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A Study of Income Stability in the Czech Republic by Finite Mixtures

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  • Jitka Bartošová
  • Nicholas T. Longford

Abstract

Income, expenditure and similar variables in monetary units tend to have distributions similar to log-normal. Description of such variables after logarithmic transformation by the normal model is often not accurate enough, especially for multivariate data. Deviations of their empirical distributions from the theoretical lognormal distribution often require more sophisticated analysis. Mixtures represent a very flexible way of reconstructing complex distributions with irregular features and are suitable for detailed modelling. Multivariate mixture models are applied to the Czech longitudinal survey of household income in the European Union Statistics on Income and Living Conditions (EU-SILC) in 2005-2008. The analysis identifies distinct patterns of progression of income, with a high percentage of households having steady annual increases over the four years (three transitions). Graphical presentation of the results is emphasised.

Suggested Citation

  • Jitka Bartošová & Nicholas T. Longford, 2014. "A Study of Income Stability in the Czech Republic by Finite Mixtures," Prague Economic Papers, Prague University of Economics and Business, vol. 2014(3), pages 330-348.
    • Handle: RePEc:prg:jnlpep:v:2014:y:2014:i:3:id:487:p:330-348
    DOI: 10.18267/j.pep.487
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    References listed on IDEAS

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    1. Longford, N.T. & Pittau, M.G., 2006. "Stability of household income in European countries in the 1990s," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1364-1383, November.
    2. Pittau, Maria Grazia & Zelli, Roberto & Johnson, Paul, "undated". "Mixture Models and Convergence Clubs," Vassar College Department of Economics Working Paper Series 91, Vassar College Department of Economics.
    3. Fraley C. & Raftery A.E., 2002. "Model-Based Clustering, Discriminant Analysis, and Density Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 611-631, June.
    4. LONGFORD Nicholas Tibor & NICODEMO Catia, 2009. "A sensitivity analysis of poverty definitions," IRISS Working Paper Series 2009-15, IRISS at CEPS/INSTEAD.
    5. Luboš Marek, 2010. "Analýza vývoje mezd v ČR v letech 1995-2008 [The Trend of Income Distributions in Czech Republic in the Years 1995-2008 Analysis]," Politická ekonomie, Prague University of Economics and Business, vol. 2010(2), pages 186-206.
    6. Maria Grazia Pittau & Roberto Zelli & Paul A. Johnson, 2010. "Mixture Models, Convergence Clubs, And Polarization," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(1), pages 102-122, March.
    7. Tomáš Želinský, 2010. "Analýza chudoby na Slovensku založená na koncepte relatívnej deprivácie [Analysis of Poverty in Slovakia Based on the Concept of Relative Deprivation]," Politická ekonomie, Prague University of Economics and Business, vol. 2010(4), pages 542-565.
    8. N. T. Longford & Pierpaolo D'Urso, 2011. "Mixture models with an improper component," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(11), pages 2511-2521, January.
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    Citations

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    Cited by:

    1. Iveta Pauhofová & Tomáš Želinský, 2015. "Regionálne aspekty príjmovej polarizácie v Slovenskej republike [Regional Aspects of Income Polarization in the Slovak Republic]," Politická ekonomie, Prague University of Economics and Business, vol. 2015(6), pages 778-796.
    2. Ivana Malá, 2015. "Vícerozměrný pravděpodobnostní model rozdělení příjmů českých domácností [Multivariate Probability Model For Incomes of the Czech Households]," Politická ekonomie, Prague University of Economics and Business, vol. 2015(7), pages 895-908.

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    More about this item

    Keywords

    income distribution; Equivalised household income; EU-SILC; longitudinal analysis; multivariate mixtures; stability;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household

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