scholarly journals Per Capita Income Inequality in Czech Households Before, During and After the Economic and Financial Crisis

2020 ◽  
Vol 68 (5) ◽  
pp. 885-899
Author(s):  
Markéta Hnízdilová ◽  
Václav Adamec
Keyword(s):  
Czech Republic ◽  
Financial Crisis ◽  
Income Inequality ◽  
Capita Income ◽  
Household Head ◽  
Income Level ◽  
Per Capita Income ◽  
The Czech Republic ◽  
Per Capita ◽  
Economic And Financial Crisis

The study tackles the issue of distribution inequality in equalized per capita income in households defined by multiple grouping criteria in the Czech Republic before, during and after the economic and financial crisis. The factors were economic status of the household head, number of children, education and the NUTS 3 administrative regions. Interval grouped per capita income data assembled within the EU-SILC framework via quota sampling were received from czso.cz for 2008, 2012 and 2016. Indicators of income level, variation, quantiles, medial and Gini index were calculated for the respective household groups. Income concentration in the Czech Republic is considerably low among OECD states and still decreasing due to government social and economic policy and favourable phase of the economic cycle. The largest income inequality was detected in the self-employed, jobless and qualified employees, households with 3 or more children, single-parent families with dependants, households with one or both tertiary educated parents or households residing in Prague or Středočeský region. The threat of poverty is imminent in the jobless, economically inactive pensioners, unqualified labourers and households with 3 or more children. Geographically, the poverty affects households mostly in Moravskoslezský or Ústecký regions. Government measures evidently helped reduce income inequality, poverty and social exclusion in Ústecký region in 2008. The least affected regions by poverty were Prague and Středočeský region. Significant differences in income level or concentration of income distributions by regional and other household grouping criteria were revealed.

scholarly journals Modelling the Income Distributions in the Czech Republic since 1992

2016 ◽  
Vol 41 (2) ◽  
Author(s):  
Diana Bílková ◽  
Ivana Malá
Keyword(s):  
Czech Republic ◽  
Capita Income ◽  
Likelihood Method ◽  
Per Capita Income ◽  
Unknown Parameters ◽  
Average Growth ◽  
The Czech Republic ◽  
Income Distributions ◽  
Per Capita ◽  
The Impact

The goal of this article is to study incomes in the Czech Republic and their development since 1992. The net annual per capita income of Czech households is analysed for all households and their respective subpopulations. Data from the microcensus 1992, 1996, 2002, and EU-SILC 2005–2008 surveys carried out by the Czech Statistical Office are used. The subpopulations are defined by a household’s location (Bohemia or Moravia), and education and age of the head of the household in order to compare the distributions ofthe income in Bohemia and Moravia and to quantify the impact of education and age on incomes. The three-parameter lognormal distribution is chosen as a probability distribution to model the per capita income distribution for the whole population and for subpopulations. To estimate the unknown parameters, the maximum likelihood method and that of L-moments are employed. The medians of equalised incomes are given for the EU members and the average growth in the 2004–2007 period is compared. For the Czech Republic, a comparison of the medians of per capita and equivalised income is made.

Regional Economic Growth and Inequality in India: A Sector-wise Decomposition Analysis

2020 ◽  
pp. 097674792091082
Author(s):  
Ranjan Aneja ◽  
Barkha ◽  
Umer Jeelanie Banday
Keyword(s):  
Income Inequality ◽  
Capita Income ◽  
Decomposition Analysis ◽  
High Growth ◽  
Major Change ◽  
Per Capita Income ◽  
Tertiary Sector ◽  
Reform Period ◽  
Per Capita

This article attempts to examine the behaviour of various sectors, with emphasis on the role of income inequality. First, the article estimates the sectoral decomposition in terms of net state domestic product (NSDP) among different states from years 1991–1992 to 2016–2017. Second, we analyse the sector-wise decomposition of regional inequality in term of per capita income. Finally, we analyse the role of developmental expenditure in regional inequalities in term of per capita developmental expenditure across various states. Based on empirical results, India has witnessed a high growth in per capita income in the post-reform period. With high growth rate, the sectoral composition of income has also registered a major change. The tertiary sector is the major contributor to growth in the post-reform period. At the sectoral level, disparity decreased within the sectors in case of primary and tertiary sector and increased in secondary sector. However, overall, the tertiary and secondary sectors are more responsible for raising the income inequality among the states while primary sector is offsetting this gap. JEL: O15, I14, I32, O12

scholarly journals PENGARUH KETIMPANGAN PENDAPATAN, PENDAPATAN PER KAPITA, DAN PENGELUARAN PEMERINTAH DI BIDANG KESEHATAN TERHADAP SEKTOR KESEHATAN DI INDONESIA

