Medida de concentración de Gini : Observaciones sobre las fórmulas de cálculo y el Principio de Población de Dalton. Propuesta de un factor de corrección

En la primera parte del presente trabajo se investigan diferentes formas de cálculo de la razón de concentración conocida como Coeficiente o Índice de Gini, y el no cumplimiento del axioma conocido como de "invariancia a la replicación" o "Principio de Población de Dalton" en algunas de ellas. El alcance de las conclusiones se limita al comportamiento de las fórmulas sometidas a prueba (se encuentran entre las más conocidas) cuando son aplicadas a distribuciones de datos desagregados. En la segunda parte se propone un factor de corrección para las fórmulas de cálculo analizadas, de manera que satisfagan el Principio de Población.

Medida de concentración de Gini : Observaciones sobre las fórmulas de cálculo y el Principio de Población de Dalton. Propuesta de un factor de corrección

En la primera parte del presente trabajo se investigan diferentes formas de cálculo de la razón de concentración conocida como Coeficiente o Índice de Gini, y el no cumplimiento del axioma conocido como de "invariancia a la replicación" o "Principio de Población de Dalton" en algunas de ellas. El alcance de las conclusiones se limita al comportamiento de las fórmulas sometidas a prueba (se encuentran entre las más conocidas) cuando son aplicadas a distribuciones de datos desagregados. En la segunda parte se propone un factor de corrección para las fórmulas de cálculo analizadas, de manera que satisfagan el Principio de Población.

Medida de concentración de Gini : Observaciones sobre las fórmulas de cálculo y el Principio de Población de Dalton. Propuesta de un factor de corrección

En la primera parte del presente trabajo se investigan diferentes formas de cálculo de la razón de concentración conocida como Coeficiente o Índice de Gini, y el no cumplimiento del axioma conocido como de "invariancia a la replicación" o "Principio de Población de Dalton" en algunas de ellas. El alcance de las conclusiones se limita al comportamiento de las fórmulas sometidas a prueba (se encuentran entre las más conocidas) cuando son aplicadas a distribuciones de datos desagregados. En la segunda parte se propone un factor de corrección para las fórmulas de cálculo analizadas, de manera que satisfagan el Principio de Población.

On Truncated Versions of Certain Measures of Inequality and Stability

The present study focuses attention on defining certain measures of income inequality for the truncated distributions and characterization of probability distributions using the functional form of these measures, extension of some measures of inequality and stability to higher dimensions, characterization of bivariate models using the above concepts and estimation of some measures of inequality using the Bayesian techniques. The thesis defines certain measures of income inequality for the truncated distributions and studies the effect of truncation upon these measures. An important measure used in Reliability theory, to measure the stability of the component is the residual entropy function. This concept can advantageously used as a measure of inequality of truncated distributions. The geometric mean comes up as handy tool in the measurement of income inequality. The geometric vitality function being the geometric mean of the truncated random variable can be advantageously utilized to measure inequality of the truncated distributions. The study includes problem of estimation of the Lorenz curve, Gini-index and variance of logarithms for the Pareto distribution using Bayesian techniques.

Socioeconomic inequality profiles in physical and developmental health from 0-7 years : Australian National Study

Background: Early and persistent exposure to socioeconomic disadvantage impairs children’s health and wellbeing. However, it is unclear at what age health inequalities emerge or whether these relationships vary across ages and outcomes. We address these issues using cross-sectional Australian population data on the physical and developmental health of children at ages 0-1, 2-3, 4-5 and 6-7 years. Methods: 10 physical and developmental health outcomes were assessed in 2004 and 2006 for two cohorts each comprising around 5000 children. Socioeconomic position was measured as a composite of parental education, occupation and household income. Results: Lower socioeconomic position was associated with increased odds for poor outcomes. For physical health outcomes and socio-emotional competence, associations were similar across age groups and were consistent with either threshold effects (for poor general health, special healthcare needs and socio-emotional competence) or gradient effects (for illness with wheeze, sleep problems and injury). For socio-emotional difficulties, communication, vocabulary and emergent literacy, stronger socioeconomic associations were observed. The patterns were linear or accelerated and varied across ages. Conclusions: From very early childhood, social disadvantage was associated with poorer outcomes across most measures of physical and developmental health and showed no evidence of either strengthening or attenuating at older compared to younger ages. Findings confirm the importance of early childhood as a key focus for health promotion and prevention efforts.

