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Model-Assisted Estimation of Small Area Poverty Measures: An Application within the Valencia Region in Spain

Author

Listed:
  • Domingo Morales

    (Miguel Hernández University of Elche)

  • María del Mar Rueda

    (University of Granada)

  • Dolores Esteban

    (Miguel Hernández University of Elche)

Abstract

This paper introduces small area estimators of poverty indexes, with special attention to the poverty rate (or Head Count Index), and studies the sampling design consistency and the asymptotic normality of these estimators. The estimators are assisted by nested error regression models and are model-assisted counterparts of model-based empirical best predictors. Simulation studies show that these estimators present a good balance between sampling bias and mean squared error. Data from the 2013 Spanish living conditions survey with respect to the region of Valencia are used to determine the performance of this new method for estimating the poverty rate.

Suggested Citation

  • Domingo Morales & María del Mar Rueda & Dolores Esteban, 2018. "Model-Assisted Estimation of Small Area Poverty Measures: An Application within the Valencia Region in Spain," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 138(3), pages 873-900, August.
    • Handle: RePEc:spr:soinre:v:138:y:2018:i:3:d:10.1007_s11205-017-1678-1
    DOI: 10.1007/s11205-017-1678-1
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    References listed on IDEAS

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    1. J. Muñoz & E. Álvarez-Verdejo & R. García-Fernández & L. Barroso, 2015. "Efficient Estimation of the Headcount Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 123(3), pages 713-732, September.
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    12. Miguel Boubeta & María José Lombardía & Domingo Morales, 2016. "Empirical best prediction under area-level Poisson mixed models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 548-569, September.
    13. Boubeta, Miguel & Lombardía, María José & Morales, Domingo, 2017. "Poisson mixed models for studying the poverty in small areas," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 32-47.
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    15. Esther López-Vizcaíno & María José Lombardía & Domingo Morales, 2015. "Small area estimation of labour force indicators under a multinomial model with correlated time and area effects," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(3), pages 535-565, June.
    16. Esteban, M.D. & Morales, D. & Pérez, A. & Santamaría, L., 2012. "Small area estimation of poverty proportions under area-level time models," Computational Statistics & Data Analysis, Elsevier, vol. 56(10), pages 2840-2855.
    17. Eric Crettaz & Christian Suter, 2013. "The Impact of Adaptive Preferences on Subjective Indicators: An Analysis of Poverty Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(1), pages 139-152, October.
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    Cited by:

    1. Esteban Fernandez-Vazquez & Alberto Diaz Dapena & Fernando Rubiera-Morollon & Ana Viñuela, 2020. "Spatial Disaggregation of Social Indicators: An Info-Metrics Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(2), pages 809-821, November.

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