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

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  • Poggi, Ambra

    ()
    (LABORatorio R. Revelli)

  • Ramos, Xavi

    ()
    (Universitat Autònoma de Barcelona)

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).

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 2614.

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Length: 17 pages
Date of creation: Feb 2007
Date of revision:
Publication status: published in: Jacques Silber (ed.), The Measurement of Individual Well-Being and Group Inequalities: Essays in Memory of Z.M. Berrebi, Routledge, 2010
Handle: RePEc:iza:izadps:dp2614

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

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References

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  1. Clark, Andrew E & Oswald, Andrew J, 1994. "Unhappiness and Unemployment," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 104(424), pages 648-59, May.
  2. 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, Springer, vol. 15(4), pages 667-682.
  3. Namkee Ahn & Pedro Mira, . "A note on the changing relationship between fertility and female employment rates in developed countries," Working Papers 99-09, FEDEA.
  4. Florence Jaumotte, 2003. "Female Labour Force Participation: Past Trends and Main Determinants in OECD Countries," OECD Economics Department Working Papers 376, OECD Publishing.
  5. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
  6. Ambra Poggi, 2003. "Does persistence of social exclusion exist in Spain?," Working Papers wpdea0308, Department of Applied Economics at Universitat Autonoma of Barcelona.
  7. Heckman, James J & Ichimura, Hidehiko & Todd, Petra E, 1997. "Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 64(4), pages 605-54, October.
  8. BOSSERT, Walter & D'AMBROSIO, Conchita & PERAGINE, Vito, 2004. "Deprivation and Social Exclusion," Cahiers de recherche, Universite de Montreal, Departement de sciences economiques 2004-01, Universite de Montreal, Departement de sciences economiques.
  9. 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, 09.
  10. Stephen Nickell, 2004. "Poverty And Worklessness In Britain," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 114(494), pages C1-C25, 03.
  11. 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.
  12. 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).
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