Employment protection, temporary and permanent employment share, and procyclicality of labour productivity

The global crisis of 2008–2009 focused attention on the role of fi scal policy at times of collapsing aggregate demand. Concerns about experiencing a reincarnation of the great depression induced the Organization for Economic Cooperation and Development (OECD) (highincome group) and emerging market countries to invoke extraordinary policies for extraordinary times. Countries adopted sizable fi scal stimuli, augmented by unprecedented monetary expansions supported by elastic swap lines between the Federal Reserve and the European Central Bank, and between the Fed and four emerging markets. The fl ight to quality and the shortage of dollar liquidity posed a special challenge for emerging markets, inducing them to supplement these policies with both large sales of foreign currencies at the height of the crisis and with sizable depreciations. Yet there has been a remarkable heterogeneity in the magnitudes of the fi scal stimuli, and of the exchange rate depreciation. The differential patterns of response are traced in table 1, summarizing the fi scal stimulus/GDP and the depreciation rate in 32 countries, chosen by data availability. The fi rst three columns overview the crisis related fi scal stimulus / GDP, 2009–2011, in OECD countries and emerging markets. The crisis led to a signifi cant fi scal stimulus in the United States, Japan, and Germany, the magnitude of which increased from 2009 to 2010, refl ecting various lags associated with fi scal policy. The fourth and the fi fth columns report the massive “bailout” transfers to the banking system in the United States, Germany, and the United Kingdom that attempted to stabilize the fi nancial panic. It is noteworthy that the size of

This article examines the sectoral impact of disinflationary monetary policy by calculating the sacrifice ratios for several Organisation for Economic Co-operation and Development (OECD) and non-OECD countries. Sacrifice ratios calculated through the episode method reveal that disinflationary monetary policy has a differential impact across three sectors in both OECD and non-OECD countries. Of the three sectors, the industry and service sectors show significant output loss due to a tight monetary policy in OECD and non-OECD countries. But the agricultural sector shows a differential impact of disinflation policy: It shows a negative sacrifice ratio in OECD countries indicating that output growth is insignificantly affected by a tight monetary policy while non-OECD countries yield positive sacrifice ratios, suggesting that the output loss is significant. Further, it is observed that sacrifice ratios calculated from aggregate data are different from ratios calculated from sectoral data. JEL Classification: E52, E58, C14, O50

Acinetobacter baumannii is one of the most challenging nosocomial pathogens due to the emergence and widespread of antibiotic resistance. We aimed to provide the first analysis of global prevalence of antibiotic resistance in A. baumannii infections, by synthesizing data and knowledge through a systematic review. We searched studies reporting antibiotic resistance in A. baumannii infections using the Medline, Embase, Web of Science, and Cochrane databases from January 2000 to December 2016. Studies were eligible if they investigated and reported antibiotic resistance in A. baumannii infections with inpatients or outpatients in hospital. Our investigation showed a high prevalence of resistance to the common prescribed antibiotics in A. baumannii infections in both OECD (Organization for Economic Co-operation and Development) and non-OECD countries. Strikingly, though OECD countries have substantially lower pooled prevalence of resistance compared to non-OECD countries based on the data during 2006–2016, a further investigation in a time scale disclosed a faster increase in OECD countries during the past 11 years, and currently both of them have a comparable prevalence of resistance (2011–2016). Tigecycline and colistin are still active but their resistances are expected to become common if the preventative measures are not taken. Antibiotic resistance in A. baumannii infection developed fast and is a crisis for both OECD and non-OECD countries. A “post-antibiotic era” for A. baumannii infection is expected in the next 10–20 years without immediate actions from pharmaceutical companies and governments.

Does economic level similarly matter for injury mortality in the OECD and non-OECD countries?

