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Measuring Sub‐National Income Poverty By Using A Small Area Multivariate Approach

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  • Enrico Fabrizi
  • Maria Rosaria Ferrante
  • Silvia Pacei

Abstract

The present paper proposes a statistical strategy for the analysis of regional disparities in income poverty. For the EU countries, information on individual income has been collected until now by the European Community Household Panel survey, which only yields reliable estimates for very large regions within countries. In order to obtain reliable estimates for some of the poverty indicators suggested by the Laeken Council at the sub‐national level, we suggest the adoption of a multivariate small area estimation approach which enables us to reduce estimate variability. We concentrate on Italy, the country with the lowest degree of regional cohesion within the EU. Results show that disparity cannot be reduced to the so‐called “North–South divide,” with the “poor” South separated from the “affluent” North, as both these macro‐regions display large internal differences in terms of both poverty level and income inequality. The strategy we propose could also be adopted in order to measure poverty in other European regions, using information produced by the new EU Survey on Income and Living Conditions, which is replacing the European Community Household Panel.

Suggested Citation

  • Enrico Fabrizi & Maria Rosaria Ferrante & Silvia Pacei, 2008. "Measuring Sub‐National Income Poverty By Using A Small Area Multivariate Approach," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 54(4), pages 597-615, December.
  • Handle: RePEc:bla:revinw:v:54:y:2008:i:4:p:597-615
    DOI: 10.1111/j.1475-4991.2008.00291.x
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    Cited by:

    1. Enrico Fabrizi & Chiara Mussida, 2018. "Assessing poverty persistence in households with dependent children: the role of poverty measurement," DISCE - Quaderni del Dipartimento di Scienze Economiche e Sociali dises1839, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    2. Maria Rosaria Ferrante & Silvia Pacei, 2017. "Small domain estimation of business statistics by using multivariate skew normal models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 1057-1088, October.
    3. Marisa Bottiroli Civardi & Renata Targetti Lenti, 2008. "Multiplier Decomposition, Inequality and Poverty in a SAM Framework," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 10(1), pages 31-57, October.
    4. Enrico Fabrizi & Maria Rosaria Ferrante & Silvia Pacei, 2014. "A Micro-Econometric Analysis of the Antipoverty Effect of Social Cash Transfers in Italy," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(2), pages 323-348, June.
    5. Claudio Ceccarelli & Enrico Fabrizi & Maria Rosaria Ferrante & Silvia Pacei, 2008. "Estimation of Poverty Rates for the Italian Population classified by Household Type and Administrative Region," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 10(1), pages 59-72, October.
    6. Enrico Fabrizi & Chiara Mussida, 2020. "Assessing poverty persistence in households with children," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(4), pages 551-569, December.
    7. Roberto Gismondi & Andrea Carone, 2008. "Statistical Criteria to Manage Non-respondents’ Intensive Follow Up in Surveys Repeated along Time," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 10(1), pages 5-29, October.

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