Abstract
This chapter investigates the characteristics of chronic poverty among youth in Southern European countries. These countries have the highest levels of poverty in Europe and welfare systems unable to smooth social inequalities effectively. The main aim of this chapter is to investigate on how long-lasting poor among the Mediterranean youth differs in socio-demographic and economic characteristics. The intensity of poverty over time is measured by a very recent longitudinal poverty index based on the rationale of cumulative hardship. We tested the effects of many covariates on the incidence and intensity of chronic poverty, controlling for main socio-demographic and economic characteristics, using a ZINB model. The peculiar mix between the lack of effective state institutions and a strong presence of families explains why many factors, which usually are significantly related to poverty, do not have an important role here. A strong inertial effect is due to the intensity of poverty at the start of the time-window. Italian youth has the worst performance.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
A drawback of these two categories of models is that they usually do not take into account that there is a strong correlation among multiple spells of poverty or non-poverty for the same individual. In particular, in transition models, spells in the two alternating states (poverty and non-poverty) for the same individual are also assumed to be uncorrelated […] However, when individuals differ in unobserved terms like ability, effort, tastes, and these unobservables remain constant over the individual’s lifetime, the assumption of uncorrelated spells might be inappropriate [8].
- 2.
- 3.
Note that here, we use rounded values of the PPI. In particular, we multiplied the PPI by 1,000 and then rounded to the nearest integer. This transformation allows us to keep 30 different values also in the transformed values. Indeed in presence of a longer panel a more appropriate model would be a mixture model allowing zero-inflation and a suitable model for asymmetric data (looking at the distribution observed a reasonable model seems to be the Beta distribution with parameters lower than 1).
- 4.
In our case part of the inflation of zeroes is due to the fact that the PPI is zero also for individuals with a single spell of poverty. Indeed people who are poor only once in the 6 years of observation are 11.7% of our sample. The likelihood ratio test and the Vuong test confirm the appropriateness of the chosen functional form compared to a standard negative binomial distribution.
- 5.
Please note that the classification of the activity status is made through three categories, mutually exclusive, derived from the shrinking of the main activity declared by respondents. So a young individual is a “worker” if she is employed for at least 15 h a week, or a “student”/“unemployed or out of the labour force” even if doing a small/odd paid job but for less than 15 h per week.
References
Aassve, A., Iacovou, M., Mencarini, L.: Youth poverty and transition to adulthood in Europe. Demogr. Res. 5(2), 21–50 (2006)
Bane, M.J., Ellwood, D.T.: Slipping into and out of poverty: the dynamics of spells. J. Hum. Resour. 21(1), 1–23 (1986)
Billari, F.C.: Becoming an adult in Europe: a macro(/micro)-demographic perspective. Demogr. Res. Spec. Collection 3(2), 15–43 (2004)
Billari, F.C., Rosina, A.: Italian “latest-late” transition to adulthood: an exploration of its consequences. Genus 69, 71–88 (2004)
Bossert, W., Chakravarty, S.R., D’Ambrosio, C.: Poverty and time. J. Econ. Ineq. 10(2), 145–162 (2012)
Calvo, C., Dercon, S.: Chronic poverty and all that the measurement of poverty over time. In: Addison, T., Hulme, D., Kanbur, R. (eds.) Poverty Dynamics. Interdisciplinary Perspectives, pp. 29–58. Oxford University Press, Oxford (2009)
Cappellari, L., Jenkins, S.P.: Modelling low income transitions. J. Appl. Econ. 19, 593–610 (2004)