Dividend Imputation Systems in Industrialized Countries: An Examination of Relative Tax Burdens

Financial convergence is a process for establishing a relationship among the financial markets of different countries; as a result of such process the rates of similar financial assets in different markets and countries become very close to each other. Some factors might create financial convergence. of which the trade and international capital flows among countries, the presence of banks and other financial institutions in the international arena, the availability of clear and accurate information of markets and financial organizations, and the existence of similar infrastructure and their characteristics from economic, legal and cultural perspectives can be mentioned. The issue of financial convergence with the aim of achieving global financial markets and taking advantage of its capabilities and characteristics would be very important for all countries, especially the emerging countries. This study examines financial convergence in the money and capital markets of the Organization for Economic Co-operation and Development (OECD) and BRICS countries in the period of 2007-2020. The study utilizes the Panel Convergence Methodology and Cluster Analysis (Philips and Sul methodology) along with a clustering algorithm. The findings indicate a lack of overall convergence between OECD and BRICS countries in both financial markets (money and capital) this is due to the lack of similar economic infrastructure, differences in the size of the economy, and variations in trade, financial and monetary freedom indicators, trade relations, and capital transfers. The cluster test in the money market confirms the existence of 3 convergence clubs among the studied countries. The convergence of emerging BRICS countries in the money market, with a large number of OECD developed countries, is a confirmation of the development of their banking sector in the recent years. On the other hand, the capital market survey also shows the presence of 5 convergence clubs between OECD and BRICS countries. Besides, it's been shown that South Africa, along with Lithuania, Turkey, Slovakia and Latvia, has established a divergent group.

Greater and greater attention is being paid to air pollution problems, because of their negative impact on the environment and human health. This article measures energy efficiency, carbon dioxide emissions efficiency, and particulate matter (PM2.5) concentration efficiency to compare the energy efficiency differences between Organisation for Economic Co-operation and Development (OECD) member countries and non-OECD member countries from 2010 to 2014 using a metafrontier dynamic Data Envelopment Analysis model. We calculate technology gap ratio and input and output efficiency values to measure the energy efficiencies of each economy, finding that (a) OECD countries have a technology gap ratio of 1 or very close to 1; and except for the United Arab Emirates and Singapore, both of which exhibit annual improvements, the non-OECD countries have a significant need for efficiency improvements; (b) the average technology gap ratio of OECD is higher than that of non-OECD countries; that is, while OECD countries’ technology gap ratio (TGR) changes are relatively stable, non-OECD countries’ TGRs are gradually increasing; (c) non-OECD countries have large PM2.5 concentration efficiency gaps, with the annual efficiencies in China, India, and Nepal being less than 0.2; (d) Switzerland, Denmark, France, the United Kingdom, Iceland, Luxembourg, Norway, the United States, and the United Arab Emirates all have new and traditional energy efficiency values of 1; and (e) Botswana, Algeria, and Cambodia have poor traditional energy efficiencies, but better new energy efficiencies, whereas Hungary, South Korea, Slovakia, and Slovenia have poor new energy efficiencies and better traditional energy efficiencies.

