Poverty and social exclusion: two sides of the same coin or dynamically interrelated processes?
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 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.Download Info
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Bibliographic Info
Article provided by Taylor and Francis Journals in its journal Applied Economics.
Volume (Year): 43 (2011)
Issue (Month): 25 ()
Pages: 3549-3571
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Related research
Keywords:Other versions of this item:
- 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.
- I32 - Health, Education, and Welfare - - Welfare and Poverty - - - Measurement and Analysis of Poverty
- C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- 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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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Giles, John T. & Murtazashvili, Irina, 2012.
"A Control Function Approach to Estimating Dynamic Probit Models with Endogenous Regressors, with an Application to the Study of Poverty Persistence in China,"
IZA Discussion Papers
6887, Institute for the Study of Labor (IZA).
- 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.
- Alfonso Miranda, 2010. "Bivariate dynamic probit models for panel data," Mexican Stata Users' Group Meetings 2010 07, Stata Users Group.
- Sara Ayllón, 2009.
"Modelling State Dependence and Feedback Effects between Poverty, Employment and Parental Home Emancipation among European Youth,"
SOEPpapers on Multidisciplinary Panel Data Research
235, DIW Berlin, The German Socio-Economic Panel (SOEP).
- Sara Ayllón Gatnau, 2009. "Modelling state dependence and feedback effects between poverty, employment and parental home emancipation among European youth," Economics Working Papers 1180, Department of Economics and Business, Universitat Pompeu Fabra.
- Sara Ayllón, 2009. "Modelling state dependence and feedback effects between poverty, employment and parental home emancipation among European youth," Working Papers 10, Government Institute for Economic Research Finland (VATT).
- Ambra Poggi & Matteo G. Richiardi, 2012.
"Imputing Individual Effects in Dynamic Microsimulation Models.An application of the Rank Method,"
LABORatorio R. Revelli Working Papers Series
124, LABORatorio R. Revelli, Centre for Employment Studies.
- Matteo Richiardi & Ambra Poggi, 2012. "Imputing Individual Effects in Dynamic Microsimulation Models. An application of the Rank Method," Carlo Alberto Notebooks 267, Collegio Carlo Alberto.
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- 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.
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