IDEAS home Printed from https://ideas.repec.org/h/eme/reinzz/s1049-258520190000027002.html
   My bibliography  Save this book chapter

Regional Income Distribution in the European Union: A Parametric Approach

In: What Drives Inequality?

Author

Listed:
  • Tsvetana Spasova

Abstract

This chapter studies trends in income distributions and inequality in the European Union using data from the European Union Statistics on Income and Living Conditions. The author models the income distribution for each country under a Dagum distribution assumption and using maximum likelihood techniques. The author uses parameter estimates to form distributions for regions defined as finite mixtures of the country distributions. Specifically, the author studies the groups of ‘new’ and ‘old’ countries depending on the year they joined the European Union. The author provides formulae and estimates for the regional Gini coefficients and Lorenz curves and their decomposition for all the survey years from 2007 through 2011. The estimates of this study show that the ‘new’ European Union countries have become richer and less unequal over the observed years, while the ‘old’ ones have undergone a slight increase in inequality which is however not significant at conventional levels.

Suggested Citation

  • Tsvetana Spasova, 2019. "Regional Income Distribution in the European Union: A Parametric Approach," Research on Economic Inequality, in: What Drives Inequality?, volume 27, pages 1-18, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:reinzz:s1049-258520190000027002
    DOI: 10.1108/S1049-258520190000027002
    as