(ProQuest: ... denotes formulae omitted.)1.IntroductionThe Organization for Economic Co-operation and Development (OECD) was established in 1961 and has 34 members. The OECD budget is approximately $357 million. During the study period, total real gross domestic product (GDP) rose by 22 percent, reaching $39 trillion. Capital increased by 8 percent, reaching $7.8 trillion, while labor power increased 11 percent, reaching 610 million people within the same period (https://data.oecd.org/). GDP growth was greater than capital and labor power growth. There was significant total factor productivity growth in OECD countries.Income distribution and differentiation among OECD countries, which are the leading economies of the world, are increasing (http://oecd/idd). The ratio of the top 10 percent to the bottom 10 percent is estimated to be 9.5 percent in 2012; however the relevant figure was 7 percent in 1980. The difference between the rich and the poor requires examining convergence and divergence among the relevant countries.Growth dynamics of countries as well as convergence among those countries have been studied for a long time according to neoclassical growth theories in various studies. A series of studies indicate convergence among OECD countries. The majority of such studies use productivity per worker and total factor productivity in order to analyze convergence. The case of residual is named after Solow (1957); that part of growth is known as Total Factor Productivity (TFP).The economic productivity and convergence issue of OECD countries, the economic structures of which are partially similar to each other and that are representative of relatively advanced economies, has been investigated by our study for the period between 2000 and 2012. In that regard, MI, which is interpreted by Caves et al. (1982), and the data envelopment analysis (DEA) method used by Charnes et al. (1978) are used for TFP. The description is used as inputs and outputs. Physical capital is used as input and is among some of the most important factors that affect technological development and productivity. Gross national product is used as output. All variables are divided into labor unit and necessary analyses are performed. Data sources are provided below. The whole variable value is calculated based on 2005 U.S. dollars. A total of 34 OECD countries are included in the analysis. Although some of the countries were not OECD member during the entire given period, they are still included. Whether there are any differences between these countries will be observed during the analysis process.The aim of this study is to analyze convergence in OECD countries over a reasonable period of time at the beginning of the new millennium. The period between 2000 and 2012 is chosen intentionally in order to examine the results of the financial crisis of 2009. Another reason for the short study period is our effort to include DEA, Malmquist, and convergence analyses together. Including more data sets would have expanded the DEA and TFP tables, which in turn would exceed the limits of this study. The study period has given us the chance to employ all three analyses. The set of values in the study are obtained from OECD StatExtracts. Real physical capital per worker, real human capital per worker, and real GDP per worker are calculated based on 2005 U.S. dollars.The literature and methodology forms the first part of the study while the results of the DEA and Malmquist index (MI) analysis of TFP are given in the following chapter. The conclusion and assessment make up the last part of this study.2.LiteratureIn recent years there have been many studies that examine convergence and economic growth. Barro and Sala-i Martin (1991, 1992) and Fare et al. (2006) are the major contributors to the relevant literature. According to Kruger (2003), experiential growth investigations over the last ten years have been pursued at least three different ways. …

In the context of intensifying climate change and increasing resource constraints, addressing the dual challenges of economic growth and environmental sustainability has emerged as a critical global priority. Green Total Factor Energy Efficiency (GTFEE), an essential metric for evaluating the coordination between economic development, energy efficiency, and environmental protection, plays a pivotal role in optimizing resource allocation, fostering technological innovation, and supporting the pursuit of sustainable development. However, existing research has yet to provide a comprehensive and systematic analysis of GTFEE’s long-term trends and its underlying driving mechanisms. This study addresses this gap by focusing on OECD (Organization for Economic Co-operation and Development) countries, employing the super-efficient SBM-DEA model with non-expected outputs to evaluate GTFEE from 1995 to 2021 systematically. The analysis delves into the spatial and temporal characteristics of GTFEE and its dynamic evolution patterns. The findings reveal a sustained upward trajectory in GTFEE across OECD countries, with the average score rising from 0.7814 in 1995 to 0.8894 in 2021. Nonetheless, substantial heterogeneity persists in GTFEE levels among regions and countries. Further, using quantile random forest regression analysis, the study identifies critical determinants of GTFEE, including economic development levels, energy intensity, technological innovation capacity, industrial structure optimization, fiscal revenue, and urbanization. These results not only elucidate the driving mechanisms of GTFEE but also offer a robust theoretical foundation and actionable policy insights for advancing green energy transitions and achieving sustainable development goals. A comprehensive and integrated assessment of Green Total Factor Energy Efficiency (GTFEE) in OECD countries is crucial for advancing sustainable development. This study systematically measures GTFEE in OECD countries over the period 1995-2021, utilizing the super-efficient SBM-DEA model with an undesired output. It further analyzes the spatial and temporal distribution characteristics and dynamic evolution of GTFEE. The results indicate that, overall, GTFEE in OECD countries exhibits an upward trend throughout the study period, with the average value increasing from 0.7814 in 1995 to 0.8894 in 2021, reflecting improvements in green total factor energy efficiency. However, substantial disparities in GTFEE levels are observed across countries, suggesting varied rates of progress and effectiveness in promoting green transitions and enhancing energy efficiency. Through quantile random forest regression analysis, the study identifies key determinants influencing GTFEE, including the level of economic development (as measured by GNI per capita), energy intensity (primary energy consumption), technological innovation capacity, industrial structure optimization, fiscal revenue, and urbanization.

