943 resultados para leg inequality


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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.

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By mixing together inequalities based on cyclical variables, such as unemployment, and on structural variables, such as education, usual measurements of income inequality add objects of a di§erent economic nature. Since jobs are not acquired or lost as fast as education or skills, this aggreagation leads to a loss of relavant economic information. Here I propose a di§erent procedure for the calculation of inequality. The procedure uses economic theory to construct an inequality measure of a long-run character, the calculation of which can be performed, though, with just one set of cross-sectional observations. Technically, the procedure is based on the uniqueness of the invariant distribution of wage o§ers in a job-search model. Workers should be pre-grouped by the distribution of wage o§ers they see, and only between-group inequalities should be considered. This construction incorporates the fact that the average wages of all workers in the same group tend to be equalized by the continuous turnover in the job market.

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In this paper I devise a new channel by means of which the (empirically documented) positive correlation between ináation and income inequality can be understood. Available empirical evidence reveals that ináation increases wage dispersion. For this reason, the higher the ináation rate, the higher turns out to be the beneÖt, for a worker, of making additional draws from the distribution of wages, before deciding whether to accept or reject a job o§er. Assuming that some workers have less access to information (wage o§ers) than others, I show that the Gini coe¢ cient of income distribution turns out to be an increasing function of the wage dispersion and, consequently, of the rate of ináation. Two examples are provided to illustrate the mechanism.

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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.

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Latin America is the region that bears the highest rates of inequality in the world. Deininger and Squire (1996) showed that Latin American countries achieved only minor reductions in inequality between 1960 and 1990. On the other hand, East Asian countries, recurrently cited in recent literature on this issue, have significantly narrowed the gap in income inequality, while achieving sustained economic growth. These facts have triggered a renewed discussion on the relationship between income inequality and economic growth. According to the above literature, income inequality could have an adverse effect on countries’ growth rates. The main authors who spouse this line of thinking are Persson and Tebellini (1994), Alesina and Rodrik (1994), Perotti (1996), Bénabou (1996), and Deininger and Squire (1996, 1998). More recently, however, articles were published that questioned the evidence presented previously. Representatives of this new point of view, namely Li and Zou (1998), Barro (1999), Deininger and Olinto (2000) and Forbes (2000), believe that the relation between these variables can be positive, i.e., income inequality can indeed foster economic growth. Using this literature as a starting point, this article seeks to evaluate the relation between income inequality and economic growth in Latin America, based on a 13-country panel, from 1970 to 1995. After briefly reviewing the above articles, this study estimates the per capita GDP and growth rate equations, based on the neoclassical approach for economic growth. It also estimates the Kuznets curve for this sample of countries. Econometric results are in line with recent work conducted in this area – particularly Li and Zou (1998) and Forbes (2000) – and confirm the positive relation between inequality and growth, and also support Kuznets hypothesis.

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This paper presents semiparametric estimators of changes in inequality measures of a dependent variable distribution taking into account the possible changes on the distributions of covariates. When we do not impose parametric assumptions on the conditional distribution of the dependent variable given covariates, this problem becomes equivalent to estimation of distributional impacts of interventions (treatment) when selection to the program is based on observable characteristics. The distributional impacts of a treatment will be calculated as differences in inequality measures of the potential outcomes of receiving and not receiving the treatment. These differences are called here Inequality Treatment Effects (ITE). The estimation procedure involves a first non-parametric step in which the probability of receiving treatment given covariates, the propensity-score, is estimated. Using the inverse probability weighting method to estimate parameters of the marginal distribution of potential outcomes, in the second step weighted sample versions of inequality measures are computed. Root-N consistency, asymptotic normality and semiparametric efficiency are shown for the semiparametric estimators proposed. A Monte Carlo exercise is performed to investigate the behavior in finite samples of the estimator derived in the paper. We also apply our method to the evaluation of a job training program.

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We live in an unjust world characterized by economic inequality. No liberal theory of justice is able to justify it. Inequality is not “solved” with equality of opportunity or meritocracy. Nor by the socialist and republican critique. The poor will have to count with them and with democracy to make social progress reality. In their political struggle, they will face one economic constraint: the expected profit rate must remain attractive to business investors. Yet, giving that technological progress in increasingly capital-saving, this economic constraint does not obstruct that wages grow above the productivity rate and inequality is reduced. What really is an obstacle to social justice in the rich countries is, on one hand, the power that capitalist rentiers retain and financists acquired, and, on the other, the competition originated in low wage countries.

