Health-led growth hypothesis and health financing systems: an econometric synthesis for OECD countries.

Introduction: This study investigates the Health-Led Growth Hypothesis (HLGH) within OECD countries, examining how health expenditures influence economic growth and the role of different health financing systems in this relationship. Methods: Utilizing a comprehensive analysis spanning 2000 to 2019 across 38 OECD countries, advanced econometric methodologies were employed. Both second-generation panel data estimators (Dynamic CCEMG, CS-ARDL, AMG) and first-generation models (Panel ARDL with PMG, FMOLS, DOLS) were utilized to test the hypothesis. Results: The findings confirm the positive impact of health expenditures on economic growth, supporting the HLGH. Significant disparities were observed in the ability of health expenditures to stimulate economic growth across different health financing systems, including the Bismarck, Beveridge, Private Health Insurance, and System in Transition models. Discussion: This study enriches the ongoing academic dialog by providing an exhaustive analysis of the relationship between health expenditures and economic growth. It offers valuable insights for policymakers on how to optimize health investments to enhance economic development, considering the varying effects of different health financing frameworks.

A user-friendly method for estimating discrete choice land-use model in a panel data setting.

Land-use modeling stands as a pivotal tool in shaping sustainable development policies. With the rapid advancement of remote-sensing technology and the widespread adoption of satellite imagery-based land cover products, these datasets have emerged as primary sources for understanding land-use dynamics due to their high spatial and temporal resolutions. Yet, it remains challenging to effectively integrate such rich panel data into nonlinear econometric land-use models. This paper introduces a method to seamlessly incorporate land cover panel data into econometric models, enabling comprehensive utilization of temporal information within a single framework.-By capturing dynamic land-use patterns, the method enhances prediction accuracy while mitigating issues such as autocorrelated error terms commonly encountered in panel data analysis.-The method is straightforward to implement and applicable to many nonlinear models, making it particularly suitable for datasets with large sample sizes.

The impact of national savings on economic development: a focused study on the ten poorest countries in Sub-Saharan Africa.

The purpose of this study is to examine the impact of national savings on economic development, as measured by the Human Development Index (HDI), Inequality-adjusted HDI (iHDI), and Multidimensional Poverty Index (MPI), in ten of the poorest countries in Sub-Saharan Africa. The study employs a sequential Generalized Method of Moments (GMM) analysis to address potential endogeneity issues and account for the dynamic nature of the relationships, covering the period from 2009 to 2019. The findings reveal a complex relationship between national savings and the selected development indicators. While national savings exhibit positive impacts on HDI and iHDI, the results are not consistently statistically significant across all the sequential models. However, the analysis suggests that national savings have a positive influence on reducing multidimensional poverty, as measured by MPI, particularly when effectively channeled into productive investments. The study also highlights the significant positive impact of government expenditure and foreign direct investment (FDI) on human development, underscoring the importance of strategic public investments and foreign capital. The results suggest that while national savings are crucial, their effective utilization is essential for enhancing human development indices. Strategic investments in public goods and foreign capital are also important. The mixed effects of inflation and official development assistance (ODA) emphasize the need for stable economic policies and effective utilization of foreign aid. The modest positive impact of institutional quality suggests that improvements in governance and institutional frameworks can contribute to human development. The findings underscore the need for policies promoting financial inclusion, efficient public expenditure, foreign direct investment, and stable macroeconomic conditions to leverage national savings for economic development. The study's findings provide valuable insights for policymakers in Sub-Saharan Africa, highlighting the need for comprehensive strategies that leverage national savings, public expenditure, and foreign investment to drive sustainable economic development and poverty reduction.

A synthetic approach to the Holiday Climate Index for the Mediterranean Coast of Türkiye.

