Explore the vast range of titles available.

The population in the developed world has experienced a significant increase in life expectancy over the last 50 years. Simultaneously, while the onset of comorbidities has been deferred to older age groups, health-care expenditure has grown dramatically, primarily owing to the advancement of medical technology and the expansion of individual income levels, along with population ageing in the wake of increased longevity. However, the contribution of population ageing to health expenditure growth is subject to some theoretical and empirical scrutiny. This paper takes the question of ageing and health and health care to the data to evaluate the net impact of ageing. We focus on two main questions, namely the welfare valuation of longevity improvements for various OECD countries, along with the ‘red herring’ hypothesis which suggests that population ageing has a small and almost negligible impact on health-care expenditure. Our estimates lead us to suggest an average gain in longevity of 4.5 years since 1980, corresponding to about 13.5 per cent of lifetime income of a 20-year-old in 2000. Furthermore, we confirm a weak red-herring claim, that is, that population ageing accounts for only a 0.5 per cent annual growth rate of health-care expenditure. Finally, we find that the rise in longevity leads to a further demand for life-prolonging medical care.

Issues of residual spatial autocorrelation (RSA) and spatial scale are critical to the study of species-environment relationships, because RSA invalidates many statistical procedures, while the scale of analysis affects the quantification of these relationships. Although these issues independently are widely covered in the literature, only sparse attention is given to their integration. This paper focuses on the interplay between RSA and the spatial scaling of species-environment relationships. Using a hypothetical species in an artificial landscape, we show that a mismatch between the scale of analysis and the scale of a species' response to its environment leads to a decrease in the portion of variation explained by environmental predictors. Moreover, it results in RSA and biased regression coefficients. This bias stems from error-predictor dependencies due to the scale mismatch, the magnitude of which depends on the interaction between the scale of landscape heterogeneity and the scale of a species' response to this heterogeneity. We show that explicitly considering scale effects on RSA can reveal the characteristic scale of a species' response to its environment. This is important, because the estimation of species-environment relationships using spatial regression methods proves to be erroneous in case of a scale mismatch, leading to spurious conclusions when scaling issues are not explicitly considered. The findings presented here highlight the importance of examining the appropriateness of the spatial scales used in analyses, since scale mismatches affect the rigor of statistical analyses and thereby the ability to understand the processes underlying spatial patterning in ecological phenomena.

The rising healthcare costs due to population aging present a complex issue, with debate centering on whether these costs are driven by aging or end-of-life care. This study examines healthcare expenditures in Chinese households using data from the 2005 and 2018 Chinese Longitudinal Healthy Longevity Survey. By applying the Heckman select model and a two-part model, the research innovatively includes time to death, income, social security and health level in the benchmark regression in order to validate the recent some new Red Herring hypothesis. The findings show that time to death is the primary determinant of healthcare expenditures, while the effect of aging is minimal. Income, social security, and health status also significantly influence health expenditure, but they do not function as Red Herring variables.

PurposeThe main purpose of this paper is to examine the role of population aging in determining the health care expenditure (HCE) in India over the period 1981 to 2018.Design/methodology/approachWhile establishing the linkage between population aging and HCE, the study has used economic growth, urbanization and CO2 emissions as control variables and used the autoregressive distributed lag (ARDL) approach to cointegration and VECM based Granger causality approach to estimate both the long-run and short-run relationships among the variables.FindingsThe results of the ARDL bounds test showed that there is a stable and long-run relationship among the variables. The long-run and short-run coefficients reveal that population aging and income per capita exert a statistically significant and positive effect on per capita HCE in India. The VECM causality evidence shows that there is a presence of short-run causality from economic growth and population aging to per capita HCE, urbanization to environmental degradation and further from aging to urbanization. However, the long-run causality evidence confirms unidirectional causality from population aging to the per capita HCE.Research limitations/implicationsThe research findings could be improved by considering the changes in mortality rate over time because of other environmental factors such as air pollution, among others as control variables. Various other variables affecting the health of an aged person could be considered for better research outcome which is not included in the present study because of the paucity of data. However, the present research findings would certainly serve effective policy instrument aiming at maximizing health gains that are highly associated with the elderly population and economic growth towards achieving sustainable development in India.Originality/valueThe uniqueness of the present study lies in its estimation where the relationship between population aging and HCE is looked at while considering the impact of other environmental factors separately. The causal relationship is shown among the variables using updated econometrics time-series techniques. The study tried to resolve the ambiguity associated with the relationship between aging and HCE at a macro level.

Within the fields of English for Academic Purposes (EAP) and English for Research Publication Purposes (ERPP), the question of whether English as an Additional Language (EAL) scholars are disadvantaged by the pressure to publish in English continues to be debated. In this paper, I challenge this orthodoxy, raising questions about the evidence upon which it is based. Within a framework of ‘verbal hygiene’, I will argue that the attention accorded to ‘non-nativeness’ may be disproportionate to its significance for publication success. I conclude by proposing some reorientations for researchers and practitioners in the field that encompass non-linguistic structures of inequity.

