experience of extreme weather events and awareness of climate change-coping facilitators were associated with PBCH. Differences were observed in factors associated with PBCH levels. Significant associations with PBCH were observed within the 75th percentile group, for having a religion, household income, and workplace climate friendliness. In the 25th percentile group, having a child, the number of sources for climate change-health-related information, and experience in setting climate change-health goals and strategies significantly influenced PBCH. We propose a differentiated strategy by elucidating the factors associated with high and low quantiles of PBCH levels. By verifying specific factors associated with PBCH levels, nurses can enhance their preparedness to respond to the health risks posed by climate change in their clients. Identifying common factors associated with all quantiles of nurses is important for establishing universal PBCH characteristics. Recognising the distinctions between high and low PBCH levels can aid in developing tailored nursing strategies to enhance PBCH among nurses. This study adhered to the STROBE guidelines. No Patient or Public Contribution.

Achieving carbon neutrality and SDGs: assessing roles of solar energy, government stability, and population aging in greenhouse gas emissions

ABSTRACT In recent years, solar energy (SOE) has become a popular source of green energy that can stimulate energy transition, reduce Greenhouse Gas Emissions (GHGE), and mitigate global warming. In addition, population aging and government stability can also influence GHGE levels. However, there is a lack of research studies on the environmental impacts of SOE and population aging on GHGE in top emitters. Therefore, this research aims to unveil the heterogeneous effects of SOE, population aging, and government stability on GHGE in top emitters from 1992 to 2020. This study employed the Method of Moments Quantile Regression (MM-QR) because it can focus on the entire distribution of GHGE disclosing heterogeneous impacts of variables on GHGE. The outcomes of the study disclosed that population aging decreases the GHGE across all quantiles. However, government stability exacerbates GHGE with a slightly decreasing trend across all percentiles. SOE, however, reduces the GHGE only at the higher quantiles, while on lower quantiles, it is positively linked with the GHGE. It shows the usefulness of SOE in reducing GHGE in countries with higher emissions. Economic growth has a positive impact on GHGE, with this impact intensifying from lower to upper percentiles. This indicates that economic development exacerbates environmental deterioration, and therefore, higher GHGE and increased development are closely linked. The study did not notice any significant impact of financial globalization on GHGE. Based on the findings, a policy framework is proposed to reduce GHGE for achieving carbon neutrality and SDGs.

Resource curse, energy consumption, and moderating role of digital governance: Insights from South Asian countries

This study investigates the relationships between the resource curse, energy consumption, and the moderating role of digital governance within the context of South Asian countries. By employing a robust analytical framework, the study delves into how digital governance can potentially mitigate the adverse effects of the resource curse while influencing energy consumption patterns. It employs Method of Moment Quantile Regression (MMQR) on south asian countries panel from 2003 to 2022. The findings report detrimental impact of natural resources rent on economic growth, confirming resource curse hypothesis in low and high growth countries. Digital governance has a positive and significant impact at middle and higher quantiles. The joint influence of natural resources rent, and digital governance is associated with lower economic growth. It imply that digital governance doest not decreases the negative effect of natural resources rent on economic growth. Energy consumption contributes to higher economic growth from lower to higher quantiles. The interaction of digital governance and energy consumption has significant and positive impact on higher quantiles, suggesting that digital governance enhances energy consumption efficiency. These findings suggest valuable policy suggestions.

Achieving environmental quality through stringent environmental policies: Comparative evidence from G7 countries by multiple environmental indicators