Climate change affects the comfort level of tourists visiting coastal areas. Researching these impacts is important for a more comprehensive understanding of climate change and for developing effective adaptation solutions. Considering this fact, the study derived the Holiday Climate Index (HCI: Coast, HCI: Urban, and HCI: Combined) in the Mediterranean coastal provinces of Türkiye from 1976 to 2020. Utilizing the derived indices, the effects of climate-related holiday comfort on the number of tourist arrivals as well as on overnight stays between 1976 and 2020 were examined by panel data analysis. The study examined how comfort patterns could change during the period 2026-2050 under the pessimistic RCP8.5 scenario. It was detected that the comfort level significantly and positively affects the number of arrivals and overnight stays of tourists. Besides, comfort levels were found to deteriorate in the period 2026-2050 compared to the reference period, 1976-2020. As the comfort conditions get worse, the number of tourist arrivals and overnight stays is expected to decline in the future. It is envisaged that the results of the study can be useful for tourists, tourism professionals, operators, other stakeholders, and policymakers.

Differences in competitors' market influence due to market structure: Evidence from Japanese gambling market.

This study investigates how differences in the market structure between the Japanese horse racing and Keirin1 racing markets affects the influence exercised by high-turnover operators (major operators) in both markets on low-turnover operators (minor operators) in those markets.2 In the horse racing market structure, there are few competitors, and the difference in turnover3 between major and minor operators is large. In contrast, in the Keirin racing market structure, there are many competitors, and the difference in turnover between major and minor operators is small. Panel analysis results show that in horse racing, operators with low turnover are significantly affected by those with high turnover, while in Keirin racing, operators with low turnover are less affected by competitors with high turnover. The results not only indicate that firms are affected differently by competitors due to the market structure but also suggest that this has an impact on market segmentation policies and firms' marketing efforts.

Reassessing determinants of urban energy intensity in China: insights from controllable and uncontrollable factors.

This study adopts a new approach to reassess the factors influencing urban energy intensity in China. Initially, the factors impacting energy intensity are classified into controllable and uncontrollable categories. Subsequently, employing a single-factor multi-stage method combined with the Adaboost method, 289 Chinese cities are categorized based on uncontrollable factors to eliminate the influence of inherent differences on energy intensity. Finally, panel data regression analyses are conducted using data from 289 Chinese cities between 2005 and 2016, individually for each city type, to evaluate the extent to which controllable factors contribute to energy intensity. The findings indicate that (1) heightened energy prices, an increased share of electricity consumption, and a greater proportion of centralized heating significantly influence the reduction of energy intensity across all city types; (2) to optimize energy consumption, each city type should adopt specific strategies. For instance, cities located in resource-rich heating regions with low economic outputs can reduce their energy intensity by increasing electricity consumption, while cities with high economic outputs can decrease their energy intensity by increasing natural gas consumption. The findings of this study carry substantial implications for the Chinese government in shaping targeted energy policies tailored to different city types.

Carbon pricing and aggregate macroeconomic performance in the Eurozone: a contribution to the climate policy debate using the EU ETS and Macroeconomic Performance Index.

This article contributes to the carbon pricing debate by providing new evidence on the aggregate macroeconomic effect of the European Union Emissions Trading Scheme (EU ETS) in the Eurozone. To this end, a novel macroeconomic performance index is created to capture the overall economic performance of the Eurozone countries. The index is a weighted aggregation of key macroeconomic variables-GDP growth rate, inflation rate, employment rate, exchange rate, and long-term inflation rate-for the 19 member countries of the group. The effect of the EU ETS on this macroeconomic performance index is then empirically examined while controlling for the effects of physical capital accumulation, human capital accumulation and regulatory quality. A panel framework covering the period 2005-2022 is set up to achieve this objective and the relationship is examined using panel method of moments quantile regression with fixed effects, as well as fixed and random effects regressions of Driscoll and Kraay. A number of important revelations are made. Firstly, the behavior of the macroeconomic performance index constructed clearly reflects the economic reality of the Eurozone, with downward spikes visible in periods corresponding with the economic crisis of 2007-2009, the Eurozone debt crisis of 2010/2011, the aftermath of the financial crisis of 2016, and periods around the outbreak of the Coronavirus (COVID-19) pandemic. Hence, a case is made for the use of the macroeconomic performance index as a superior aggregate measure of the overall economic performance in empirical research. Secondly, a statistically significant negative effect of the EU ETS on aggregate macroeconomic performance in the Eurozone is confirmed. This shows that there are significant economic costs associated with the use of carbon pricing as a means of lowering pollution. Thirdly, the findings further show that the negative impact gradually decreases (in absolute values) from lower to higher quantiles. Overall, higher carbon prices cause greater economic disruption when macroeconomic performance is relatively poor but have less damaging effect when aggregate economic performance is relatively strong. Policy recommendations based on the study findings are also provided.

