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Household and Contextual Indicators of Poverty in Tunisia: A Multilevel Analysis

Author

Listed:
  • Mohamed Amara

    (University of Tunis)

  • Hatem Jemmali

    (Laboratory for Research on Quantitative Development Economics (LAREQUAD), Faculty of Economic Sciences and Management of Tunis, University of Tunis El-Manar)

Abstract

Using micro data from the 2010 National Survey on Households’ Budget, Consumption and Standard of Living, this study aims to investigate main factors contributing to poverty distribution, one of the most severe socioeconomic problems in Tunisia. To this end, we use a multilevel Logit model and a multilevel mixed linear model to simultaneously analyze the micro-level (household) and macro-level (governorate) factors that might affect the household poverty status. Household size, household composition, occupation, education levels, the gender of the household head and the number of earner by household variables were assessed at the micro-level. Unemployment rate, poverty rate, industrial and agriculture parts and the migration are included to control the effect of contextual effects. Our findings showed that the likelihood of household being poor is positively and significantly related to household size, more children and lower education level. Extreme poverty is more likely to occur in rural than urban areas. Macro-level analyses indicated that greater neighbourhood unemployment rate was associated with higher odds of poverty, while greater industrial agglomeration and migration balance were associated with reduced odds of poverty.

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  • Mohamed Amara & Hatem Jemmali, 2018. "Household and Contextual Indicators of Poverty in Tunisia: A Multilevel Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 137(1), pages 113-138, May.
  • Handle: RePEc:spr:soinre:v:137:y:2018:i:1:d:10.1007_s11205-017-1602-8
    DOI: 10.1007/s11205-017-1602-8
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    2. Anna Murawska & Bartosz Mickiewicz & Małgorzata Zajdel & Małgorzata Michalcewicz-Kaniowska, 2020. "Multidimensional Analysis of the Relationship between Sustainable Living Conditions and Long and Good Health in the European Union Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 716-735.
    3. Sączewska-Piotrowska Anna, 2018. "Territorial Division and Income Affluence – Analysis Using Two-Level Logit Models," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 22(4), pages 65-78, December.

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