    Download full text from publisher

    File URL: https://www.emerald.com/insight/content/doi/10.1108/S1049-258520190000027002/full/html?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://www.emerald.com/insight/content/doi/10.1108/S1049-258520190000027002/full/epub?utm_source=repec&utm_medium=feed&utm_campaign=repec&title=10.1108/S1049-258520190000027002
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://www.emerald.com/insight/content/doi/10.1108/S1049-258520190000027002/full/pdf?utm_source=repec&utm_medium=feed&utm_campaign=repec
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1108/S1049-258520190000027002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nicholas T. Longford & Maria Grazia Pittau & Roberto Zelli & Riccardo Massari, 2012. "Poverty and inequality in European regions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(7), pages 1557-1576, January.
    2. Christian Kleiber, 2008. "A Guide to the Dagum Distributions," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 6, pages 97-117, Springer.
    3. Chotikapanich, Duangkamon & Griffiths, William E. & Rao, D. S. Prasada, 2007. "Estimating and Combining National Income Distributions Using Limited Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 97-109, January.
    4. Lambert, Peter J & Aronson, J Richard, 1993. "Inequality Decomposition Analysis and the Gini Coefficient Revisited," Economic Journal, Royal Economic Society, vol. 103(420), pages 1221-1227, September.
    5. Frank A. Cowell & Russell Davidson & Emmanuel Flachaire, 2015. "Goodness of Fit: An Axiomatic Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 54-67, January.
    6. Carmelo Garcia Perez & Mercedes Prieto Alaiz, 2011. "Using the Dagum model to explain changes in personal income distribution," Applied Economics, Taylor & Francis Journals, vol. 43(28), pages 4377-4386.
    7. Branko Milanovic, 2012. "Global inequality recalculated and updated: the effect of new PPP estimates on global inequality and 2005 estimates," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 10(1), pages 1-18, March.
    8. Stefano Filauro, 2017. "European incomes, national advantages: EU-wide inequality and its decomposition by country and region," EERI Research Paper Series EERI RP 2017/05, Economics and Econometrics Research Institute (EERI), Brussels.
    9. Van Kerm, Philippe & P. Jenkins, Stephen, 2011. "Patterns of persistent poverty: evidence from EU-SILC," ISER Working Paper Series 2011-30, Institute for Social and Economic Research.
    10. Gordon Anderson & Maria Grazia Pittau & Roberto Zelli & Jasmin Thomas, 2018. "Income Inequality, Cohesiveness and Commonality in the Euro Area: A Semi-Parametric Boundary-Free Analysis," Econometrics, MDPI, vol. 6(2), pages 1-20, March.
    11. Xavier Sala-i-Martin, 2006. "The World Distribution of Income: Falling Poverty and … Convergence, Period," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(2), pages 351-397.
    12. Duangkamon Chotikapanich & William E. Griffiths & D. S. Prasada Rao & Vicar Valencia, 2012. "Global Income Distributions and Inequality, 1993 and 2000: Incorporating Country-Level Inequality Modeled with Beta Distributions," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 52-73, February.
    13. Fabrizi, Enrico & Ferrante, Maria Rosaria & Pacei, Silvia & Trivisano, Carlo, 2011. "Hierarchical Bayes multivariate estimation of poverty rates based on increasing thresholds for small domains," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1736-1747, April.
    14. Gholamreza Hajargasht & William E. Griffiths & Joseph Brice & D.S. Prasada Rao & Duangkamon Chotikapanich, 2012. "Inference for Income Distributions Using Grouped Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 563-575, May.
    15. Aristei, David & Perugini, Cristiano, 2010. "Preferences for redistribution and inequality in well-being across Europe," Journal of Policy Modeling, Elsevier, vol. 32(2), pages 176-195, March.
    16. Monique Graf & Desislava Nedyalkova, 2014. "Modeling of Income and Indicators of Poverty and Social Exclusion Using the Generalized Beta Distribution of the Second Kind," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(4), pages 821-842, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Duangkamon Chotikapanich & William E. Griffiths & Gholamreza Hajargasht & Wasana Karunarathne & D. S. Prasada Rao, 2018. "Using the GB2 Income Distribution," Econometrics, MDPI, vol. 6(2), pages 1-24, April.
    2. Duangkamon Chotikapanich & William E. Griffiths & Gholamreza Hajargasht & Wasana Karunarathne & D.S. Prasada Rao, 2018. "Using the GB2 Income Distribution: A Review," Department of Economics - Working Papers Series 2036, The University of Melbourne.
    3. William E. Griffiths and Gholamreza Hajargasht, 2012. "GMM Estimation of Mixtures from Grouped Data:," Department of Economics - Working Papers Series 1148, The University of Melbourne.
    4. Chotikapanich, Duangkamon & Griffiths, William E. & Rao, D.S. Prasada & Karunarathne, Wasana, 2014. "Income Distributions, Inequality, and Poverty in Asia, 1992–2010," ADBI Working Papers 468, Asian Development Bank Institute.
    5. Vladimir Hlasny, 2021. "Parametric representation of the top of income distributions: Options, historical evidence, and model selection," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 1217-1256, September.
    6. Camelia Minoiu & Sanjay Reddy, 2014. "Kernel density estimation on grouped data: the case of poverty assessment," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(2), pages 163-189, June.
    7. Griffiths, William & Hajargasht, Gholamreza, 2015. "On GMM estimation of distributions from grouped data," Economics Letters, Elsevier, vol. 126(C), pages 122-126.
    8. David Warner & D. S. Prasada Rao & William E. Griffiths & Duangkamon Chotikapanich, 2014. "Global Inequality; Levels and Trends, 1993–2005: How Sensitive are These to the Choice of PPPs and Real Income Measures?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(S2), pages 281-304, November.
    9. Duangkamon Chotikapanich & William Griffiths & Wasana Karunarathne & D.S. Prasada Rao, 2013. "Calculating Poverty Measures from the Generalised Beta Income Distribution," The Economic Record, The Economic Society of Australia, vol. 89, pages 48-66, June.
    10. Alexis Akira Toda & Yulong Wang, 2021. "Efficient minimum distance estimation of Pareto exponent from top income shares," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(2), pages 228-243, March.
    11. Pinkovskiy, Maxim L., 2013. "World welfare is rising: Estimation using nonparametric bounds on welfare measures," Journal of Public Economics, Elsevier, vol. 97(C), pages 176-195.
    12. Enrico Fabrizi & Maria Rosaria Ferrante & Carlo Trivisano, 2020. "A functional approach to small area estimation of the relative median poverty gap," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1273-1291, June.
    13. Walter, Paul & Weimer, Katja, 2018. "Estimating poverty and inequality indicators using interval censored income data from the German microcensus," Discussion Papers 2018/10, Free University Berlin, School of Business & Economics.
    14. Crombrugghe, D.P.I. de & Szirmai, A. & Bluhm, R., 2014. "Poor trends: The pace of poverty reduction after the Millennium Development Agenda," MERIT Working Papers 2014-006, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    15. Soondong Hong & Heejoon Han & Chang Sik Kim, 2020. "World distribution of income for 1970–2010: dramatic reduction in world income inequality during the 2000s," Empirical Economics, Springer, vol. 59(2), pages 765-798, August.
    16. Sugasawa, Shonosuke & Kobayashi, Genya & Kawakubo, Yuki, 2020. "Estimation and inference for area-wise spatial income distributions from grouped data," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
    17. Allanson, Paul, 2014. "Income stratification and between-group inequality," Economics Letters, Elsevier, vol. 124(2), pages 227-230.
    18. Miguel Niño‐Zarazúa & Laurence Roope & Finn Tarp, 2017. "Global Inequality: Relatively Lower, Absolutely Higher," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(4), pages 661-684, December.
    19. Hajargasht, Gholamreza & Griffiths, William E., 2013. "Pareto–lognormal distributions: Inequality, poverty, and estimation from grouped income data," Economic Modelling, Elsevier, vol. 33(C), pages 593-604.
    20. Silvia De Nicol`o & Maria Rosaria Ferrante & Silvia Pacei, 2021. "Mind the Income Gap: Bias Correction of Inequality Estimators in Small-Sized Samples," Papers 2107.08950, arXiv.org, revised May 2023.

    More about this item

    Keywords

    Income distribution; Dagum distribution; finite mixtures; inequality; Gini decomposition; European Union; D31; D63; C13;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eme:reinzz:s1049-258520190000027002. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Emerald Support (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.