Empirical Analysis of Energy Consumption and Economic Growth in Post-Soviet Eurasia: Do They Matter for Foreign Policy?

This study aims to evaluate the relationship between renewable and non-renewable energy consumption and economic growth in post-Soviet Eurasian countries by employing panel data from 15 countries from 1996 to 2018. The results reveal that the contribution of renewable energy consumption (REC) to economic growth is greater than non-renewable energy consumption. The overall findings imply that the transformation of energy consumption from non-renewable to renewable offers environmental advantages and growth opportunities. Furthermore, the transition to renewables may also expand the range of foreign relations policy options available for these countries, which, in turn, might contribute to a better alignment with evolving global regimes. Transition demands towards the long-term sustainability of global energy sources put pressure on countries to expand their domestic policy efforts and join international cooperation efforts. Therefore, post-Soviet Eurasian countries should develop strategic policy mechanisms and reforms designed to accelerate investments in renewable energy technologies.

Estimating the effect of socio-economic factors on infant mortality rates in Latin America between 2000 and 2019: a panel data analysis.

OBJECTIVES: Infant mortality is a crucial indicator of socio-economic development, reflecting the conditions in which children are born and raised. Despite notable reductions in Latin America, infant mortality rates remain relatively high compared to other regions worldwide. By understanding the socio-economic factors that influence infant mortality, we not only uncover immediate causes of infant deaths but also shed light on broader socio-economic and healthcare disparities contributing to the burden of disease. This study analyzes the impact of socio-economic factors on infant mortality rates in Latin America from 2000 to 2019, estimating the speed and magnitude of the response of infant mortality rates to changes in specific socio-economic factors. STUDY DESIGN: Longitudinal panel study. METHODS: Panel data regression models were used to examine the influence of specific socio-economic factors on infant mortality rates in Latin America. Additionally, impulse response functions estimated by local projections were used to estimate the speed and magnitude of the impact of socio-economic factors on infant mortality rates. RESULTS: The results highlight the importance of factors such as healthcare expenditure, female literacy, public expenditures on education, maternal mortality, physician density, total fertility rate, and tuberculosis incidence as significant determinants of infant mortality rates in the region. CONCLUSION: This study adds to the existing literature by offering empirical evidence on the association between these socio-economic factors and infant mortality in Latin America. It also provides a foundation for future research that investigates specific cases within Latin America and examines the variations of these socio-economic factors within those countries.

Impact of COVID-19 on negative body image: Evidence based on social media data.

Body experiences and conditions bear close relations to social development and human well-being. However, no consensus has been reached regarding the impact of coronavirus disease 2019 on negative body image. Investigating a reliable relationship between COVID-19 and negative body image, we developed a dictionary of negative body image to obtain panel data on body image for 31 Chinese provinces/municipalities/autonomous regions. We compared negative body image before and after the pandemic and explored the impact of pandemic severity. The prevalence of negative body image decreased following the outbreak and remained at a relatively low level for two years. After controlling regional and temporal effects, we verified epidemic severity as an important predictor of the decline in negative body image. The findings suggest that the public is likely to accept their physical appearances during lockdown due to changes in lifestyle and the fear of mortality. This research has important implications for gaining insights into the dynamic transformation of public negative body image under the influence of catastrophic public health events.

Economic incentive in enhancing community waste separation and collection: A panel data analysis in China.