In this study, the geniatric status of OECD (Organisation for Economic Co-operation and Development) countries was measured, and the effects of aging status on disease patterns in each country were quantitatively assessed. A theoretical model explaining the effects was suggested, and the implications were discussed. Data used in this study were the OECD Health Statistics data and WHO Global Burden of Disease data. The values for each country were paired with disability-adjusted life years (DALYs) presented by the WHO and Institute for Health Metrics and Evaluation (IHME). A cross-country panel analysis was conducted to analyze the effects of senility on the burden of disease in OECD countries. Geniatric status had effects on the burden of disease (P = .048). Total health expenditure significantly reduced the burden of disease (P = .001). In the panel model with YLL (Year of Life Lost) as the outcome variable, geniatric status had twice greater effects on the burden of disease than that in the model with DALY (P = .003). In medical insurance-related policies, the characteristics of the disease should be considered. In particular, chronic diseases have not received much attention compared to their risk. However, the disease that actually affects the burden of disease is a disease that becomes chronic and requires long-term treatment rather than a disease with a high fatality rate. And, as a result of this study, the higher the level of resource consumption for treatment in OECD countries, where aging is progressing, the burden of disease was rather reduced. Therefore, if there is institutional support to receive appropriate treatment, it will be possible to reduce the national burden of disease.

This study examines the relationship between economic factors and environmental sustainability in OECD (Organisation for Economic Co-operation and Development) countries from 1990 to 2022, with a particular focus on the impact of renewable energy consumption and environmental technologies on CO2 emissions. The research utilizes empirical data to establish a clear negative correlation between the adoption of renewable energy sources and the level of CO2 emissions, highlighting the effectiveness of renewable energy in reducing the environmental impact of economic activities. This finding supports the theoretical perspective that transitioning to cleaner energy sources is vital for achieving environmental sustainability and aligns with the objectives of the OECD’s environmental sustainability program. Further analysis reveals a significant negative impact of environmental technologies on CO2 emissions, underscoring the importance of technological innovation in environmental conservation efforts. The study also explores the dual influence of GDP growth, urbanization, industrialization, and trade on CO2 emissions, revealing both positive and negative effects across different stages of economic development. Initially, these factors contribute to increased emissions, but as economies mature and integrate more efficient and cleaner technologies, their impact on emissions becomes negative. These findings demonstrate the complex interplay between economic development and environmental sustainability and emphasize the need for policies that encourage renewable energy adoption, support environmental technological innovations, and guide economies towards sustainable practices. The study provides valuable insights for policymakers and stakeholders, advocating for an integrated approach to ensure long-term environmental sustainability in OECD countries.

The objectives of this study are to implicitly investigate the relationship that exist between energy consumption (renewable and non-renewable energy) and human development (with the Human Development Index as proxy); and energy consumption and industrial sector performance (with industrial output as proxy) in selected sub-Saharan Africa and the Organization for Economic Co-operation and Development (OECD) countries. Four groups of models were specified and estimated using Panel data for 21 countries according to income criteria from 1990 to 2022. These data were analyzed using Panel Ordinary Least Square (OLS) before which they were filtered with the use of Augmented Dickey Fuller (ADF) unit root test while the Johansen cointegration test was used to justify the long-run relationship among all included variables. The findings of this study revealed that energy consumption was positively related and statistically significant in explaining changes in human development and industrial sector performance in the selected sub-Saharan Africa and the OECD countries. However, changes in Human Development Index (HDI) were not statistically significant in explaining changes inindustrial sector performance in both regions. The results of the estimated models revealed a three-way directional causality among the selected variables. Additionally, it was established that a significant gap exist in human development, energy consumption and industrial sector performance, in favour of the selected OECD countries. Furthermore, it was also established that energy consumption and industrial output are potent determinants of human development in the selected OECD and sub-Saharan African Countries.

