nep-ltv New Economics Papers
on Unemployment, Inequality and Poverty
Issue of 2006‒08‒05
seven papers chosen by
Maximo Rossi
Universidad de la Republica

  1. Estimation and interpretation of measures of inequality, poverty, and social welfare using Stata By Stephen P. Jenkins
  2. Multidimensional Generalized Gini Indices By Thibault Gajdos; John Weymark
  3. Comparisons of income mobility profiles By Van Kerm, Philippe
  4. Earnings Losses of Displaced Workers: Evidence from a Matched Employer-employee Data Set By Anabela Carneiro; Pedro Portugal
  5. Openness, inequality, and poverty : endowments matter By Gourdon, Julien; Maystre, Nicolas; de Melo, Jaime
  6. Money and Mental Wellbeing : A Longitudinal Study of Medium-Sized Lottery Wins By Gardner, Jonathan; Oswald, Andrew J.
  7. Distribution and Development in a Model of Misgovernance By Blackburn, Keith; Forgues-Puccio, Gonzalo F.

  1. By: Stephen P. Jenkins (University of Essex)
    Abstract: This presentation reviews methods for summarizing and comparing income distributions, together with the related literature about variance estimation for a range of summary measures. Although the focus is on income and the perspective is that of an economist, the methods have been widely applied to other variables, including health-related ones, and by researchers from many disciplines. Topics covered include the measurement of inequality, poverty, and social welfare, and distributional comparisons based on the dominance methods as well as summary indices. Illustrations are provided using a suite of public-domain Stata programs written by the author and collaborators (e.g., glcurve, ineqdeco, povdeco, sumdist, svyatk, svygei, svylorenz), together with built-in commands.
    Date: 2006–07–23
  2. By: Thibault Gajdos (CREST - Centre de Recherche en Économie et Statistique - [INSEE] - [ École Nationale de la Statistique et de l'Administration Économique]); John Weymark (Department of Economics, Vanderbilt University - [Vanderbilt University])
    Abstract: The axioms that characterize the generalized Gini social evaluation orderings for one-dimensional distributions are extended to the multidimensional attributes case. A social evaluation ordering is shown to have a two-stage aggregation representation if these axioms and a separability assumption are satisfied. In the first stage, the distributions of each attribute are aggregated using generalized Gini social evaluation functions. The functional form of the second-stage aggregator depends on the number of attributes and on which version of a comonotonic additivity axiom is used. The implications of these results for the corresponding multidimensional indices of relative and absolute inequality are also considered.
    Keywords: Generalized Gini, multidimensional inequality
    Date: 2006–07–17
  3. By: Van Kerm, Philippe (CEPS/INSTEAD, Luxembourg)
    Abstract: Methods are developed for income mobility comparisons between countries or between population subgroups based on the construction of mobility profiles. Mobility profiles provide an evocative picture of both the magnitude of income changes in a population, and its distribution across the income range. Comparisons of mobility profiles permit assessments in which mobility among the poor is given greater weight than mobility among the rich. Non-intersection of mobility profiles is shown to correspond with unambiguous rankings according to a large class of functions for the social evaluation of mobility. Particular focus is put on generalized Gini social evaluation functions from which summary indices are derived to obtain complete orderings. An empirical application based on the European Community Household Panel survey illustrates the usefulness of the methods and show how they can be used to shed new light on `pro-poor growth' issues.
    Keywords: income mobility; pro-poor growth ; dominance
    JEL: D31 D63 I32
    Date: 2006–07
  4. By: Anabela Carneiro (CETE, Faculdade de Economia, Universidade do Porto); Pedro Portugal (Banco de Portugal and Universidade Nova de Lisboa)
    Abstract: This paper examines the long-term earnings losses of displaced workers in Portugal, using a nationally representative longitudinal linked employer-employee data set. The results show that four years after displacement the earnings of displaced workers remain around 9% (women) to 12% (men) below their counterfactual expected levels. The post-displacement earnings losses are mainly associated with the loss of tenure within the firm and, to a lesser extent, to the loss of sector-specific features. Furthermore, workers who experienced a spell of nonemployment are the most affected by job displacement. Finally, this study points to the importance of controlling for employers' characteristics in this type of wages-dynamic analysis, since there are systematic differences in earnings between displaced and non-displaced workers that stem from differences in firm characteristics. Ignoring them may confound the evaluation of the earnings losses.
    Keywords: Displacement, earnings losses determinants, firm characteristics
    JEL: J31 J63 J65
    Date: 2006–06
  5. By: Gourdon, Julien; Maystre, Nicolas; de Melo, Jaime
    Abstract: Using tariffs as a measure of openness, the authors find consistent evidence that the conditional effects of trade liberalization on inequality are correlated with relative factor endowments. Trade liberalization is associated with increases in inequality in countries well-endowed in highly skilled workers and capital or with workers that have very low education levels and in countries relatively well-endowed in mining and fuels. Trade liberalization is associated with decreases in inequality in countries that are well-endowed with primary-educated labor. Similar results are also apparent when decile data are used instead of the usual Gini coefficient. The results are strongly supportive of the factor-proportions theory of trade and suggest that trade liberalization in poor countries where the share of the labor force with very low education levels (likely employed in nontradable activities) is high raises inequality. In the sample, countries with low education levels also have relatively scarce endowments of capital. Quantitatively capital scarcity is the dominating effect so that trade liberalization is accompanied by reduced income inequality in low-income countries. Within-country inequality is also positively correlated with measures of macroeconomic instability. Simulation results suggest that relatively small changes in inequality as measured by aggregate measures of inequality like the Gini coefficient are magnified when estimates are carried out using decile data.
    Keywords: Free Trade,Economic Theory & Research,Inequality,Trade Law,Pro-Poor Growth and Inequality
    Date: 2006–08–01
  6. By: Gardner, Jonathan (Watson Wyatt Worldwide); Oswald, Andrew J. (Department of Economics, University of Warwick)
    Abstract: One of the famous questions in social science is whether money makes people happy. We offer new evidence by using longitudinal data on a random sample of Britons who receive medium-sized lottery wins of between £1000 and £120,000 (that is, up to approximately U.S. $200,000). When compared to two control groups -- one with no wins and the other with small wins -- these individuals go on eventually to exhibit significantly better psychological health. Two years after a lottery win, the average measured improvement in mental wellbeing is 1.4 GHQ points
    Keywords: Psychological health ; Happiness ; GHQ ; Income
    JEL: D1 I3
    Date: 2006
  7. By: Blackburn, Keith; Forgues-Puccio, Gonzalo F.
    Abstract: This paper presents an analysis of bureaucratic corruption, income inequality and economic development. The analysis is based on a dynamic general equilibrium model in which bureaucrats are appointed by the government to implement a redistributive programme of taxes and subsidies designed to benefit the poor. Corruption is reflected in bribery and tax evasion as bureaucrats conspire with the rich in providing false information to the government. In accordance with empirical evidence, the model predicts a positive relationship between corruption and inequality, and a negative relationship between corruption and development.
    Keywords: Corruption, inequality, development.
    JEL: D31 D73 H26 O11
    Date: 2005

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