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Personal Income Distribution at the Local Level. An Estimation for Spanish Municipalities Using Tax Microdata

Author

Listed:
  • Miriam Hortas-Rico

    () (Universidad Complutense de Madrid, Spain.)

  • Jorge Onrubia

    () (Universidad Complutense de Madrid)

  • Daniele Pacifico

    (Department of the Treasury – Italian Ministry of Economy and Finance; Centre for North-South Economic Research, University of Cagliari, Italy)

Abstract

Local income data is a key element to analyze residents’ standard of living and wellbeing as well as an important economic indicator, very used in a wide range of studies related to regional convergence, urban economics, fiscal federalism, housing and spatial welfare analysis. Despite its importance, there is a lack of official data on local incomes and, most importantly, on local income distributions. In this paper we use official data on personal income tax returns and a reweighting procedure to derive a representative income sample at the local level. Unlike previous attempts in the literature to get local income estimates, the results obtained allow us to derive not only an average value of income but its local distribution, a valuable and informative tool for distributional and income inequality analysis. We apply this methodology to Spanish micro-data and illustrate its potential use in income inequality analysis by means of computed Gini and Atkinson coefficients for a set of municipalities.

Suggested Citation

  • Miriam Hortas-Rico & Jorge Onrubia & Daniele Pacifico, 2013. "Personal Income Distribution at the Local Level. An Estimation for Spanish Municipalities Using Tax Microdata," International Center for Public Policy Working Paper Series, at AYSPS, GSU paper1314, International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University.
  • Handle: RePEc:ays:ispwps:paper1314
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    File URL: http://icepp.gsu.edu/files/2015/03/ispwp1314.pdf
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    References listed on IDEAS

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    1. 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.
    2. Azizur Rahman & Ann Harding & Robert Tanton & Shuangzhe Liu, 2010. "Methodological Issues in Spatial Microsimulation Modelling for Small Area Estimation," International Journal of Microsimulation, International Microsimulation Association, vol. 3(2), pages 3-22.
    3. Glen Bramley & Gavin Smart, 1996. "Modelling Local Income Distributions in Britain," Regional Studies, Taylor & Francis Journals, vol. 30(3), pages 239-255.
    4. Atkinson, Anthony B., 1970. "On the measurement of inequality," Journal of Economic Theory, Elsevier, vol. 2(3), pages 244-263, September.
    5. Mills, Jeffrey A & Zandvakili, Sourushe, 1997. "Statistical Inference via Bootstrapping for Measures of Inequality," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 133-150, March-Apr.
    6. John Creedy & Ivan Tuckwell, 2004. "Reweighting Household Surveys for Tax Microsimulation Modelling: An Application to the New Zealand Household Economic Survey," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 7(1), pages 71-88, March.
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    Keywords

    local income distribution; sample reweighting; income inequality;

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