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In this paper, we investigate the nature of income inequality across nations. First, rather than functional forms or parameter values in calibration exercises that can potentially drives results, we estimate, test, and distinguish between types of aggregate production functions currently used in the growth literature. Next, given our panel-regression estimates, we perform several exercises, such as variance decompositions, simulations and counter-factual analyses. The picture that emerges is one where countries grew in the past for different reasons, which should be an important ingredient in policy design. Although there is not a single-factor explanation for the difference in output per-worker across nations, inequality, followed by distortions to capital accumulations and them by human capital accumulation.

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O objetivo deste trabalho é entender mais sobre o papel da liberalização sobre a desigualdade salarial, mais precisamente, sobre a desigualdade residual dos salários. Usando a abertura comercial brasileira, a extensa redução tarifária que ocorreu entre 1987 e 1995, é investigado empiricamente se os diferentes níveis de exposição ao comércio entre os estados contribuíram para os diferentes movimentos da desigualdade. Os resultados indicam que estados mais expostos à liberalização comercial experimentaram um aumento relativo da desigualdade residual dos salários ou, de forma equivalente, uma menor redução. Estes resultados enriquecem a discussão dos efeitos da abertura comercial sobre a desigualdade.

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Investimentos em capital humano são essenciais para o desenvolvimento econômico de um pais. No Brasil, diversas fontes apontam para a falta de mão de obra qualificada como sendo uma das causas de um fraco crescimento econômico. Esta dissertação explora as teorias que ligam desigualdade de renda com performance econômica. A parte empírica se foca em uma das teorias apresentadas, a de imperfeições no mercado de credito. De acordo com esta teoria, mercados de credito imperfeitos são fracos alocadores de recursos e não possibilitam que indivíduos de baixa renda invistam no próprio capital humano. No Brasil, há uma escassez de estudos empíricos focados em testar os canais através dos quais a desigualdade de renda afeta o crescimento, trazendo significância para esta dissertação. Os resultados apresentados aqui foram obtidos através da pesquisa familiar – POF – realizada pelo IBGE. Os dados mostram que investimentos em educação crescem como percentual do orçamento com o aumento da renda familiar. Aumentos de renda para classes de renda já elevadas não provocam igual aumento nas despesas educacionais. Os dados sugerem a existência de uma restrição orçamentária para Brasileiros de baixa e média renda independente da região. Foram encontradas fortes evidencias de que classes de baixa e média renda no Brasil tem acesso limitado ao mercado de credito. Portanto, existe evidencia de que redistribuição aumentaria o gasto agregado em educação

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In this paper we measure inequality of opportunity in daycare and preschool services in Brazil. For this purpose, we construct an opportunity index that modifies the human opportunity index proposed in the literature and used in Barros et al. (2009) to measure inequality in basic opportunities in Latin America and the Caribbean. Specifically, we construct an opportunity measure that includes not only attendance but also parental choice not to enroll children in daycare or preschool, using data from a supplementary questionnaire included in the 2006 version of Pesquisa Nacional por Amostra de Domicílios (PNAD). The results show that there are large differences between our opportunity index and the human opportunity index for children aged 0-3 years old and considerably smaller differences for children aged 4-6 years old, which suggests that preschool may be closer to a basic opportunity than daycare.

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This work investigates the effects of inflation on income distribution. We use a dynamic shopping-time model to show that a differentiated access to transacting technologies by poor and rich consumers is enough to generate a positive link between inflation and the Gini coefficient of income distribution.

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In this paper I claim that, in a long-run perspective, measurements of income inequality, under any of the usual inequality measures used in the literature, are upward biased. The reason is that such measurements are cross-sectional by nature and, therefore, do not take into consideration the turnover in the job market which, in the long run, equalizes within-group (e.g., same-education groups) inequalities. Using a job-search model, I show how to derive the within-group invariant-distribution Gini coefficient of income inequality, how to calculate the size of the bias and how to organize the data in arder to solve the problem. Two examples are provided to illustrate the argument.

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This paper explores the evolution of the cross-section income distribution in economies where endogenous neighborhood formation interacts with positive within-neighborhood feedback effects. We study an economy in which the economic success of adults is determined by the characteristics of the families in the neighborhood in which a person grows up. These feedbacks take two forms. First, the tax base of a neighborhood affects the leveI of education investment in offspring. Second, the effectiveness of education investment is affected by a neighborhood's in come distribution, reflecting factors such as role model or labor market connection effects. Conditions are developed under which endogenous stratification, defined as the tendency for families wi th similar incomes to choose to form common communities, will occur. When families are allowed to choose their neighborhoods, wealthy families will have an incentive to segregate themselves from the rest of the population. This resulting stratification is supported by house price differences between ricli and poor communities. Endogenous stratification can lead to pronounced intertemporal inequality as different families provide very different interaction environments for offspring. When the transformation of human capital into in come exhibits constant retums to scale, cross-section in come differences may also grow across time. As a result, endogenous stratification and neighborhood feedbacks can interact to produce long run inequality.