Benchmarking health IT among OECD countries: better data for better policy

This paper examines the relationship between coal consumption and economic growth for 30 OECD (Organisation for Economic Co-operation and Development) countries and 32 non-OECD countries for 1990–2013 using a multivariate dependent panel analysis. For the analysis, we conducted the common factor defactorization process, unit root test, cointegration test, long-run cointegrating vector, and Granger causality test. Our results suggest the following: First, there is no long-run relationship between coal consumption and economic growth in OECD countries; however, in non-OECD countries, the relationship does exist. Second, excessive coal usage may hinder economic growth in the long run. Lastly, the growth hypothesis (coal consumption affects economic growth positively) is supported in the short run for non-OECD countries. As coal consumption has a positive effect on economic growth in the short run and a negative effect in the long run, energy conservation policies may have adverse effects only in the short run. Thus, non-OECD countries should gradually switch their energy mix to become less coal-dependent as they consider climate change. Moreover, a transfer of technology and financial resources from developed to developing countries must be encouraged at a global level.

Goal. To consider the possibility of introducing the methodology for calculating avoidable mortality in the educational process by the example of determining the indicators of avoidable mortality from cervical cancer.Materials and methods. The data are based on criteria and indicators developed by experts from the Organization for Economic Cooperation and Development (OECD) countries. A comparative analysis of the indicators of avoidable mortality due to cancer in the OECD countries and other countries was carried out. Statistical data for 2015-2021 were obtained from the National Statistical Bureau of the Agency of the Republic of Kazakhstan for Strategic Planning and Reforms (https://stat.gov.kz).Discussion. Evaluation of the effectiveness of health systems is becoming increasingly important in the OECD and EU countries (European Union). Avoidable mortality indicators serve as a starting point for assessing the effectiveness of public health and health policy in preventing premature mortality from preventable and treatable causes of death. Acquisition of skills in calculating avoidable mortality and interpretation of the results of calculations of indicators of avoidable mortality from diseases within the framework of the development of an educational program (areas of training – Management in healthcare, MBA, EMBA and Global Health and Healthcare) are necessary for future specialists in practice, in particular when conducting a comparative assessment of indicators of the effectiveness of the healthcare system with OECD countries. Effective activities of the health system in the field of public health protection carried out in different countries have a great impact on the spread and control of diseases. For example, the reduction in the level of avoidable mortality from cervical cancer in several regions of Kazakhstan (Akmola region, Zhambyl region, Shymkent city, Turkestan region) in the period from 2015 to 2021 proves the effectiveness of preventive measures implemented in these regions. At the same time, in some regions of Kazakhstan (West Kazakhstan region, Kyzylorda region, Mangystau region, Pavlodar region, Kostanay region, East Kazakhstan region), mortality rates from cervical cancer have increased and there is a need to strengthen measures at the level of primary and secondary prevention and treatment. Thus, the definition and study of the regional heterogeneity of indicators of avoidable mortality will allow us to identify the weaknesses and strengths of the implemented strategies for the protection of the health of the female population.Results. The methodology for calculating avoidable mortality is a key element for achieving the Third Sustainable Development Goal (SDG). Future masters of educational programs Management in Healthcare, MBA, EMBA and Global Health and Healthcare need to master the methodology for calculating avoidable mortality, as well as clearly understand the concepts and concepts of preventive and treatable mortality, which will allow them to carry out timely assessment of implemented programs in the future and will contribute to the adoption of decisive and more targeted, effective measures to reduce avoidable mortality.Conclusions. As a result of the inclusion of the methodology for calculating avoidable mortality in the educational program of the master's degree, students are given the opportunity to master new terminology related to the concepts of avoidable mortality, acquire skills in calculating indicators of avoidable mortality, as well as conducting a comparative analysis of the causes of mortality, which can mainly be prevented by effective public health measures and primary prevention, as well as the causes of mortality, which can be cured with the help of timely and effective health measures, including secondary prevention and treatment (i.e. after the onset of diseases, to reduce mortality).