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Uswatun Hasanah
Keyword(s):  
Income Inequality ◽  
Capita Income ◽  
Health Effect ◽  
Government Expenditure ◽  
Health Sector ◽  
Research Area ◽  
External Factors ◽  
Per Capita Income ◽  
Income Per Capita ◽  
Per Capita

AbstractHuman resource is one of capital importance in the development of a nation. One of the important aspects that affect human resources are a public health level, where health sector has an important role. The status of one's health is the result of the interaction of various factors, namely internal and external factors. Internal factors consist of physical and psychological factors, while external factors consist of economic factors, education, environment and cultureThis research aims to examine and analyze the effect of income inequality as measured by the Gini Ratio against the health sector as measured by life expectancy in Indonesia in 2005-2013. On the research of regression equation using data panels with Random Effects Model approach. The results of this research is the inequality of income, per capita income, and Government expenditure in the health effect simultaneously against health sector in Indonesia in 2005-2013 and is partial, inequality of income, per capita income, and Government expenditure in the health sector impact health sector in Indonesia in 2005-2013. Keywords : Health sector, income inequality, income per capita, Government expenditure in health sector. Research Area: Indonesia

scholarly journals Socio-Economic and Demographic Factors of Poverty Alleviation in Pakistan: A Case Study of Southern Punjab

2020 ◽  
Vol 6 (2) ◽  
pp. 525-538
Author(s):  
Rashid Ahmad ◽  
Muhammad Zahir Faridi
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Capita Income ◽  
Household Head ◽  
Rural Poverty ◽  
Least Square ◽  
Per Capita Income ◽  
High Dependency ◽  
Per Capita ◽  
Dependency Rate

This study aims to explore the socio-economic and demographic determinants of poverty in Southern Punjab by using the cross sectional data consisting of 785 household heads. Binary logistic regression  and ordinary least square method are used for estimation. The findings exhibit that the variables like family system, household size, presence of disease and status of employment of household head are positively and significantly related to  poverty whereas household head age, rural-to-urban migration,  years of schooling,  number of earners, women status of work, remittances, the physical assets value and ownership of house significantly and negatively influence the likelihood of poverty and positively influence the per capita income of the households in Southern Punjab. The study also provides the comparison of regional and division level. It is concluded that DG Khan division is the poorest among all the divisions of the southern Punjab. In DG Khan Division, the households have less education, high dependency ratio. In rural areas of southern Punjab, there is more poverty as compare to urban areas. The rural poverty is due to many factors like high dependency rate, lower level of education, adoption of profession, lower per capita income, dissaving. It is suggested that education should be promoted, employment opportunity should be provided so that dependency rate may be reduced, rural areas should be restructured by provision of basic necessities of life.

scholarly journals Effect of per Capita Income on the Relationship between Periodontal Disease during Pregnancy and the Risk of Preterm Birth and Low Birth Weight Newborn. Systematic Review and Meta-Analysis

2020 ◽  
Vol 17 (21) ◽  
pp. 8015
Author(s):  
Carmen Alba Moliner-Sánchez ◽  
José Enrique Iranzo-Cortés ◽  
José Manuel Almerich-Silla ◽  
Carlos Bellot-Arcís ◽  
José Carmelo Ortolá-Siscar ◽  
...  
Keyword(s):  
Birth Weight ◽  
Preterm Birth ◽  
Low Birth Weight ◽  
Periodontal Disease ◽  
Pregnant Women ◽  
Capita Income ◽  
Meta Analysis ◽  
Income Level ◽  
Per Capita Income ◽  
Per Capita

This work analyzed the available evidence in the scientific literature about the risk of preterm birth and/or giving birth to low birth weight newborns in pregnant women with periodontal disease. A systematic search was carried out in three databases for observational cohort studies that related periodontal disease in pregnant women with the risk of preterm delivery and/or low birth weight, and that gave their results in relative risk (RR) values. Eleven articles were found, meeting the inclusion criteria. Statistically significant values were obtained regarding the risk of preterm birth in pregnant women with periodontitis (RR = 1.67 (1.17–2.38), 95% confidence interval (CI)), and low birth weight (RR = 2.53 (1.61–3.98) 95% CI). When a meta-regression was carried out to relate these results to the income level of each country, statistically significant results were also obtained; on the one hand, for preterm birth, a RR = 1.8 (1.43–2.27) 95% CI was obtained and, on the other hand, for low birth weight, RR = 2.9 (1.98–4.26) 95% CI. A statistically significant association of periodontitis, and the two childbirth complications studied was found, when studying the association between these results and the country’s per capita income level. However, more studies and clinical trials are needed in this regard to confirm the conclusions obtained.

