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


  • Francesco Devicienti
  • Ambra Poggi


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 the first- and second-order Markov dynamics are examined. We estimate the model using the Italian sample of the European Community Household Panel (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, 2011. "Poverty and social exclusion: two sides of the same coin or dynamically interrelated processes?," Applied Economics, Taylor & Francis Journals, vol. 43(25), pages 3549-3571.
  • Handle: RePEc:taf:applec:v:43:y:2011:i:25:p:3549-3571
    DOI: 10.1080/00036841003670721

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    References listed on IDEAS

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    8. 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).
    9. 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.
    10. Tindara Addabbo, 2000. "Poverty Dynamics: Analysis of Household Incomes in Italy," LABOUR, CEIS, vol. 14(1), pages 119-144, March.
    11. Stephen P. Jenkins, 2000. "Modelling household income dynamics," Journal of Population Economics, Springer;European Society for Population Economics, vol. 13(4), pages 529-567.
    12. Francesco Devicienti & Valentina Gualtieri, 2004. "Dinamiche e persistenza della povertà in Italia: Un’analisi con microdati panel di fonte ECHP," LABORatorio R. Revelli Working Papers Series 34, LABORatorio R. Revelli, Centre for Employment Studies.
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    Cited by:

    1. Carlos Gradín & Olga Cantó, 2009. "Why are child poverty rates so persistently high in Spain?," Working Papers 123, ECINEQ, Society for the Study of Economic Inequality.
    2. Francesco Devicienti & Valentina Gualtieri & Mariacristina Rossi, 2014. "The Persistence Of Income Poverty And Lifestyle Deprivation: Evidence From Italy," Bulletin of Economic Research, Wiley Blackwell, vol. 66(3), pages 246-278, July.
    3. Rolf Aaberge & Andrea Brandolini, 2014. "Multidimensional poverty and inequality," Discussion Papers 792, Statistics Norway, Research Department.
    4. Ayllón, Sara & Fusco, Alessio, 2017. "Are income poverty and perceptions of financial difficulties dynamically interrelated?," Journal of Economic Psychology, Elsevier, vol. 61(C), pages 103-114.
    5. Moniek Coumans & Hans Schmeets, 2015. "The Socially Excluded in the Netherlands: The Development of an Overall Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(3), pages 779-805, July.
    6. Ayllón, Sara, 2009. "Modelling state dependence and feedback effects between poverty, employment and parental home emancipation among European youth," Working Papers 10, VATT Institute for Economic Research.
    7. Plum Alexander, 2016. "Can Low-Wage Employment Help People Escape from the No-Pay – Low-Income Trap?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 16(4), pages 1-28, October.
    8. repec:hal:journl:hal-00393322 is not listed on IDEAS
    9. Richiardi Matteo & Poggi Ambra, 2012. "Imputing Individual Effects in Dynamic Microsimulation Models. An application of the Rank Method," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201213, University of Turin.
    10. Sara Ayllón & András Gábos, 2017. "The Interrelationships between the Europe 2020 Poverty and Social Exclusion Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 130(3), pages 1025-1049, February.
    11. Nathalie Chusseau & Joel Hellier, 2014. "Globalization and social segmentation," Working Papers 339, ECINEQ, Society for the Study of Economic Inequality.
    12. Isabel Busom & Beatriz Corchuelo & Ester Martínez-Ros, 2017. "Participation inertia in R&D tax incentive and subsidy programs," Small Business Economics, Springer, vol. 48(1), pages 153-177, January.
    13. Erika Raquel Badillo & Rosina Moreno, 2016. "Are Collaborative Agreements in Innovation Activities Persistent at the Firm Level? Empirical Evidence for the Spanish Case," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 49(1), pages 71-101, August.
    14. Giuseppe Arcangelis & Majlinda Joxhe, 2015. "How do migrants save? Evidence from the British Household Panel Survey on temporary and permanent migrants versus natives," IZA Journal of Migration, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-23, December.
    15. Isabel Busom & Beatriz Corchuelo & Ester Martínez-Ros, 2015. "Dynamics of firm participation in R&D tax credit and subsidy programs," Working Papers wpdea1503, Department of Applied Economics at Universitat Autonoma of Barcelona.
    16. Matteo Richiardi & Ambra Poggi, 2014. "Imputing Individual Effects in Dynamic Microsimulation Models. An application to household formation and labour market participation in Italy," International Journal of Microsimulation, International Microsimulation Association, vol. 7(2), pages 3-39.
    17. Chichaibelu, Bezawit & Waibel, Hermann, 2015. "The Interrelated Dynamics of Multiple Borrowing and Over-indebtedness among Rural Households in Thailand and Vietnam," 2015 Conference, August 9-14, 2015, Milan, Italy 211463, International Association of Agricultural Economists.
    18. Giles, John & Murtazashvili, Irina, 2010. "A control function approach to estimating dynamic probit models with endogenous regressors, with an application to the study of poverty persistence in China," Policy Research Working Paper Series 5400, The World Bank.
    19. Alfonso Miranda, 2010. "Bivariate dynamic probit models for panel data," Mexican Stata Users' Group Meetings 2010 07, Stata Users Group.
    20. Giles John & Murtazashvili Irina, 2013. "A Control Function Approach to Estimating Dynamic Probit Models with Endogenous Regressors," Journal of Econometric Methods, De Gruyter, vol. 2(1), pages 69-87, July.
    21. J. Vrooman & Stella Hoff, 2013. "The Disadvantaged Among the Dutch: A Survey Approach to the Multidimensional Measurement of Social Exclusion," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 113(3), pages 1261-1287, September.
    22. J. Cok Vrooman & Stella J. M. Hoff & Maurice Guiaux, 2015. "Descendants of Hardship: Prevalence, Drivers and Scarring Effects of Social Exclusion in Childhood," Social Inclusion, Cogitatio Press, vol. 3(4), pages 76-97.

    More about this item

    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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