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 Faktor-faktor Yang Mempengaruhi AHH Provinsi Bali

2019 ◽  
Vol 8 (2) ◽  
pp. 71-83
Author(s):  
Luh Dita Darmayanti ◽  
Surya Dewi Rustariyuni
Keyword(s):  
Life Expectancy ◽  
Government Spending ◽  
Capita Income ◽  
Linear Regression Analysis ◽  
Government Expenditure ◽  
Health Sector ◽  
Per Capita Income ◽  
Income Per Capita ◽  
Education And Health ◽  
Per Capita

The degree of public health can be measured by looking at the amount of Life Expectancy (AHH). AHH is the result of calculating projections often used as one of the People's Welfare Indicators (IKR). Assuming a declining trend in infant mortality rates (IMR) and changes in the population's age composition, the objectives in this study are: 1) to analyze the effect of income per capita, government spending in education, and health simultaneously affect life expectancy in Bali Province / City in the 2011-2017 period and 2) to analyze the effect of per capita income, government spending the education and health sector influences the life expectancy in the Regency / City of Bali Province in the 2011-2017 period. The data used in this study is secondary data in 2011-2017. This study uses Multiple Linear Regression analysis techniques used to process classical assumption test data using Eviews 9. The results of this study stated that the variable income per capita (X1), government expenditure in education (X2), and government expenditure in health (X3) simultaneously affected the life expectancy (Y) in districts/cities in Bali Province. Partially per capita income has a positive and significant impact on life expectancy. Government expenditure in education and government expenditure in health does not affect life expectancy in Bali Province districts/cities.  

scholarly journals Fakta empiris kurva U-terbalik Kuznets mengenai pertumbuhan ekonomi di Provinsi Jambi

2019 ◽  
Vol 14 (1) ◽  
pp. 9-16
Author(s):  
Nessy Fameylan Alin ◽  
Heriberta Heriberta ◽  
Etik Umiyati
Keyword(s):  
Income Inequality ◽  
Capita Income ◽  
Per Capita Income ◽  
Income Per Capita ◽  
Per Capita ◽  
Kuznets Hypothesis ◽  
The Relationship

The study aimed to analyze the development of the gini ratio and income per capita and to prove whether the hypothesis of Kuznets (U-inverted curve) applies in Jambi Province. To prove whether the Kuznets hypothesis applies in Jambi Province through an analysis of the relationship between per capita income and the gini ratio. The results of the study found that the growth of per capita income in Jambi Province was followed by the development of relatively fluctuating income inequality. Therefore,  the Kuznets' hypothesis is not valid in Jambi Province.

scholarly journals Determinan Kualitas Pembangunan Manusia di Kabupaten/Kota Provinsi Jawa Tengah

2018 ◽  
Vol 5 (3) ◽  
pp. 269-277
Author(s):  
Agung Yudhi Pramono ◽  
Etty Soesilowati
Keyword(s):  
Local Government ◽  
Capita Income ◽  
Government Expenditure ◽  
Health Sector ◽  
Least Square ◽  
Dependency Ratio ◽  
Per Capita Income ◽  
Central Java ◽  
Per Capita ◽  
Local Government Expenditure

