Suchergebnisse

The subject of the research is growth factors of the average life expectancy. The goal of the research is to identify the most substantial factors that can impact the level and dynamics of life expectancy, and by influencing which it may be possible to increase the average life expectancy. The research methods used are observation, data collection, analysis, and synthesis, comparison, grouping, correlation and regression analysis, econometric modelling, systematic and complex approach. The research results. Within this research, the authors have investigated more than 40 variables across 16 countries based on the data of open sources, databases, and publications of official statistical institutions of specific countries for the period from 1969 to 2017; and from 1992 to 2017 for a number of recently formed countries. For the purposes of further analysis, the authors have chosen four countries: Belarus, Ukraine, Great Britain, and China. For those countries, the corresponding regression models between the level of life expectancy and a number of factors in two variations depending on the modelling interval have been developed, and the impact degree assessment has been made. The domain of applicability of the research results is the corresponding governmental policy targeted at increasing the average life expectancy, being one of the ways to save and augment human capital which plays a fairly important role in forming the national wealth of a country. Conclusions. Based on the results of the conducted econometric modelling, various models across a number of countries and several time periods have been developed and analysed. One of them is to assess the potential impact of the development of ecologically clean production on the level of average life expectancy. With the necessity of generalized reasoning, the authors have made an aggregate impact assessment of the most substantial factors on the endogenous variable in consideration, based on the complex interpretation of the results across the four chosen countries. Thus, the most prevalent variables in the descending order of influence are: final consumption expenses per capita, gross domestic product per capita, arable land per capita, and the current unemployment level. However, it is worth mentioning that in order to achieve the desirable level and dynamics of the average life expectancy, complex influence on the whole array of factors in consideration is necessary, not just on specific ones.

Anonymous tells a story about an old engineer regaling people with aphorism like "you may know the significant digits but do you know the significance of the number", in talking about what the average joe is experiencing. Here are some easily calculated numbers showing the distinction between mean and median average hourly earnings (note that […]

AbstractIn wealth accounting and sustainability assessments, we characterize the non-declining wealth criterion under dynamic average utilitarianism (DAU) as defined by Dasgupta (2001). Under DAU, the objective function consists of total intergenerational well-being divided by the present discounted sum of population from the present to the future. It is shown that, in order for an economy to be on a sustainable path, inclusive wealth should grow at a rate higher than the difference between the discount rate and the share of current population of the discounted future population. Our application to the inclusive wealth index shows that, among other results, the DAU criterion changes sustainability assessments for some developing countries with future demographic change, implying that wealth does not accumulate sufficiently in light of DAU. We also show empirical estimates of the value of population change under total utilitarianism, average utilitarianism, and DAU.

"Recent research employing cross-national regressions shows that the incomes of the poor move one-for-one with overall average incomes, suggesting that economic growth is virtually sufficient for poverty reduction. This paper attempts to probe beneath cross-country averages by analyzing provincial data on the poverty–growth nexus in the Philippines. The results show that economic growth explains a lot but not all about poverty. The balance that seems fairly large can be accounted for by other factors (e.g., infrastructure, human capital, and location-specific characteristics) and institutions (e.g., political economy and agrarian reform). Thus, while growth is indeed good for the poor, it is not good enough. How much is not good enough is illustrated by this paper and will become clearer as subnational analysis is extended to more countries. For policy purposes, an intracountry examination of the determinants of poverty reduction seems clearly superior to cross-country analysis."