scholarly journals EVIDÊNCIAS EMPÍRICAS SOBRE CONVERGÊNCIA DA DESIGUALDADE DE RENDA ENTRE OS MUNICÍPIOS CEARENSES

2015 ◽  
Vol 18 (2) ◽  
pp. 557
Author(s):  
Airton Lopes Amorim ◽  
Ricardo Bruno Nascimento dos Santos ◽  
Eliane Pinheiro de Sousa ◽  
Daniel Arruda Coronel
Keyword(s):  
Income Inequality ◽  
Capita Income ◽  
Gini Index ◽  
Initial Period ◽  
Threshold Effect ◽  
Per Capita Income ◽  
Conditional Convergence ◽  
Average Value ◽  
Convergence Clubs ◽  
Per Capita

A desigualdade de renda tende a diminuir em municípios com elevada desigualdade e a aumentar naqueles com baixa desigualdade? Este trabalho tenta responder a essa questão ao verificar se existiu convergência da desigualdade de renda entreos municípios cearenses, nos anos 1991 e 2000. A principal medida de desigualdade de renda utilizada foi o índice de Gini, sendoos testes de convergência realizados por meio de modelos com efeito threshold, nos quais as variáveis concernentes ao índice deGini, à renda per capita e aos anos de estudo, medidas no período inicial, foram consideradas como possíveis variáveis threshold. Os resultados permitiram rejeitar a hipótese de clubes de convergência da desigualdade de renda entre os municípios cearenses. Noentanto, não se pode rejeitar a hipótese de convergência condicional da desigualdade de renda entre os mesmos, sendo que eles estariam convergindo para um valor médio de equilíbrio de desigualdade de renda maior, ou seja, os municípios cearenses estariam tornando-se mais concentradores de renda per capita. Palavras-chave: Desigualdade de renda, Índice de Gini, efeitos Threshold.EMPIRICAL EVIDENCES ABOUT THE CONVERGENCE OF INCOME INEQUALITY AMONG CITIES FROM CEARAAbstract: The income inequality tends to decrease in municipalities with high inequality and increase in those with low inequality? This paper intends to answer this question by checking if there was convergence of income inequality in the municipalities of the State of Ceará, in the years 1991 and 2000. The main measurement of income inequality used was the Gini index, with the convergencetests conducted through models with threshold effect, in which the variables relating to the Gini index, to the per capita income and to the years of study were considered, measured in the initial period as possible threshold variables. The results allowed rejectingthe hypothesis of convergence clubs of the per capita income inequality among the cities from Ceará. However there is no way to reject the hypothesis of conditional convergence of the income inequality in the municipalities among the same, where these would be converging to an average value of the bigger income inequality, that is, they would be turning themselves into more per capita income-concentrating municipalities.Key words: Income inequality, Gini Index, Threshold effect.

scholarly journals Livelihood capitals on income inequality among rural households: evidence from China

2020 ◽  
Vol 50 (2) ◽  
Author(s):  
Fan Yang ◽  
Yao Jiang ◽  
Weizhong Zeng
Keyword(s):  
Income Inequality ◽  
Household Income ◽  
Capita Income ◽  
Rural Households ◽  
Per Capita Income ◽  
Agricultural Income ◽  
Total Household Income ◽  
Property Income ◽  
Per Capita ◽  
Livelihood Capitals

ABSTRACT: We used the data of the China Labor-force Dynamics Survey 2014 to examine the effects of livelihood capitals which include natural, material, human, financial, and social capitals on total household income, per capita income, agricultural income, wage income, operational income, and property income inequality among rural households in China. Results showed that different kinds of livelihood capitals have different effects on different types of rural households’ income. Specifically; (1) although, the area of cultivated land reduces agricultural income inequality, it increases per capita income inequality. (2) Forest land area enlarges per capita income inequality and total household income inequality. (3) Tractor variable reduces inequality in agricultural income and total household income. (4) While reducing the property income inequality, education variable enlarges the wage income inequality, the per capita income inequality and the total household income inequality. (5) Book variable reduces property income inequality. (6) Loan variable increases inequality in agricultural incomes. (7) Party variable reduces the agricultural income inequality. (8) Although, the internet variable increases agricultural income inequality, and property income inequality, it reduces wage income inequality, operational income inequality, per capita income, and total household income inequality.

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