This paper investigates the effect of the socioeconomic development on life expectancy at birth as an indicator of mortality or longevity in five EU accession candidate countries (Macedonia, Serbia, Bosnia and Herzegovina, Montenegro, and Albania). Using aggregate time series pool data on an annual level from UN and World Bank databases for the period 1990-2017 and Full Information Maximum Likelihood model, it was found that this connection between the socioeconomic conditions and life expectancy at birth is a prerequisite for longer life in all these five countries. Our dependent variable was the life expectancy at birth, and the background exploratory variables for the socioeconomic development were GDP per capita and infant mortality rate. The main results are that higher values of GDP per capita and lower values of infant mortality levels lead to higher life expectancy at birth suggesting that longevity of people in these five countries is increasing. These results are supported by our theoretical background and research framework hypotheses.
This paper analyses the effect of mortality rates (under-five and adult mortality) and population growth on the population ageing in a pooled sample of nine lower and upper middle European countries. Therefore, the main goal of this research is to investigate the ageing process of the population in the context of mortality mechanisms (under five and adult mortality) and of population growth in nine European LUMIs. The analysis is implemented in terms of Pooled least squares with cross-section fixed effects methodology. The novelty used within this research is White two-way cluster standard errors & covariance. This study is based on a database from the World Bank and UN covering the period 1995–2019. The expected results are making available quantitative analysis and insights in the context of mechanisms between the ageing process of population, mortality and population growth across these European LUMIs. Results are consistent with the notion that the increasing ageing process within these countries may be a consequence of the negative impact of population growth and from the influence of adult mortality for both sexes. The research results confirm the presence of solid ties of the mechanism between mortality, population growth and population ageing. Therefore, a clear point was provided that mortality acceleration will depend primarily on the level of population growth.
Attention to addressing undernourishment in low-and middle-income countries has expanded notably since the beginning of the 21st century. Population growth increases the overall demand for food, while income growth affects consumption patterns. Using annual aggregate data from the World Bank in 2001–2020 and econometric approaches, this research investigates the changes in the growth rates in rural and urban populations and GDP per capita and the prevalence of undernourishment as % of the population in low-income countries, lower-middle-income countries, and upper-middle income countries. The main goal of the study is to convey a deeper understanding by quantifying the impacts of rural and urban population growth as well as GDP per capita growth on the prevalence of undernourishment. The robust regression models showed that the prevalence of undernourishment in these countries was strongly associated with rural and urban population growth. A positive impact of rural population growth on undernutrition was found in all three groups of countries, with the most significant positive effects found in upper-middle-income countries. The negative effect of urban population growth on undernourishment was largest for the upper middle-income countries. Furthermore, fully modified ordinary least squares results revealed that the changes in the prevalence of undernourishment are mostly associated with long-term changes in the rural and urban population growth. The Difference in Difference (DiD) estimation confirmed only the causal effect of rural population growth on the prevalence of undernourishment in the panel of these countries. The findings of this study have both methodological and policy implications.
This research aims to examine the quality of migration statistics in the countries of former Yugoslavia (Slovenia, Bosnia and Herzegovina, Macedonia, Croatia, Serbia, and Montenegro) including Kosovo and Metohija as well. The comparative aspect of the research study provides an analysis on assessing the quality of migration statistics in terms of sources and data of migration statistics. The research results show that the region of the former Yugoslavia, except for Slovenia has ineffective migration statistics registration and serious limitations in this part. Furthermore, in a situation of absence of population registers almost within the whole region of former Yugoslavia, the population census and the administrative data serve as the only source for migration statistics. Moreover, almost all of the former Yugoslav republics have some existing problems in implementation of censuses regarding estimates of the usual resident population. Therefore, the migration statistics in the former Yugoslavia region provided by its national institutions should be considered as questionable.
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