IDEAS home Printed from https://ideas.repec.org/a/csb/stintr/v14y2013i3p359-378.html
   My bibliography  Save this article

Estimation of Income Inequality and the Poverty Rate in Poland, by Region and Family Type

Author

Listed:
  • Alina Jędrzejczak
  • Jan Kubacki

Abstract

High income inequality can be a source of serious socio-economic problems, such as increasing poverty, social stratification and polarization. Periods of pronounced economic growth or recession may impact different groups of earners differently. Growth may not be shared equally and economic crises may further widen gaps between the wealthiest and poorest sectors. Poverty affects all ages but children are disproportionately affected by it. The reliable inequality and poverty analysis of both total population of households and subpopulations by various family types can be a helpful piece of information for economists and social policy makers. The main objective of the paper was to present some income inequality and poverty estimates with the application to the Polish data coming from the Household Budget Survey. Besides direct estimation methods, the model based approach was taken into regard. Standard errors of estimates were also considered in the paper.

Suggested Citation

  • Alina Jędrzejczak & Jan Kubacki, 2013. "Estimation of Income Inequality and the Poverty Rate in Poland, by Region and Family Type," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 14(3), pages 359-378, September.
  • Handle: RePEc:csb:stintr:v:14:y:2013:i:3:p:359-378
    as

    Download full text from publisher

    File URL: http://index.stat.gov.pl/repec/files/csb/stintr/csb_stintr_v14_2013_i3_n2.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sen, Amartya K, 1976. "Poverty: An Ordinal Approach to Measurement," Econometrica, Econometric Society, vol. 44(2), pages 219-231, March.
    2. Matti Langel & Yves Tillé, 2013. "Variance estimation of the Gini index: revisiting a result several times published," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(2), pages 521-540, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alina Jędrzejczak, 2014. "Income Inequality and Income Stratification in Poland," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 15(2), pages 269-282, March.
    2. Isabel Molina & Paul Corral & Minh Nguyen, 2022. "Estimation of poverty and inequality in small areas: review and discussion," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(4), pages 1143-1166, December.
    3. Francesca Battisti & Francesco Porro, 2023. "A multi-decomposition of Zenga-84 inequality index: an application to the disparity in CO $$_2$$ 2 emissions in European countries," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 957-981, September.
    4. Alina Jędrzejczak & Dorota Pekasiewicz, 2020. "Changes in Income Distribution for Different Family Types in Poland," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 26(2), pages 135-146, May.
    5. Francesco Porro & Michele Zenga, 2020. "Decomposition by subpopulations of the Zenga-84 inequality curve and the related index $$\zeta $$ζ: an application to 2014 Bank of Italy survey," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 187-207, March.

    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. Chakravarty, Satya R. & Deutsch, Joseph & Silber, Jacques, 2008. "On the Watts Multidimensional Poverty Index and its Decomposition," World Development, Elsevier, vol. 36(6), pages 1067-1077, June.
    2. Masood Sarwar Awan & Muhammad Amir Aslam, 2011. "Multidimensional Poverty in Pakistan: Case of Punjab Province," Journal of Economics and Behavioral Studies, AMH International, vol. 3(2), pages 133-144.
    3. Oihana Aristondo & Casilda Lasso De La Vega & Ana Urrutia, 2010. "A New Multiplicative Decomposition For The Foster–Greer–Thorbecke Poverty Indices," Bulletin of Economic Research, Wiley Blackwell, vol. 62(3), pages 259-267, July.
    4. Espinoza-Delgado, José & Silber, Jacques, 2018. "Multi-dimensional poverty among adults in Central America and gender differences in the three I’s of poverty: Applying inequality sensitive poverty measures with ordinal variables," MPRA Paper 88750, University Library of Munich, Germany.
    5. Borooah, Vani, 2007. "Measuring economic inequality: deprivation, economising and possessing," MPRA Paper 19422, University Library of Munich, Germany.
    6. N'dri, Lasme Mathieu & Kakinaka, Makoto, 2020. "Financial inclusion, mobile money, and individual welfare: The case of Burkina Faso," Telecommunications Policy, Elsevier, vol. 44(3).
    7. Lane Kenworthy, 2004. "Welfare States, Real Income and Poverty," LIS Working papers 370, LIS Cross-National Data Center in Luxembourg.
    8. Heindl, Peter & Schuessler, Rudolf, 2015. "Dynamic properties of energy affordability measures," Energy Policy, Elsevier, vol. 86(C), pages 123-132.
    9. Hendrik Thiel & Stephan L. Thomsen, 2015. "Individual Poverty Paths and the Stability of Control-Perception," SOEPpapers on Multidisciplinary Panel Data Research 794, DIW Berlin, The German Socio-Economic Panel (SOEP).
    10. Belhadj, Besma & Limam, Mohamed, 2012. "Unidimensional and multidimensional fuzzy poverty measures: New approach," Economic Modelling, Elsevier, vol. 29(4), pages 995-1002.
    11. repec:pru:wpaper:8 is not listed on IDEAS
    12. Francisco J. Ciocchini & Gabriel Molteni, 2008. "Medidas alternativas de la pobreza en el Gran Buenos Aires, 1995-2006," Ensayos de Política Económica, Departamento de Investigación Francisco Valsecchi, Facultad de Ciencias Económicas, Pontificia Universidad Católica Argentina., vol. 1(2), pages 46-82, Octubre.
    13. Duclos, Jean-Yves & Araar, Abdelkrim & Giles, John, 2010. "Chronic and transient poverty: Measurement and estimation, with evidence from China," Journal of Development Economics, Elsevier, vol. 91(2), pages 266-277, March.
    14. Mathias KUEPIE & Eric Patrick FEUBI PAMEN, 2017. "An Application of the Alkire-Foster’s Multidimensional Poverty Index to Data from Madagascar: Taking Into Account the Dimensions of Employment and Gender Inequality," Working Paper 6ca04615-044d-41a0-8737-9, Agence française de développement.
    15. Russell Davidson & Jean-Yves Duclos, 2000. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," Econometrica, Econometric Society, vol. 68(6), pages 1435-1464, November.
    16. Temple, Jonathan & Ying, Huikang, 2014. "Life During Structural Transformation," CEPR Discussion Papers 10297, C.E.P.R. Discussion Papers.
    17. Ziqing Dong & Yves Tillé & Giovanni M. Giorgi & Alessio Guandalini, 2021. "Linearization and variance estimation of the Bonferroni inequality index," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 1008-1029, July.
    18. Sanghamitra Bandyopadhyay, 2016. "The Vulnerable Are Not (Necessarily) the Poor," Research on Economic Inequality, in: Inequality after the 20th Century: Papers from the Sixth ECINEQ Meeting, volume 24, pages 29-57, Emerald Group Publishing Limited.
    19. Muhammad Omer & Sarah Jafri, 2008. "Pro-Poor Growth in Pakistan," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 9(1), pages 51-68, June.
    20. Gaurav Datt & Martin Ravallion, 1998. "Farm productivity and rural poverty in India," Journal of Development Studies, Taylor & Francis Journals, vol. 34(4), pages 62-85.
    21. Xiaofeng Lv & Gupeng Zhang & Guangyu Ren, 2017. "Gini index estimation for lifetime data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 275-304, April.

    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:csb:stintr:v:14:y:2013:i:3:p:359-378. 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: Beata Witek (email available below). General contact details of provider: https://edirc.repec.org/data/gusgvpl.html .

    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.