Compatible with the increasing public interest on climate change, countries have taken measures to combat climate change and support environmental sustainability. Considering this fact, this study investigates whether environmental measures, proxied by the environmental policy stringency (EPS) index, are efficient in achieving sustainability of environment in G7 countries as the leading economies; uses multiple environmental sustainability indicators, and applies quantile methods from 1991/Q1 to through 2020/Q4. The results show that (i) EPS curbs carbon dioxide emissions in France and the United States across all quantiles. Also, it has a declining effect in Germany and Italy at lower quantiles and in Canada at lower and higher quantiles; (ii) EPS declines ecological footprint in United States across all quantiles, while it curbs in Canada and Germany at lower quantiles as well as in Italy and United Kingdom at higher quantiles; (iii) EPS stimulates load capacity factor in France, United Kingdom, and United States across all quantiles and in Canada at higher quantiles; (iv) causal effect of EPS on the environment varies throughout quantiles; (v) the robustness of the results by quantile regression method is verified. Overall, the results reveal that the effect of EPS on environmental sustainability differentiates across environmental indicators, countries, and quantiles. In ensuring environmental quality, EPS is completely helpful in the United States, fully inefficient in Japan, and has a mixed effect in remaining G7 countries.

Impact of global financial and energy markets, uncertainty, and climate change attention on Bitcoin carbon footprint

Bitcoin mining places huge demands on energy systems and increases carbon emissions, which sequentially adds to the impact of climate change. This study investigates the impact of a series of factors on the Bitcoin carbon footprint (BCF). The overall effect of USD on reducing BCF is greater than that of stocks, bonds, and gold. The negative impacts of coal and natural gas on BCF are more pronounced at lower BCF quantiles, whereas renewable energy has almost entirely negative effects. Moreover, the uncertainty of economic and climate policies, energy and stock markets (EPU, CPU, EUI and VIX), as well as the climate physical risk index (CPR) have negative effects on BCF in most quantiles, especially in the lower and higher quantiles.

Profit produced by post-pandemic inflation: Evidence from an emerging economy

This paper focuses on the post-pandemic inflationary context, providing further details on how rising corporate profits contribute to the inflationary process in Türkiye. Using quarterly data from 2010 to 2022, we extend the existing literature by employing the Quantile ARDL method to assess the roles that both cost-push and demand-pull factors play in post-pandemic inflation. The chosen empirical strategy is motivated by the main objective of the study, as it allows us to quantify how the factors contributing to inflationary process differ when comparing periods of high inflation (higher quantiles) with periods of low inflation (lower quantiles). The empirical findings support the idea that the drivers of Turkish inflation are context-dependent, with specific causes emerging during inflationary episodes. The results show that cost-push factors, rather than demand-pull factors, are the main cause of the post-pandemic inflation surge in Türkiye. Our estimation results show that the coefficient for interest rates in Türkiye is only -0.42 %, while the corresponding figure for the profit share is 5.26 %, indicating that the effect of the profit share is 12 times greater than that of interest rate. We also find evidence of conflict and profit-driven inflation, confirming that the post-pandemic inflation surge in Türkiye is largely driven by cost-push factors and rising profits.

Unearthing the importance of energy transition, political globalization, and natural resources on environmental degradation for Turkey: The role of economic growth and urbanization

The switch from fossil fuels to renewable energy is at the center of the globally hunt for answers to climate change. However, each country's infrastructure and financial status are unique. The notion of energy transition is becoming more and more significant in this context, as it places emphasis on the efficiency of nations' energy systems and their readiness for the alterations in issue. Based on this, the study's goal is to look at how Turkey's political globalization and energy transition have affected the environment. In this context, the new quantile-quantile multivariate regression approach was used to examine the impacts on carbon emissions in a data set encompassing the period 1970–2020 of the innovative energy transition index, political globalization, economic development, and natural resource rents. This method makes it possible to analyze and verify the efficacy of the energy transition as well as the transition for varying emission levels. The energy transition lowers carbon emissions in all quantiles, according to the findings of the empirical assessments, although in high quantiles (high CO2 levels), the shift's pollution-reducing impact is more pronounced. Furthermore, the intermediate quantiles of carbon emissions are less affected by political globalization in terms of lowering emissions.

