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Mapping average equivalized income using robust small area methods

Author

Listed:
  • Enrico Fabrizi
  • Caterina Giusti
  • Nicola Salvati
  • Nikos Tzavidis

Abstract

type="main" xml:lang="es"> A menudo son necesarias medidas de bienestar económico para áreas geográficas pequeñas, ya que los indicadores económicos pueden distribuirse de manera desigual entre subconjuntos de regiones relativamente pequeñas. Se considera una estimación de áreas pequeñas de ingresos equivalentes promedio. A menudo, los datos de ingresos familiares disponibles sólo se logran encontrar para una muestra de hogares por lo general demasiado pequeña como para ofrecer estimaciones confiables para regiones pequeñas. Se considera una técnica de estimación de área pequeña que es robusta frente a valores atípicos, produce resultados consistentes con estimaciones ponderadas del diseño obtenidas para áreas más grandes y capaz de generar mapas sin apenas contracción. La metodología propuesta se aplica a los Sistemas Laborales Locales en la Toscana (Italia).

Suggested Citation

  • Enrico Fabrizi & Caterina Giusti & Nicola Salvati & Nikos Tzavidis, 2014. "Mapping average equivalized income using robust small area methods," Papers in Regional Science, Wiley Blackwell, vol. 93(3), pages 685-701, August.
    • Handle: RePEc:bla:presci:v:93:y:2014:i:3:p:685-701
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    File URL: http://hdl.handle.net/10.1111/pirs.12015
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    References listed on IDEAS

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    1. Antal, Erika & Tillé, Yves, 2011. "A Direct Bootstrap Method for Complex Sampling Designs From a Finite Population," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 534-543.
    2. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    3. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January.
    4. Romina Boarini & Åsa Johansson & Marco Mira d'Ercole, 2006. "Alternative Measures of Well-Being," OECD Economics Department Working Papers 476, OECD Publishing.
    5. Jiming Jiang & P. Lahiri, 2006. "Mixed model prediction and small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(1), pages 1-96, June.
    6. Yogi Vidyattama & Rebecca Cassells & Ann Harding & Justine Mcnamara, 2013. "Rich or Poor in Retirement? A Small Area Analysis of Australian Private Superannuation Savings in 2006 Using Spatial Microsimulation," Regional Studies, Taylor & Francis Journals, vol. 47(5), pages 722-739, May.
    7. Romina Boarini & Åsa Johansson & Marco Mira d'Ercole, 2006. "Alternative Measures of Well-Being," OECD Social, Employment and Migration Working Papers 33, OECD Publishing.
    8. Frey, Jesse & Cressie, Noel, 2003. "Some results on constrained Bayes estimators," Statistics & Probability Letters, Elsevier, vol. 65(4), pages 389-399, December.
    9. Ray Chambers & Nikos Tzavidis, 2006. "M-quantile models for small area estimation," Biometrika, Biometrika Trust, vol. 93(2), pages 255-268, June.
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    Cited by:

    1. Marchetti Stefano & Giusti Caterina & Pratesi Monica & Salvati Nicola & Giannotti Fosca & Pedreschi Dino & Rinzivillo Salvatore & Pappalardo Luca & Gabrielli Lorenzo, 2015. "Small Area Model-Based Estimators Using Big Data Sources," Journal of Official Statistics, Sciendo, vol. 31(2), pages 263-281, June.
    2. Zhang Junni L. & Bryant John, 2020. "Fully Bayesian Benchmarking of Small Area Estimation Models," Journal of Official Statistics, Sciendo, vol. 36(1), pages 197-223, March.
    3. Caterina Giusti & Lucio Masserini & Monica Pratesi, 2017. "Local Comparisons of Small Area Estimates of Poverty: An Application Within the Tuscany Region in Italy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(1), pages 235-254, March.
    4. Paolo Frumento & Nicola Salvati, 2020. "Parametric modelling of M‐quantile regression coefficient functions with application to small area estimation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 229-250, January.
    5. Francesco Schirripa Spagnolo & Antonella D’Agostino & Nicola Salvati, 2018. "Measuring differences in economic standard of living between immigrant communities in Italy," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1643-1667, July.
    6. Yogi Vidyattama & Robert Tanton & Nicholas Biddle, 2015. "Estimating small-area Indigenous cultural participation from synthetic survey data," Environment and Planning A, , vol. 47(5), pages 1211-1228, May.

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