While incentive mechanisms have been proven to motivate residents to separate their waste, empirical research is still needed to determine whether this separation behaviour could be maintained over time. The main objective of this paper is to investigate waste separation management activities in the city of Dongying, China, as a case study to clarify how local community citizens' waste separation participation and recycling activities change over time cross-sectionally under the influence of an economic incentive mechanism - PS. This study used least square dummy variable analysis to investigate local waste separation behaviour in 98 communities over 22 months. Results showed that community resident waste participation and recycling behaviour tend to grow in the early stages and gradually show saturation without growth in the middle and late stages. This result implies limitations to the incentive mechanism, such that it could only motivate a part of residents to participate in waste separation; for those unaffected by financial incentives, it was suggested that educational or compulsory means be used to make them separate their waste.

Determinants of ecological footprint in European countries: Fresh insight from Bayesian model averaging for panel data analysis.

This study examines the determinants of the ecological footprint of production in European countries from 1992 to 2020. Using partial and semipartial correlation analyses and Bayesian Model Averaging (BMA) approach for the first time, the research identifies key variables affecting ecological footprint. Using Bayesian methods, posterior inclusion probabilities (PIPs) were calculated for each variable's coefficient estimates, revealing their relative importance. Biocapacity, energy consumption, industrialization, financial development, life expectancy, and globalization displayed notably high PIPs, indicating their strong influence on the ecological footprint. In addition, the study employs cointegration tests to examine the long-run relationship between ecological footprint and explanatory variables. The results indicate significant cointegration between these variables across panels, supported by various test statistics. In the Weighted Pooled DOLS estimation, biocapacity, energy consumption, and life expectancy significantly influence the ecological footprint, while industrialization, financial development, and globalization exert a comparatively smaller impact. Researchers and policymakers should consider these determinants for effective sustainable development planning. These findings underscore the intricate interplay of factors shaping the ecological footprint and offer insights for effective policy interventions towards sustainable development.

Can aging population affect economic growth through the channel of government spending?

The demographic transition toward an aging society is a global phenomenon. An increase in the aging population directly challenges the government positions and public expenditures as it directly affects a country's aggregate demand and, thus, the country's income level. This paper investigates the impact of an aging population on the size of government spending. Using an updated dataset of 87 countries from 1996 to 2017, we study the aggregate level and each composition of government expenditures. Furthermore, we investigate whether the aging population influences the allocation of government spending toward different categories and economic growth changes. The paper uses the generalized method of moment (GMM) model for the dynamic panel data analysis to address the endogeneity problem. Our main findings suggest that an increase in the old-age population significantly induces higher aggregate government spending but only in developed countries and in particular on the spending in the social protection and environment categories. However, the aging society leads to lower government expenditure on education. Other critical findings reveal that changes in some compositions of government spending toward cultural expenditures impact growth slowdown, while an allocation toward education spending positively impacts economic growth.

Capital structure determinants across sectors: Comparison of observed evidences from the use of time series and panel data estimators.

This comparative study is an attempt to explore the determinants of capital structure for Malaysian firms listed in various sectors level. Within the framework of traditional and moderate dynamic capital structure theories, the key determinants such as fixed assets, current assets, return on equity, size, earning per share and total assets are tested in relation to the debt-equity ratio. The large-scale study entails data collected from 551 listed firms of Bursa Malaysia main market over 12 years period i.e. 2005-2016. Notably, this study combines Time Series econometrics with Panel Data analysis to enhance methodological robustness. Moreover, the comparative analysis approach is designated to recognize the most persistent capital structure determinants. In the first place, the Multiple Regression analysis (MRA) is selected as a baseline estimation method. Subsequently, the Auto Regression Distributed Lag model (ARDL), the Panel Data Static models, and Dynamic model via the Generalized Method of Moments (GMM) are employed to identify the capital structure determinants for the firms listed at Bursa Malaysia. The outcomes are surprising and indicate that the entire market is primarily controlled by the studied determinant total assets, which is significant in both construction and property sectors through MRA, ARDL, and GMM analysis. Technically, the significant role of tangibility and the existence of speed of adjustment across sectors imply that the Dynamic Capital Structure is the most prominent among all, followed by the Dynamic Trade-off theory.

Analyzing the effects of energy productivity: the case of European Union countries.