Does spatial clustering help explaining differences in the inequality of income distribution? : evidence from Argentina

Resumen: Este artículo analiza la relación entre la agrupación espacial de la distribución del ingreso y la desigualdad en las provincias de Argentina. El objetivo de este trabajo es usar técnicas espaciales para analizar hasta que punto la agrupación espacial de la distribución del ingreso afecta la desigualdad de la distribución del ingreso en un contexto regional de Argentina. En general, la literatura de desigualdad implícitamente considera a cada región o provincia como una entidad independiente y el potencial para la observación de la interacción a través del espacio a menudo se ha ignorado. Mientras tanto, la autocorrelación espacial ocurre cuando la distribución espacial de la variable de interés exhibe un patrón sistemático. Yo computo tres medidas de autocorrelación espacial global: La I de Moran, c de Geary, y G de Getis y Ord, como grado de CLUSTERING provincial entre 1991 y 2002. La principal conclusión del trabajo es que hay evidencia que provincias con desigualdad relativamente alta (baja) tienden a ser localizadas cerca de otras provincias con alta (baja) desigualdad más a menudo de lo esperado debido al azar. Por ende cada provincia no debería ser vista como una observación independiente, como ha sido supuesto implícitamente en estudios previos sobre la desigualdad de ingresos regional.

The role of income inequality on fiscal multipliers

A Work Project, presented as part of the requirements for the Award of a Masters Double Degree in Economics from the Nova School of Business and Economics and University of Maastricht

Spatial Inequality in Chile

Despite success in reducing poverty over the last twenty years, inequality in Chile has remained virtually unchanged, making Chile one of the least equal countries in the world. High levels of inequality have been shown to hamper further reductions in poverty as well as economic growth and local inequality has been shown to affect such outcomes as violence and health. The study of inequality at the local level is thus crucial for understanding the economic well-being of a country. Local measures of inequality have been difficult to obtain, but recent theoretical advances have enabled the combination of survey and census data to obtain estimators of inequality that are robust at disaggregated geographic levels. In this paper, we employ this methodology to produce consistent estimators of inequality for every county in Chile. We find a great deal of variation in inequality, with county-level Gini coefficients ranging from 0.41 to 0.63.

Income inequality in a job-search model with heterogeneous discount factors: (revised version, forthcoming 2006, Revista Economia)

This paper investigates the income inequality generated by a jobsearch process when di§erent cohorts of homogeneous workers are allowed to have di§erent degrees of impatience. Using the fact the average wage under the invariant Markovian distribution is a decreasing function of the discount factor (Cysne (2004, 2006)), I show that the Lorenz curve and the between-cohort Gini coe¢ cient of income inequality can be easily derived in this case. An example with arbitrary measures regarding the wage o§ers and the distribution of time preferences among cohorts provides some insights into how much income inequality can be generated, and into how it varies as a function of the probability of unemployment and of the probability that the worker does not Önd a job o§er each period.

On the positive correlation between income inequality and unemployment

Several empirical studies in the literature have documented the existence of a positive correlation between income inequalitiy and unemployment. I provide a theoretical framework under which this correlation can be better understood. The analysis is based on a dynamic job search under uncertainty. I start by proving the uniqueness of a stationary distribution of wages in the economy. Drawing upon this distribution, I provide a general expression for the Gini coefficient of income inequality. The expression has the advantage of not requiring a particular specification of the distribution of wage offers. Next, I show how the Gini coefficient varies as a function of the parameters of the model, and how it can be expected to be positively correlated with the rate of unemployment. Two examples are offered. The first, of a technical nature, to show that the convergence of the measures implied by the underlying Markov process can fail in some cases. The second, to provide a quantitative assessment of the model and of the mechanism linking unemployment and inequality.

Income inequality: the role of impatience in a job-search process

This paper investigates the income inequality generated by a jobsearch process when di§erent cohorts of homogeneous workers are allowed to have di§erent degrees of impatience. Using the fact the average wage under the invariant Markovian distribution is a decreasing function of the time preference (Cysne (2004)), I show that the Lorenz curve and the between-cohort Gini coe¢ cient of income inequality can be easily derived in this case. An example with arbitrary measures regarding the wage o§ers and the distribution of time preferences among cohorts provides some quantitative insights into how much income inequality can be generated, and into how it varies as a function of the probability of unemployment and of the probability that the worker does not Önd a job o§er each period.

Growth, poverty and inequality in Central America

Includes bibliography

Income inequality in Brazil: What has changed in recent years?

Includes bibliography.

Poverty Reduction and the Income Inequality in China

In 2000, the United Nations adopted the Millennium Development Goals which set targets for raising living standards in low-income countries. The first goal was to “eradicate extreme poverty and hunger” (United Nations). The World Bank defines extreme poverty as income of less than $1.25 per day (World Bank, 2010a). Based on this definition, the World Bank estimates that the percentage of the population in China living in extreme poverty has fallen from 84 percent in 1981 to about 16 percent in 2005, a period during which China’s population grew by more than 300 million people (see Table 1 on last page). Because China is a very large country with a current population approaching 1.4 billion (more than four times the United States population), its dramatic reduction in poverty over the past 30 years has had a profound effect on global poverty measures. In fact, poverty reduction in China is the main reason that the incidence of extreme poverty in developing countries has fallen from about 52 percent in 1981 to 25 percent in 2005 (Table 1). While the absolute number of poor in China fell by some 627 million, the number of poor in other developing countries actually grew slightly (from 1,065 million to 1,166 million). These figures represent a decline in the percentage of the total population in poverty in other developing countries because of general population growth over that 25-year period (World Bank, 2010b).