scholarly journals Inequality in Early Modern Spain: New evidence from the Ensenada Cadastre in Castile, c. 1750

2020 ◽  
pp. 255-273
Author(s):  
Esteban Nicolini ◽  
Fernando Ramos-Palencia
Keyword(s):  
Income Inequality ◽  
Capita Income ◽  
18Th Century ◽  
Social Conflict ◽  
Social Spending ◽  
Evidence Based ◽  
European Regions ◽  
Early Modern Spain ◽  
Per Capita ◽  
New Evidence

This chapter addresses income inequality by offering new evidence based on the Ensenada Cadastre, a unique database on Castilian households circa 1750. We find that inequality in 18th-century Spain was substantial, especially in urban and/or highly populated areas. There was also a positive – but somewhat weaker – relationship not only between inequality and per capita income but also between inequality and poverty. We posit that extreme economic inequality was likely responsible for numerous episodes of social conflict. Finally, the extent of formalized charity and social spending was less than in other Western European regions.

Political Finance and Participation in Congressional Elections

1976 ◽  
Vol 425 (1) ◽  
pp. 59-73 ◽  
Author(s):  
Paul A. Dawson ◽  
James E. Zinser
Keyword(s):  
Income Inequality ◽  
Political Parties ◽  
Capita Income ◽  
Congressional Elections ◽  
Campaign Contributions ◽  
Factors Affecting ◽  
Political Finance ◽  
Per Capita ◽  
Registered Voters ◽  
Campaign Expenditures

Citizens participate in the electoral process both to enjoy intrinsic benefits and in the hope of future bene fits. Factors affecting the strength of these consumption and investment motives therefore will affect registration and turnout rates, levels of campaign contributions, and electoral margins. To some extent, the strength of these motives is fixed by relatively static factors: levels of district per capita income, the degree of income inequality, the partisan division of registered voters. However, both motives also are affected by factors more apt to vary: for example, statutory arrangements, the activities of political parties, levels and types of campaign expenditures. In particular, statutory arrangements and the activities of parties which reduce costs can increase participation. Moreover, substan tial efforts to alter the partisan division of registered voters can increase campaign contributions. Also, campaign expenditures channel motivations in partisan directions, stim ulate partisan turnout, and affect electoral margins. Results reported here suggest the likelihood of bipartisan support for policies facilitating registration and voting, challenge assumptions about the effects of incumbency on campaign contributions, raise doubts about legislated ceilings on cam paign expenditures, and weaken the case for public financing of congressional elections.

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

An Econometric Analysis of the Links Between Income Inequality and Economic Growth

2009 ◽  
pp. 130
Author(s):  
Yohannes G. Hailu ◽  
Tesfa G. Gebremedhin ◽  
Randall W. Jackson
Keyword(s):  
Economic Growth ◽  
Income Inequality ◽  
Empirical Evidence ◽  
Growth Model ◽  
Capita Income ◽  
Regional Growth ◽  
County Level ◽  
Income Inequalities ◽  
Per Capita ◽  
The Relationship

This study investigates temporal demographic changes and income inequalities, and more importantly the relationship between income inequality and economic growth inWest Virginia. Departing from earlier studies, a regional growth model is utilized and empirically tested using county level West Virginia data (1990-2000). Results suggest that per-capita income change is positively related to population and employment changes but negatively related to income inequality. This empirical evidence indicates that higher income inequality can potentially hinder economic growth.

A panel vector AutoRegression analysis of income inequality dynamics in each of the 50 states of USA

2017 ◽  
Vol 44 (6) ◽  
pp. 797-815
Author(s):  
Olugbenga Onafowora ◽  
Oluwole Owoye
Keyword(s):  
Income Inequality ◽  
Educational Attainment ◽  
Capita Income ◽  
Economic Freedom ◽  
Vector Autoregression ◽  
Population Ageing ◽  
Content Type ◽  
Long Run ◽  
Per Capita ◽  
Panel Vector Autoregression

Purpose The purpose of this paper is to investigate the income inequality dynamics in each of the 50 states of USA over the period 1981-2011. Design/methodology/approach The paper estimates an augmented Kuznets curve panel Vector AutoRegression in per capita income, economic freedom, educational attainment, unemployment, and population ageing along with evaluating generalized impulse responses functions (GIRF) and generalized forecast-error variance decompositions (GFEVD). Findings All the variables are integrated of order one and are panel cointegrated. Kuznets’ hypothesized inverted U-shaped relationship between inequality and growth is not supported by the data. Unemployment and population ageing have statistically significant positive effects on inequality in the long-run; education has statistically significant negative impact; economic freedom has statistically insignificant positive effect. Long-run bidirectional causality exists among the variables. GFEVD show that excluding income inequality itself, variation in income inequality is more influenced by perturbations in per capita income, educational attainment, and unemployment. GIRF corroborate the results of the GFEVD. Originality/value This paper fulfills an identified need to study the causal relationship between inequality and its determining factors without assuming the a priori exogeneity or endogeneity of the underlying variables.

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 Global Inequality in Life Expectancies: What Role Does Income Inequality Play?

2020 ◽  
Author(s):  
Nirajana Banerjee ◽  
Ritojeet Basu ◽  
Ananya De ◽  
Monalisa Poali
Keyword(s):  
Income Inequality ◽  
Life Expectancy ◽  
Gini Coefficient ◽  
Capita Income ◽  
Health Expenditure ◽  
Global Inequality ◽  
Life Expectancy At Birth ◽  
Choropleth Maps ◽  
Per Capita ◽  
Over Time

Context: Life expectancy best helps to capture the health and well-being of a population. However, wide differences are seen in life expectancies across different countries and at different points of time.Research objective: This study examines trends in global inequalities in Life Expectancy at birth between countries from 1960 to 2017, and studies how income inequality affects inequality in life expectancy.Data and methodology: Life expectancy at birth is the main variable under study. We have also used data on GDP per capita at purchasing power parity, Health Expenditure per capita and Government Expenditure on health per capita. Six measures of inequality have been used, primary being the Gini coefficient. We have divided the countries into four groups according to the World Bank Classification Scheme, and have used graphs, choropleth maps and Moran’s I for statistical analysis. The causal relationship between inequality in Life Expectancy and per capita GDP is examined using reduced form regression models.Findings: The life expectancy at birth shows a steadily rising trend. The choropleth maps indicate considerable spatial variations in life expectancy, which are stable over time. There is a decline in the global inequality in life expectancy over time. Moreover, the decomposition analysis for the Gini coefficient shows that in any year, the between groups inequality is more important than the within groups inequality. This is corroborated by the decomposition of Gini over time. We infer from the devised regression models that there is a positive association between per capita income inequality and inequality in life expectancy. The regressions point out evidence that inequality in lifespan and inequality in per capita income can be explained in terms of inequality in health expenditure.

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.

Sign in / Sign up

Export Citation Format

Share Document