The surge in fossil fuel consumption, culminating in global warming and climate change, compels nations to implement protective measures. Consequently, the concepts of "sustainable growth" and the "green economy" have gained prominence in response to heightened environmental consciousness. In light of these imperatives, nations have embarked on the formulation of sustainable and environmentally conscious policies, with the dual objective of safeguarding the environment and fostering economic growth. These factors have collectively contributed to the growing significance of energy policies within European nations, spurring a burgeoning momentum in research areas pertaining to energy efficiency and energy productivity. While extant literature has demonstrated the positive environmental impact of energy productivity, there exists a paucity of research pertaining to its economic implications. Energy productivity, defined as achieving equivalent or greater output with reduced energy consumption, bears the potential to influence economic output, thereby exerting cascading effects on various facets of the economy, including growth and exports. The principal aim of this study is to highlight that the augmentation of energy productivity can yield not only environmental advantages but also economic benefits. To achieve this objective, we conduct econometric analyses on panel data spanning the years 2000 to 2020 across the 27 member states of the European Union. Specifically, we explore the effects of energy productivity on diverse economic parameters, encompassing economic growth, high technology exports, medium and high technology exports, total exports, and trade volume. Employing the Driscoll-Kraay standard errors estimator, our findings evince that energy productivity exerts statistically significant and positive influences on economic growth, medium and high technology exports, total exports, and trade volume.

Effects of depression on medication adherence in HIV/AIDS patients: Korea HIV/AIDS cohort study.

BACKGROUND: The number of people with HIV/AIDS has consistently increased in Korea since the first case of HIV/AIDS infection was reported in 1985. The depressive symptoms of patients with HIV/AIDS may lead to medication non-adherence. This study sought to investigate the cross-sectional and longitudinal association between depression and antiretroviral treatment adherence in the Korean HIV/AIDS population. METHODS: We included participants of the Korea HIV/AIDS cohort study between 2009 and 2017. All information was collected at the enrollment and every annual visit, including sociodemographic characteristics, health-related behaviors, HIV/AIDS infection-related factors, depression score, and frequency of skipped medication. We performed a cross-sectional analysis of 601 participants registered between 2009 and 2017. Longitudinal data were evaluated by panel regression analysis in 515 patients who registered from 2009 to 2013. RESULTS: In cross-sectional analysis, the HIV/AIDS patients with depressive symptoms were more likely to be non-adherent (adjusted OR = 0.52, 95 % CI 0.34, 0.79, p = 0.002). Medication adherence was significantly associated with a health-related lifestyle; the adjusted odds ratio of the non-smoking and non-drinking group was 1.75 (95 % CI 1.05, 2.90, p = 0.031). The longitudinal panel regression model revealed a significant negative impact of depression on medication adherence (adjusted OR = 0.50, 95 % CI 0.30, 0.84, p = 0.009). Non-smoking and non-drinking participants were 2.31 times more likely to adhere to antiretroviral treatment (95 % CI 1.29, 4.15, p = 0.005). CONCLUSIONS: Our finding of depression and lifestyle modifications being significant contributors underscore the importance of proactive interventions to optimize the treatment outcomes of PLWH.

Preventable mortality in the Russian Federation: a retrospective, regional level study.

Background: Avoidable mortality, including both treatable and preventable deaths, is frequently used as an indicator of health system performance. Whilst the term treatable mortality refers to deaths that might be averted by medical interventions, preventable mortality generally reflects the impact of system-wide health policies. The concept of preventable mortality has not been evaluated extensively in the Russian Federation, particularly at the regional or sub-national (oblast) level. Methods: We calculated total preventable mortality as well as individual rates for males and females in each oblast using data from the Russian Fertility and Mortality Database (RusFMD) and computed the contributions of specific preventable causes of death to the overall rates. We also evaluated the relationship between preventable mortality and its main correlates during the years 2014-2018 using panel fixed effects modelling with variables that reflected both, behavioural risk factors and access to health care. Findings: Overall preventable mortality in the Russian Federation has been on a downward trend. Whilst 548 preventable deaths per 100,000 person-years were reported in the year 2000, only 301 per 100,000 person-years were reported in 2018. Whilst mortality due to cancer, cardiovascular, and alcohol-related diseases has declined (albeit unevenly) amongst both males and females, deaths resulting from complications of diabetes and human immunodeficiency virus infection have increased. Our findings also revealed significant heterogeneity in preventable mortality at the oblast level. For example, in 2018, deaths due to preventable causes were concentrated primarily in Siberia and the Far East. Smoking and the availability of nurses were identified as significant correlates of preventable mortality at the oblast level. Interpretations: Efforts designed to strengthen the current health care system, notably those serving the rural and less densely populated oblasts, might reduce the rate of preventable mortality in Russia. These efforts might be coupled with an ongoing focus on programs designed to reduce smoking. Funding: None.

