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Multivariate Small Area Estimation of Multidimensional Latent Economic Well‐being Indicators

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  • Angelo Moretti
  • Natalie Shlomo
  • Joseph W. Sakshaug

Abstract

Factor analysis models are used in data dimensionality reduction problems where the variability among observed variables can be described through a smaller number of unobserved latent variables. This approach is often used to estimate the multidimensionality of well‐being. We employ factor analysis models and use multivariate empirical best linear unbiased predictor (EBLUP) under a unit‐level small area estimation approach to predict a vector of means of factor scores representing well‐being for small areas. We compare this approach with the standard approach whereby we use small area estimation (univariate and multivariate) to estimate a dashboard of EBLUPs of the means of the original variables and then averaged. Our simulation study shows that the use of factor scores provides estimates with lower variability than weighted and simple averages of standardised multivariate EBLUPs and univariate EBLUPs. Moreover, we find that when the correlation in the observed data is taken into account before small area estimates are computed, multivariate modelling does not provide large improvements in the precision of the estimates over the univariate modelling. We close with an application using the European Union Statistics on Income and Living Conditions data.

Suggested Citation

  • Angelo Moretti & Natalie Shlomo & Joseph W. Sakshaug, 2020. "Multivariate Small Area Estimation of Multidimensional Latent Economic Well‐being Indicators," International Statistical Review, International Statistical Institute, vol. 88(1), pages 1-28, April.
    • Handle: RePEc:bla:istatr:v:88:y:2020:i:1:p:1-28
    DOI: 10.1111/insr.12333
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    1. Dan Andrews & Aida Caldera Sánchez & Åsa Johansson, 2011. "Housing Markets and Structural Policies in OECD Countries," OECD Economics Department Working Papers 836, OECD Publishing.
    2. Tony Atkinson & Bea Cantillon & Eric Marlier & Brian Nolan, 2002. "Indicators for Social Inclusion," Politica economica, Società editrice il Mulino, issue 1, pages 7-28.
    3. Marchetti, Stefano & Tzavidis, Nikos & Pratesi, Monica, 2012. "Non-parametric bootstrap mean squared error estimation for M-quantile estimators of small area averages, quantiles and poverty indicators," Computational Statistics & Data Analysis, Elsevier, vol. 56(10), pages 2889-2902.
    4. Martin Ravallion, 2011. "On multidimensional indices of poverty," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(2), pages 235-248, June.
    5. Gaston Yalonetzky, 2014. "Conditions for the most robust multidimensional poverty comparisons using counting measures and ordinal variables," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 43(4), pages 773-807, December.
    6. Atkinson, Tony & Cantillon, Bea & Marlier, Eric & Nolan, Brian, 2002. "Social Indicators: The EU and Social Inclusion," OUP Catalogue, Oxford University Press, number 9780199253494.
    7. González-Manteiga, W. & Lombardi­a, M.J. & Molina, I. & Morales, D. & Santamari­a, L., 2008. "Analytic and bootstrap approximations of prediction errors under a multivariate Fay-Herriot model," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5242-5252, August.
    8. Innocent Ngaruye & Joseph Nzabanita & Dietrich von Rosen & Martin Singull, 2017. "Small area estimation under a multivariate linear model for repeated measures data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(21), pages 10835-10850, November.
    9. Steven Boker & Michael Neale & Hermine Maes & Michael Wilde & Michael Spiegel & Timothy Brick & Jeffrey Spies & Ryne Estabrook & Sarah Kenny & Timothy Bates & Paras Mehta & John Fox, 2011. "OpenMx: An Open Source Extended Structural Equation Modeling Framework," Psychometrika, Springer;The Psychometric Society, vol. 76(2), pages 306-317, April.
    10. Fusco, Alessio, 2015. "The relationship between income and housing deprivation: A longitudinal analysis," Economic Modelling, Elsevier, vol. 49(C), pages 137-143.
    11. Molina, Isabel, 2009. "Uncertainty under a multivariate nested-error regression model with logarithmic transformation," Journal of Multivariate Analysis, Elsevier, vol. 100(5), pages 963-980, May.
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