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Poverty and social exclusion: two sides of the same coin or dynamically interrelated processes?

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  • Francesco Devicienti
  • Ambra Poggi

Abstract

There is growing interest in the analysis and measurement of social exclusion, to complement the static and dynamic literature on income poverty. On theoretical grounds, social exclusion and income poverty are seen as different processes, but with closely interrelated dynamics. However, our empirical understanding of the way these two processes dynamically interact at the individual level is still very limited. To shed some light on the issue, we use a dynamic bivariate probit model, controlling for unobserved heterogeneity and Wooldridge (2005)-type initial conditions. Both first and second order Markov dynamics are examined. We estimate the model using the Italian sample of the ECHP, waves 1-8, and find a sizable extent of state dependence in both poverty and social exclusion. Moreover, there are dynamic cross-effects, implying that poverty and social exclusion are mutually reinforcing. Social policies aimed at eradicating poverty and avoiding individuals’ social and economic marginalization should take these interaction effects explicitly into account.

Suggested Citation

  • Francesco Devicienti & Ambra Poggi, 2007. "Poverty and social exclusion: two sides of the same coin or dynamically interrelated processes?," LABORatorio R. Revelli Working Papers Series 62, LABORatorio R. Revelli, Centre for Employment Studies.
  • Handle: RePEc:cca:wplabo:62
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    References listed on IDEAS

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    1. Walter Bossert & Conchita D'Ambrosio & Vito Peragine, 2007. "Deprivation and Social Exclusion," Economica, London School of Economics and Political Science, vol. 74(296), pages 777-803, November.
    2. Satya R. Chakravarty & Conchita D’Ambrosio, 2019. "The Measurement of Social Exclusion," Themes in Economics, in: Satya R. Chakravarty (ed.), Poverty, Social Exclusion and Stochastic Dominance, pages 167-189, Springer.
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    4. Ambra Poggi, 2004. "Social exclusion mobility in Spain, 1994-2000," Working Papers wpdea0409, Department of Applied Economics at Universitat Autonoma of Barcelona.
    5. Poggi, Ambra & Ramos, Xavier, 2007. "Empirical Modeling of Deprivation Contagion among Social Exclusion Dimensions (Using MCMC Methods)," IZA Discussion Papers 2614, Institute of Labor Economics (IZA).
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    7. Martin Biewen, 2004. "Measuring State Dependence in Individual Poverty Status: Are there Feedback Effects to Employment Decisions and Household Composition?," Discussion Papers of DIW Berlin 429, DIW Berlin, German Institute for Economic Research.
    8. Joseph Deutsch & Jacques Silber, 2005. "Measuring Multidimensional Poverty: An Empirical Comparison Of Various Approaches," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 51(1), pages 145-174, March.
    9. Tsakloglou, Panos & Papadopoulos, Fotis, 2001. "Identifying Population Groups at High Risk of Social Exclusion: Evidence from the ECHP," IZA Discussion Papers 392, Institute of Labor Economics (IZA).
    10. Heitmueller, Axel & Michaud, Pierre-Carl, 2006. "Informal Care and Employment in England: Evidence from the British Household Panel Survey," IZA Discussion Papers 2010, Institute of Labor Economics (IZA).
    11. Francesco Devicienti, 2002. "Poverty persistence in Britain: A multivariate analysis using the BHPS, 1991–1997," Journal of Economics, Springer, vol. 77(1), pages 307-340, December.
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    More about this item

    Keywords

    poverty dynamics; social exclusion; state dependence; dynamic bivariate probit model with random effects.;
    All these keywords.

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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