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Empirical Modeling of Deprivation Contagion Among Social Exclusion Dimensions (Using MCMC Methods)

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  • Ambra Poggi
  • Xavier Ramos

Abstract

Economic theory and empirical evidence clearly show that social exclusion dimensions are inter-related. Notwithstanding that, dimensions are usually assumed independent from one another in the economics literature. In this paper we explore the inter-dependency of social exclusion dimensions and study the transmission of deprivation among them. In particular, we propose the use of stochastic epidemic models, which are typically used to study the transmission of infectious diseases, to the analysis of deprivation diffusion among social exclusion dimensions with the aim of acquiring a deeper understanding of the mechanism governing deprivation transmission. We also provide an empirical implementation that investigates the consequences, in terms of future deprivation, for Italian and Spanish women of being jobless, as opposed to doing paid work. We also investigate the consequences of being unemployed versus being inactive. We conclude that working seems to act as a protective mechanism to shocks. In addition, conditional on losing one’s job, women who subsequently search for a job (unemployed) are more likely to experience contagion than women who do not search (inactive).

Suggested Citation

  • Ambra Poggi & Xavier Ramos, 2007. "Empirical Modeling of Deprivation Contagion Among Social Exclusion Dimensions (Using MCMC Methods)," LABORatorio R. Revelli Working Papers Series 59, LABORatorio R. Revelli, Centre for Employment Studies.
  • Handle: RePEc:cca:wplabo:59
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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. Philip D. O'Neill & David J. Balding & Niels G. Becker & Mervi Eerola & Denis Mollison, 2000. "Analyses of infectious disease data from household outbreaks by Markov chain Monte Carlo methods," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(4), pages 517-542.
    3. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Oxford University Press, vol. 64(4), pages 605-654.
    4. Satya R. Chakravarty & Conchita D'Ambrosio, 2006. "The Measurement Of Social Exclusion," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 52(3), pages 377-398, September.
    5. Florence Jaumotte, 2003. "Female Labour Force Participation: Past Trends and Main Determinants in OECD Countries," OECD Economics Department Working Papers 376, OECD Publishing.
    6. Clark, Andrew E & Oswald, Andrew J, 1994. "Unhappiness and Unemployment," Economic Journal, Royal Economic Society, vol. 104(424), pages 648-659, May.
    7. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
    8. Stephen Nickell, 2004. "Poverty And Worklessness In Britain," Economic Journal, Royal Economic Society, vol. 114(494), pages 1-25, March.
    9. Pedro Mira & Namkee Ahn, 2002. "A note on the changing relationship between fertility and female employment rates in developed countries," Journal of Population Economics, Springer;European Society for Population Economics, vol. 15(4), pages 667-682.
    10. Tsakloglou, Panos & Papadopoulos, Fotis, 2001. "Identifying Population Groups at High Risk of Social Exclusion: Evidence from the ECHP," IZA Discussion Papers 392, Institute for the Study of Labor (IZA).
    11. Ambra Poggi, 2007. "Does persistence of social exclusion exist in Spain?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 5(1), pages 53-72, April.
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    Keywords

    deprivation; social exclusion; contagion models; Markov chain Monte Carlo methods; metropolis-Hastings algorithm; stochastic models; propensity score.;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General

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