1. Comparative analyses of diversity variation among and between regions allow testing of alternative explanatory models and ideas. Here, we explore the relationships between the tree x-diversity of small rain forest plots in Africa and in Amazonia and climatic variables, to test the explanatory power of climate and the consistency of relationships between the two continents. 2. Our analysis included 1003 African plots and 512 Amazonian plots. All are located in old-growth primary non-flooded forest under 900 m altitude. Tree a-diversity is estimated using Fisher's alpha calculated for trees with diameter at breast height ≥ 10 cm. Mean diversity values are lower in Africa by a factor of two. 3. Climate-diversity analyses are based on data aggregated for grid cells of 2.5 x 2.5 km. The highest Fisher's alpha values are found in Amazonian forests with no climatic analogue in our African data set. When the analysis is restricted to pixels of directly comparable climate, the mean diversity of African forests is still much lower than that in Amazonia. Only in regions of low mean annual rainfall and temperature is mean diversity in African forests comparable with, or superior to, the diversity in Amazonia. 4. The climatic variables best correlated with the tree α-diversity are largely different in the African and Amazonian data, or correlate with African and Amazonian diversity in opposite directions. 5. These differences in the relationship between local/landscape-scale a-diversity and climate variables between the two continents point to the possible significance of an array of factors including: macro-scale climate differences between the two regions, overall size of the respective species pools, past climate variation, other forms of long-term and short-term environmental variation, and edaphics. We speculate that the lower a-diversity of African lowland rain forests reported here may be in part a function of the smaller regional species pool of tree species adapted to warm, wet conditions. 6. Our results point to the importance of controlling for variation in plot size and for gross differences in regional climates when undertaking comparative analyses between regions of how local diversity of forest varies in relation to other putative controlling factors.

I'd rather not be an idiot and neither would you. One useful tool in avoid idiocy and figuring out what's true is to be aware of logical fallacies. Some errors in thinking are so common that they have been named in infamy. This article is an anti-idiocy vaccine to immunize you to common fallacies such as poisoning the well, begging the question, false dichotomy, and others, in order to give you a better shot at avoiding fallacy and finding out what's true.

Fallacies are common errors in an argument and they undermine the logic of that argument. They obstruct the process of argumentation since they do not contribute to the resolution in difference in opinion. The current study investigates fallacies in four religious argumentative debates between Muslims and atheists. It adopts Toulmin et al (1984) as a model for analysis. Results show that both debating parties, Muslims and atheists commit fallacies but the latter exceeds the former quantitatively and qualitatively. The most common fallacies in Muslims' arguments are straw man argument, poisoning the well and attacking the person whereas the straw man argument, argument from ignorance, hasty generalization and appeal to compassion are the most committed ones by atheists.

Aim: Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial autocorrelation patterns. Location: Tropical rain forest, West Africa and Atlantic Central Africa. Methods: Alpha diversity estimates were compiled for trees with diameter at breast height ≥ 10 cm in 573 inventory plots. Linear regression (ordinary least squares, OLS) and random forest (RF) statistical techniques were used to project alpha diversity estimates at unsampled locations using climate data and remote sensing data [Moderate Resolution Imaging Spectroradiometer (MODIS), normalized difference vegetation index (NDVI), Quick Scatterometer (QSCAT), tree cover, elevation]. The prediction reliabilities of OLS and RF models were evaluated using a novel approach and compared to that of a kriging model based on geographic location alone. Results: The predictive power of the kriging model was comparable to that of OLS and RF models based on climatic and remote sensing data. The three models provided congruent predictions of alpha diversity in well-sampled areas but not in poorly inventoried locations. The reliability of the predictions of all three models declined markedly with distance from points with inventory data, becoming very low at distances > 50 km. According to inventory data, Atlantic Central African forests display a higher mean alpha diversity than do West African forests. Main conclusions: The lower tree alpha diversity in West Africa than in Atlantic Central Africa may reflect a richer regional species pool in the latter. Our results emphasize and illustrate the need to test model predictions in a spatially explicit manner. Good OLS or RF model predictions from inventory data at short distance largely result from the strong spatial autocorrelation displayed by both the alpha diversity and the predictive variables rather than necessarily from causal relationships. Our results suggest that alpha diversity is driven by history rather than by the contemporary environment. Given the low predictive power of models, we call for a major effort to broaden the geographical extent and intensity of forest assessments to expand our knowledge of African rain forest diversity.

The ‘red herring’ hypothesis (RHH) claims that apart from income and medical technology, proximity to death rather than age constitutes the main determinant of healthcare expenditure (HCE). This paper seeks to underpin the RHH with some theory to derive new predictions also for a rationed setting, and to test them against published empirical evidence. One set comprising ten predictions uses women’s longer life expectancy as an indicator of the difference in time to death in their favor. Out of 28 testing opportunities drawn from the published evidence, in the case of no rationing seven out of eleven result in full and two in partial confirmation; in the case of rationing, twelve out of 17 result in full and one in partial confirmation. The other set, containing 35 testing opportunities, concerns the age profile of HCE. In the case of no rationing, seven out of twelve result in full and four in partial confirmation; in the case of rationing, eleven out of 23 in full and nine in partial confirmation. There are but ten contradictions in total. Overall, the new tests of the RHH can be said to receive a good deal of empirical support, both from countries and settings with and without rationing.