COVID-19 Related Early Google Search Behavior and Health Communication in the United States: Panel Data Analysis on Health Measures.

The COVID-19 outbreak at the end of December 2019 spread rapidly all around the world. The objective of this study is to investigate and understand the relationship between public health measures and the development of the pandemic through Google search behaviors in the United States. Our collected data includes Google search queries related to COVID-19 from 1 January to 4 April 2020. After using unit root tests (ADF test and PP test) to examine the stationary and a Hausman test to choose a random effect model, a panel data analysis is conducted to investigate the key query terms with the newly added cases. In addition, a full sample regression and two sub-sample regressions are proposed to explain: (1) The changes in COVID-19 cases number are partly related to search variables related to treatments and medical resources, such as ventilators, hospitals, and masks, which correlate positively with the number of new cases. In contrast, regarding public health measures, social distancing, lockdown, stay-at-home, and self-isolation measures were negatively associated with the number of new cases in the US. (2) In mild states, which ranked one to twenty by the average daily new cases from least to most in 50 states, the query terms about public health measures (quarantine, lockdown, and self-isolation) have a significant negative correlation with the number of new cases. However, only the query terms about lockdown and self-isolation are also negatively associated with the number of new cases in serious states (states ranking 31 to 50). Furthermore, public health measures taken by the government during the COVID-19 outbreak are closely related to the situation of controlling the pandemic.

Heterogeneous impacts of multi-energy power generation on carbon emissions: evidence from China's provincial data.

The goals of carbon peak and carbon neutrality have put forward higher requirements for the low-carbon development of power supply. This paper discusses the impacts of multi-energy power generation on carbon emissions for 30 regions in China and proposes low-carbon development suggestions for the electric power industry. The research found that firstly there is a significant strong positive correlation between thermal power and carbon emissions in most regions of China, so the carbon emission reduction of power supply should still focus on thermal power. Secondly, wind power and photovoltaic power have positive effects or negative effects on carbon emissions in different regions. But combined with the analysis results in regions with the rapid development of wind power or photovoltaic power, it could be found that wind power and photovoltaic power contributed to reducing carbon emissions when they developed to a certain scale. It is proposed to speed up the construction of wind power and photovoltaic power in regions with rich wind resources or solar resources such as Inner Mongolia, Xinjiang, Liaoning, and Gansu. Thirdly, hydropower and nuclear power both have negative effects on carbon emissions. Considering the large demand for electricity in coastal regions where nuclear power is located, it is suggested that coastal regions should gradually promote the construction and application of nuclear power on the basis of safety.

Greenhouse gas emissions, economic globalization, and health expenditures nexus: does population aging matter in emerging market economies?

Papers on population aging and the effects of environmental quality on health expenditure have critical policy consequences. However, findings in the relevant literature are mixed, and papers generally focus on developed countries. To provide new information to the literature, this paper examines the impact of globalization, economic growth, greenhouse gas emissions, and population aging on health expenditures in emerging market economies with annual data for the period 2000 to 2018. The paper follows a second-generation advanced panel data method that considers cross-sectional dependency. The estimation results reveal that population aging, economic growth, and greenhouse gas emissions have an increasing effect on health expenditures, while globalization has a decreasing effect. Furthermore, one-way causality running from population aging to health expenditures is confirmed, while a feedback causality relationship is observed between health expenditures and other indicators (globalization, economic growth, and greenhouse gas emissions). After all, the outputs of this paper can provide critical policy implications about the relationships between aging, globalization, air quality, and health expenditures in developing countries.