scholarly journals Quantitative Assessment of the Dynamics of Changes in the GDP Per Capita Index in the Regions of Bulgaria and Slovakia

2019 ◽  
Vol 12 (2) ◽  
pp. 127-135
Author(s):  
Agata Surówka
Keyword(s):  
Transition Matrix ◽  
Quantitative Assessment ◽  
Quantitative Methods ◽  
Gdp Per Capita ◽  
General Distribution ◽  
Transition Matrices ◽  
Global Trends ◽  
Rate Of Development ◽  
Per Capita ◽  
Distribution Of Income

SummarySubject and purpose of work: The article presents the results of research into the dynamics of changes in income distribution as measured by means of GDP per capita for the regions Bulgaria and Slovakia using quantitative methods.Materials and methods: The transition matrix was used as a research tool. As some authors note, since most of the research is limited to the assessment and analysis of global trends, this does not allow to distinguish the situation in which regions maintain their relative position from the situations in which the general distribution of income changes slightly while the location of some regions changes significantly. In this case, individual regions may differ considerably in their rate of development even in the periods when no convergence was observed.Results: The approach adopted in this study made it possible to verify the degree of diversification of the economic strength of the regions examined and conduct a comparative analysis of the dynamics of changes in the transition matrices.Conclusions: It was concluded that the regions of Slovakia and Bulgaria are developing at the same pace. Income stability can be observed. It is justifiable to look for and workout modern tools that will enable tracking changes in regional development.

scholarly journals Evolución De La Desigualdad Y Pobreza En Nicaragua En El Periodo De 1991 A 2014

2018 ◽  
Vol 14 (31) ◽  
pp. 337
Author(s):  
Carlos Ernesto Luquez Gaitán ◽  
Ernest Yasser Núñez Betancourt ◽  
Manuel del Valle Sánchez
Keyword(s):  
World Bank ◽  
Unemployment Rate ◽  
Quantitative Assessment ◽  
Historical Perspective ◽  
Gdp Per Capita ◽  
Steady Increase ◽  
Structural Reforms ◽  
Real Gdp ◽  
Poverty And Inequality ◽  
Per Capita

This paper discusses the situation of the evolution of inequality and poverty from a historical perspective, including the structural reforms in Nicaragua during the decade of 1990. It also examines the decline in poverty in Nicaragua from 1991 through World Bank indicators. Methods of measuring inequality and poverty such as the Gini coefficient, GDP per capita, and the incidence rate of poverty, as well as the poverty gap, are used. It includes the results of quantitative assessment of poverty and inequality, and concludes with a decline in poverty. There is evidence of a steady increase in real GDP and a steady trend in the unemployment rate.

scholarly journals POVERTY RATE DURING THE 1998 AND 2008 CRISIS PERIOD IN 5 ASEAN COUNTRIES

2018 ◽  
Vol 3 (1) ◽  
pp. 49
Author(s):  
Ridho Firmansyah ◽  
Sri Kusreni
Keyword(s):  
Population Growth ◽  
Government Spending ◽  
Fixed Effect Model ◽  
Poverty Rate ◽  
Gdp Per Capita ◽  
Effect Model ◽  
Panel Data Regression ◽  
Per Capita ◽  
Asean Countries ◽  
Distribution Of Income

This study aims to examine and analyze the effect of GDP per capita, Inequal distribution of income, unemployment, population growth and government spending on education on poverty in five ASEAN countries. This study uses panel data regression equation using the Fixed Effect Model (FEM). The results showed that the effect of GDP per capita, Inequal distribution of income, unemployment, population growth and government spending on education affects simultaneously on poverty. While partially each independent variable have different effect on poverty in five ASEAN countries.

Searching for new Sources of growth. Are the Developing Countries Catching up with the Developed ones?

2015 ◽  
pp. 30-53
Author(s):  
V. Popov
Keyword(s):  
Developing Countries ◽  
Western Europe ◽  
Gdp Per Capita ◽  
The West ◽  
Catching Up ◽  
The Us ◽  
The World ◽  
Economic Divergence ◽  
Per Capita ◽  
Relative Standing

This paper examines the trajectory of growth in the Global South. Before the 1500s all countries were roughly at the same level of development, but from the 1500s Western countries started to grow faster than the rest of the world and PPP GDP per capita by 1950 in the US, the richest Western nation, was nearly 5 times higher than the world average and 2 times higher than in Western Europe. Since 1950 this ratio stabilized - not only Western Europe and Japan improved their relative standing in per capita income versus the US, but also East Asia, South Asia and some developing countries in other regions started to bridge the gap with the West. After nearly half of the millennium of growing economic divergence, the world seems to have entered the era of convergence. The factors behind these trends are analyzed; implications for the future and possible scenarios are considered.