Penelitian ini bertujuan untuk menganalisis seberapa besar pengaruh pengeluaran pemerintah daerah sektor pendidikan, pengeluaran pemerintah daerah sektor kesehatan, rasio ketergantungan penduduk dan pendapatan perkapita terhadap pembangunan manusia yang diukur dengan IPM. Populasi penelitian terdiri dari 35 Kabupaten/Kota di Provinsi Jawa Tengah, menggunakan data sekunder dari Badan Pusat Statistik Provinsi Jawa Tengah dan Biro Keuangan Sekretaris Daerah Provinsi Jawa Tengah dalam periode 2009 sampai 2013. Variabel penelitian ini indeks pembangunan manusia, pengeluran pemerintah daerah sektor pendidikan, pengeluaran pemerintah daerah sektor kesehatan, rasio ketergantungan penduduk, dan pendapatan perkapita. Dalam penelitian ini, digunakan metode penelitian kuantitatif dengan menggunakan analisis regresi data panel model efek tetap (FEM) dengan metode Generalized Least Square (GLS). Hasil penelitian ini dapat diketahui bahwa pengeluaran pemerintah daerah sektor pendidikan berpengaruh positif dan signifikan terhadap IPM, pengeluaran pemerintah daerah sektor kesehatan berpengaruh positif dan signifikan terhadap IPM, rasio ketergantungan penduduk berpengaruh negatif dan signifikan terhadap IPM, sementara pendapatan perkapita tidak berpengaruh secara signifikan terhadap IPM. This research has purpose to analyze how much influence of the local government expenditure in educational sector, local government expenditure in health sector, dependency ratio, and per capita income of a human development measured by HDI. the population of this research consists of 35 regionals in Central Java and region bureau money secretary of Central Java province among 2009 and 2013 period. the variables used in this research are HDI, local government expenditure in educational sector, local government expenditure in health sector, dependency ratio, and per capita income. in this research, quantitative and regression analysis of Fixed Effect Model is used as well as Generalized Least Square method (GLS). The results of this research are the outcome of regional government in educational and health sector influence significance and positively to the HDI, dependency ratio significance and negatively influence to the HDI, while per capita income does not influence significance to the HDI.

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 Relationship between income inequality, socioeconomic development, vulnerability index, and maternal mortality in Brazil, 2017

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Maria do Socorro Candeira Costa ◽  
Francisco Winter dos Santos Figueiredo
Keyword(s):  
Maternal Mortality ◽  
Capita Income ◽  
Gini Index ◽  
Socioeconomic Development ◽  
Maternal Mortality Ratio ◽  
Socioeconomic Indicators ◽  
Per Capita Income ◽  
Socioeconomic Determinants ◽  
Income Per Capita ◽  
Per Capita

Abstract Background Public health recognizes that health conditions depend on factors related to the development patterns income distribution, degree of poverty, working conditions, among other social determinants. The objective of this study was to analyze the association of maternal mortality with the Human Development Index (HDI), Gini Index, Income per capita, and the Social Vulnerability. Method The study analyzed the relationship between MMR and socioeconomic indicators in the 26 federative units and the Federal District of Brazil, in 2017. The socioeconomic indicators used in the study were: HDI, Gini Index, Income per capita, and SVI. Crude and adjusted linear regression were performed between maternal mortality and socioeconomic indicators. Results When analyzing which socioeconomic determinants that are related to maternal mortality ratio rates, a higher per capita income positive effect was observed for lower MMR (β = − 150.8; CI 95% -289.9 to − 11.7; r2 = 0.17; p = 0.035), as well as a trend of higher MMR in relation to the SVI (β = 97.7; CI 95% -12.2 to 207.6; r2 = 0.12; p = 0.079). In model found by the stepwise forward selections, only the per capita income was um index related to less RMM (β = − 0.02; CI 95% -0.05 to − 0.002; r2 = 0.15; p = 0.028). Conclusion The findings showed that the per capita income has a negative association MMR in the different states of Brazil, but seems canceled because of the other socioeconomic determinants related to the poor live conditions.

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 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.

scholarly journals ANALISIS MIDDLE INCOME TRAP DI INDONESIA

2017 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Asmirawati Asmirawati
Keyword(s):  
Capita Income ◽  
Direct Investment ◽  
Least Square ◽  
High Tech ◽  
Per Capita Income ◽  
Middle Income ◽  
Level Of Education ◽  
Income Per Capita ◽  
Per Capita ◽  
Middle Income Trap

This paper aims to analyze middle income trap in Indonesia where per capita income is the main indicator in determining whether a country is included in the middle income category or not. By looking at the effect of high technology products , education level, direct investment and dependent ratio on per capita income in Indonesia. The results of this model use the ordinary least square method, which shows that the export of high-tech products has a positive and significant effect on per capita income, the level of education has a positive and significant effect on per capita income, direct investment has a negative and significant effect on per capita income, the ratio has a positive and significant effect. income per capita and high-tech product exports, level of education, direct investment, and the ratio have a significant effect on income per capita in Indonesia.

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