Devicienti, F.: Estimating poverty persistence in Britain. Empir. Econ. 40(3), 657–686 (2011)
Dutta, I., Roope, L., Zank, H.: On intertemporal poverty measures: the role of affluence and want. Soc. Choice Welf. (2012). doi:10.1007/s00355-012-0709-8
Eurostat: Material deprivation in the EU. Stat. Focus 21, 1–11 (2005)
Ferreira, L.V.: Persistent poverty: Portugal and the southern European welfare regime. Eur Soc 10(1), 49–71 (2008)
Ferrera, M.: The “southern model” of welfare in social Europe. J. Eur. Soc. Policy 6(1), 17–37 (1996)
Foster, J.E.: A class of chronic poverty measures. In: Addison, T., Hulme, D., Kanbur, R. (eds.) Poverty Dynamics. Interdisciplinary Perspectives, pp. 59–76. Oxford University Press, Oxford (2009)
Hills, M.S., Jenkins, S.P.: Poverty among children: chronic or transitory? In: Bradbury, B., Jenkins, S.P., Micklewright, J. (eds.) The Dynamics of Child Poverty in Industrialised Countries, pp. 174–195. Cambridge University Press, Cambridge (2001)
Hoy, M., Zheng, B.: Measuring lifetime poverty. J. Econ. Theory 146(6), 2544–2562 (2011)
Iacovou, M., Aassve, A.: Youth Poverty in Europe. Joseph Rowntree Foundation, York (2007) (Available at http://www.jrf.org.uk/sites/files/jrf/2121-poverty-youth-europe.pdf)
Jalan, J., Ravaillon, M.: Transient poverty in postreform rural China. J. Comp. Econ. 26(2), 338–357 (1998)
Jenkins, S.P.: Modelling household income dynamics. J. Popul. Econ. 13(4), 529–567 (2000)
Long, J.S.: Regression Models for Categorical and Limited Dependent Variables. Sage, Thousand Oaks (1997)
Matsaganis, M., Ferrera, M., Capucha, L., Moreno, L.: Mending nets in the south: anti-poverty policies in Greece, Italy, Portugal and Spain. Soc. Policy Adm. 37(6), 639–655 (2003)
Mendola, D., Busetta, A.: The importance of consecutive spells of poverty: a path-dependent index of longitudinal poverty. Rev. Income Wealth 58(2), 355–374 (2012)
Mendola, D., Busetta, A., Aassve, A.: What keeps young adults in permanent poverty? A comparative analysis using ECHP. Soc. Sci. Res. 38(4), 840–857 (2009)
Mendola, D., Busetta, A., Milito, A.M.: Combining the intensity and sequencing of the poverty experience: a class of longitudinal poverty indices. J. R. Stat. Soc. A 174, 953–73 (2011)
Quintini, G., Martin, S.: Starting Well or Losing their Way? The position of youth in the labour market in OECD countries. OECD Social, Employment and Migration Working Papers, No. 39 (2006). doi:10.1787/351848125721
Reyneri, E.: Sociologia del mercato del lavoro. Il Mulino, Bologna (2005)
Stevens, A.H.: Climbing out of poverty, falling back in: measuring the persistence of poverty over multiple spells. J. Hum. Resour. 34(3), 557–588 (1999)
Zheng, B.: Measuring chronic poverty: a gravitational approach. Seminar paper presented at University of Colorado, Denver (2012)
Acknowledgements
Although this chapter is the result of the joint effort of both authors, who share the full responsibility for the content, Sects. 31.1, 31.2, and 31.3 are attributable to D. Mendola, while Sects. 31.4 and 31.5 to A. Busetta. The authors gratefully acknowledge the financial support provided by University of Palermo [grant no. 1267929730 - CORI] under the responsibility of professor A.M. Milito, and IRISS at CEPS/INSTEAD for providing the ECHP data under the FP6 (Trans-national Access contract RITA 026040).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Mendola, D., Busetta, A. (2013). Chronic Poverty in European Mediterranean Countries. In: Torelli, N., Pesarin, F., Bar-Hen, A. (eds) Advances in Theoretical and Applied Statistics. Studies in Theoretical and Applied Statistics(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35588-2_31
Download citation
DOI: https://doi.org/10.1007/978-3-642-35588-2_31
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35587-5
Online ISBN: 978-3-642-35588-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)