Atlas of economic complexity, Russian regional pages

2018 ◽  
pp. 71-91 ◽  
Author(s):  
I. L. Lyubimov ◽  
M. V. Lysyuk ◽  
M. A. Gvozdeva
Keyword(s):  
Value Added ◽  
Growth Strategy ◽  
Gdp Per Capita ◽  
Export Diversification ◽  
Russian Regions ◽  
Economic Complexity ◽  
Diversification Strategies ◽  
Central Regions ◽  
Per Capita ◽  
Regions Of Russia

Well-established results indicate that export diversification might be a better growth strategy for an emerging economy as long as its GDP per capita level is smaller than an empirically defined threshold. As average incomes in Russian regions are likely to be far below the threshold, it might be important to estimate their diversification potential. The paper discusses the Atlas of economic complexity for Russian regions created to visualize regional export baskets, to estimate their complexity and evaluate regional export potential. The paper’s results are consistent with previous findings: the complexity of export is substantially higher and diversification potential is larger in western and central regions of Russia. Their export potential might become larger if western and central regions, first, try to join global value added chains and second, cooperate and develop joint diversification strategies. Northern and eastern regions are by contrast much less complex and their diversification potential is small.

The Reproduction Vector of the Russian Economy: 1999-2007

2008 ◽  
pp. 94-109 ◽  
Author(s):  
D. Sorokin
Keyword(s):  
Economic Policy ◽  
Human Capital ◽  
Growth Rates ◽  
Developed Countries ◽  
Gdp Per Capita ◽  
Real Sector ◽  
Russian Economy ◽  
Per Capita ◽  
The Developed Countries

The problem of the Russian economy’s growth rates is considered in the article in the context of Russia’s backwardness regarding GDP per capita in comparison with the developed countries. The author stresses the urgency of modernization of the real sector of the economy and the recovery of the country’s human capital. For reaching these goals short- or mid-term programs are not sufficient. Economic policy needs a long-term (15-20 years) strategy, otherwise Russia will be condemned to economic inertia and multiplying structural disproportions.

Regional household poverty and mobility analysis – a transition probability approach

2020 ◽  
Vol 63 (3) ◽  
pp. 286-302
Author(s):  
Damian Mowczan ◽  
Keyword(s):  
Transition Probability ◽  
General Level ◽  
Transition Matrices ◽  
Equivalent Unit ◽  
Central Statistical ◽  
Per Capita ◽  
Probability Matrices ◽  
General Mobility ◽  
One Year ◽  
The One

The main objective of this paper was to estimate and analyse transition-probability matrices for all 16 of Poland’s NUTS-2 level regions (voivodeship level). The analysis is conducted in terms of the transitions among six expenditure classes (per capita and per equivalent unit), focusing on poverty classes. The period of analysis was two years: 2015 and 2016. The basic aim was to identify both those regions in which the probability of staying in poverty was the highest and the general level of mobility among expenditure classes. The study uses a two-year panel sub-sample of unidentified unit data from the Central Statistical Office (CSO), specifically the data concerning household budget surveys. To account for differences in household size and demographic structure, the study used expenditures per capita and expenditures per equivalent unit simultaneously. To estimate the elements of the transition matrices, a classic maximum-likelihood estimator was used. The analysis used Shorrocks’ and Bartholomew’s mobility indices to assess the general mobility level and the Gini index to assess the inequality level. The results show that the one-year probability of staying in the same poverty class varies among regions and is lower for expenditures per equivalent units. The highest probabilities were identified in Podkarpackie (expenditures per capita) and Opolskie (expenditures per equivalent unit), and the lowest probabilities in Kujawsko-Pomorskie (expenditures per capita) and Małopolskie (expenditures per equivalent unit). The highest level of general mobility was noted in Małopolskie, for both categories of expenditures.

The monetary value of disability-adjusted-life-years lost in Kenya in 2017.pdf

2019 ◽  
Author(s):  
Joses Kirigia ◽  
Rose Nabi Deborah Karimi Muthuri
Keyword(s):  
New York ◽  
International Monetary Fund ◽  
Health Expenditure ◽  
Analytical Framework ◽  
World Health ◽  
Gdp Per Capita ◽  
Current Health ◽  
Monetary Value ◽  
Life Years ◽  
Per Capita

<div>A variant of human capital (or net output) analytical framework was applied to monetarily value DALYs lost from 166 diseases and injuries. The monetary value of each of the 166 diseases (or injuries) was obtained through multiplication of the net 2019 GDP per capita for Kenya by the number of DALYs lost from each specific cause. Where net GDP per capita was calculated by subtracting current health expenditure from the GDP per capita. </div><div> </div><p>The DALYs data for the 166 causes were from IHME (Global Burden of Disease Collaborative Network, 2018), GDP per capita data from the International Monetary Fund world economic outlook database (International Monetary Fund, 2019), and the current health expenditure per person data from the WHO Global Health Expenditure Database (World Health Organization, 2019b). A model consisting of fourteen equations was calculated with Excel Software developed by Microsoft (New York).</p><p> </p>

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