Exploring asymmetries in cryptocurrency intraday returns and implied volatility: New evidence for high-frequency traders

This paper aims to analyze the return-volatility relationship of Bitcoin and Ethereum across different return frequencies and all conditional quantiles of implied volatility, based on a unique 6.5 million observations. We employ the newly constructed Model-Free Implied Volatility (MFIV) of Bitcoin (BitVol) and Ethereum (EthVol) and use an asymmetric Quantile Regression Model (QRM) to capture the intraday asymmetric return-volatility relationship at different quantiles of the distribution of the dependent variable. Our findings show that the estimated coefficient using daily data is significant only at medium- to high-volatility regimes, while the estimated coefficients using high-frequency data are highly significant across all volatility regimes. Moreover, our results indicate that the asymmetry varies across frequencies and quantiles, with weak asymmetric effects at low quantiles and high frequencies, and strong asymmetric effects at high quantiles and low frequencies. This study provides new insight, especially for high-frequency traders.

Does fintech really matter for energy, economy and environment? From the lenses of SDG-7, SDG-8, SDG-13, COP27 and COP28

This study investigates the impact of fintech on economic development, energy transition and environmental well-being in OECD nations from 2005 to 2018 by utilizing MM-QR and CS-ARDL methods. Results reveal the different degree of positive impact of fintech on the said variables. In this regard, fintech plays a key role in planning, development and management of financial institutions and enhancing economic growth and development in the region across all the quantiles. Moreover, energy transition and green energy management get influence positively through technological involvement in the financial system. Lastly, the relationship between fintech and environment is moderately positive in the beginning and gets stronger in higher quantiles. Fintech facilitates environmental policy stringency, green finance and channelization of various financial sources towards environment well-being. It also effectively integrates economy, energy and environment towards attainment of sustainable development goal-7 (ensure affordable and clean energy), goal-8 (economic growth and development) and goal −13 (Climate challenges, concerns and action) and objectives of COP27 and 28. In light with the findings, several policy implications are suggested.

Uncovering the drivers of ecological footprints: A STIRPAT analysis of urbanization, economic growth, and energy sustainability in OECD countries

This study investigates the impact of human activities on environmental degradation, focusing on the roles of urbanization, economic growth, energy intensity and renewable energy within the STIRPAT framework. To this end, the study adopts the ecological footprint (EF) as the environmental indicator. Employing Panel Quantile Regression, the study analyzes data from 31 OECD countries spanning the period 2000–2021. The findings reveal that renewable energy consumption and urbanization exert significant negative influences on the EF, with urbanization proving more effective than renewable energy usage across all quantiles. Both economic growth and energy intensity contribute to environmental degradation, and the impact on the EF escalates with higher quantiles. Additionally, the causality test results demonstrate a two-way causal link among urbanization, economic growth, energy intensity, renewable energy use, and EF. Finally, based on the empirical results, this paper suggests that an energy revolution should be carried out to promote the sustainable use of energy. Meanwhile, the high-level urbanization is suggested to reduce the EF through the aggregation of living production to achieve sustainable development.

Uncovering time-, frequency- and quantile-based impacts of energy, fiscal policy instruments, and economic growth on sustainable development

ABSTRACT Hampering environmental deterioration and limiting global warming has become a significant task for policymakers at the global level in order to achieve sustainable development. Dozens of studies have questioned various policy instruments, but the role of fiscal policy instruments for sustainable development has not yet been extensively examined. Therefore, this study aims to investigate the impact of fiscal policy tools, economic development, and renewable energy (REN) utilization on sustainable development, represented by the load capacity factor (LCF). The study focuses on Germany from 1995Q1 to 2021Q4 using novel wavelet- and quantile-based estimation methods. The empirical evidence shows a time- and frequency-based dependency between fiscal policy tools, economic growth, REN utilization, and sustainable development. Economic growth and REN utilization enhance sustainable development through their positive impacts, especially at higher quantiles. The potential positive impact of REN utilization offers hope for ensuring sustainable development and preserving the ecology for the well-being of future generations. Despite the limited positive impact of a specific tax-based fiscal policy instrument, the overall effect of tax-based policy instruments on sustainable development is negative across all quantiles. Protection-based fiscal policy instruments, namely environmental protection expenditures, promote ecological sustainability in higher quantiles. These findings have significant implications regarding ensuring a sustainable future for German policymakers. In this regard, German policymakers should not rely on tax-based fiscal policies to improve ecological sustainability. Instead, they should consider promoting ecological protection expenditures to strengthen sustainable development.