IDEAS home Printed from https://ideas.repec.org/a/spt/stecon/v10y2021i1f10_1_3.html
   My bibliography  Save this article

Empirical Analyses of Income: Finland (2009) and Australia (1967-1968)

Author

Listed:
  • Johan Fellman

Abstract

Analyses of income data are often based on assumptions concerning theoretical distributions. In this study, we apply statistical analyses, but ignore specific distribution models. The main income data sets considered in this study are taxable income in Finland (2009) and household income in Australia (1967-1968). Our intention is to compare statistical analyses performed without assumptions of the theoretical models with earlier results based on specific models. We have presented the central objects, probability density function, cumulative distribution function, the Lorenz curve, the derivative of the Lorenz curve, the Gini index and the Pietra index. The trapezium rule, Simpson´s rule, the regression model and the difference quotients yield comparable results for the Finnish data, but for the Australian data the differences are marked. For the Australian data, the discrepancies are caused by limited data. JEL classification numbers: D31, D63, E64.

Suggested Citation

  • Johan Fellman, 2021. "Empirical Analyses of Income: Finland (2009) and Australia (1967-1968)," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 10(1), pages 1-3.
    • Handle: RePEc:spt:stecon:v:10:y:2021:i:1:f:10_1_3
    as

    Download full text from publisher

    File URL: http://www.scienpress.com/Upload/JSEM%2fVol%2010_1_3.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. McDonald, James B. & Ransom, Michael R., 1981. "An analysis of the bounds for the Gini coefficient," Journal of Econometrics, Elsevier, vol. 17(2), pages 177-188, November.
    2. Rohde, Nicholas, 2009. "An alternative functional form for estimating the Lorenz curve," Economics Letters, Elsevier, vol. 105(1), pages 61-63, October.
    3. Kwang Soo Cheong, 2002. "An empirical comparison of alternative functional forms for the Lorenz curve," Applied Economics Letters, Taylor & Francis Journals, vol. 9(3), pages 171-176.
    4. Kakwani, N C & Podder, N, 1973. "On the Estimation of Lorenz Curves from Grouped Observations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 278-292, June.
    5. Needleman, Lionel, 1978. "On the Approximation of the Gini Coefficient of Concentration," The Manchester School of Economic & Social Studies, University of Manchester, vol. 46(2), pages 105-122, June.
    6. Gupta, Manash Ranjan, 1984. "Functional Form for Estimating the Lorenz Curve," Econometrica, Econometric Society, vol. 52(5), pages 1313-1314, September.
    7. Ogwang, Tomson & Rao, U. L. Gouranga, 2000. "Hybrid models of the Lorenz curve," Economics Letters, Elsevier, vol. 69(1), pages 39-44, October.
    8. Kakwani, Nanak C & Podder, N, 1976. "Efficient Estimation of the Lorenz Curve and Associated Inequality Measures from Grouped Observations," Econometrica, Econometric Society, vol. 44(1), pages 137-148, January.
    9. Chotikapanich, Duangkamon, 1993. "A comparison of alternative functional forms for the Lorenz curve," Economics Letters, Elsevier, vol. 41(2), pages 129-138.
    10. Gastwirth, Joseph L, 1972. "The Estimation of the Lorenz Curve and Gini Index," The Review of Economics and Statistics, MIT Press, vol. 54(3), pages 306-316, August.
    11. Johan Fellman, 2012. "Estimation of Gini coefficients using Lorenz curves," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 1(2), pages 1-3.
    12. Kakwani, Nanak, 1980. "On a Class of Poverty Measures," Econometrica, Econometric Society, vol. 48(2), pages 437-446, March.
    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. Louis Mesnard, 2022. "About some difficulties with the functional forms of Lorenz curves," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(4), pages 939-950, December.
    2. WANG, Zuxiang & SMYTH, Russell & NG, Yew-Kwang, 2009. "A new ordered family of Lorenz curves with an application to measuring income inequality and poverty in rural China," China Economic Review, Elsevier, vol. 20(2), pages 218-235, June.
    3. Thitithep Sitthiyot & Kanyarat Holasut, 2021. "A simple method for estimating the Lorenz curve," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-9, December.
    4. Wang, Yuanjun & You, Shibing, 2016. "An alternative method for modeling the size distribution of top wealth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 443-453.
    5. Miguel Sordo & Jorge Navarro & José Sarabia, 2014. "Distorted Lorenz curves: models and comparisons," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 42(4), pages 761-780, April.
    6. Wang, ZuXiang & Smyth, Russell, 2015. "A hybrid method for creating Lorenz curves," Economics Letters, Elsevier, vol. 133(C), pages 59-63.
    7. ZuXiang Wang & Yew-Kwang Ng & Russell Smyth, 2007. "Revisiting The Ordered Family Of Lorenz Curves," Monash Economics Working Papers 19-07, Monash University, Department of Economics.
    8. Chotikapanich, Duangkamon & Griffiths, William E, 2002. "Estimating Lorenz Curves Using a Dirichlet Distribution," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 290-295, April.
    9. Satya Paul & Sriram Shankar, 2020. "An alternative single parameter functional form for Lorenz curve," Empirical Economics, Springer, vol. 59(3), pages 1393-1402, September.
    10. Sarabia, José María & Gómez-Déniz, Emilio & Sarabia, María & Prieto, Faustino, 2010. "A general method for generating parametric Lorenz and Leimkuhler curves," Journal of Informetrics, Elsevier, vol. 4(4), pages 524-539.
    11. Khosravi Tanak, A. & Mohtashami Borzadaran, G.R. & Ahmadi, Jafar, 2018. "New functional forms of Lorenz curves by maximizing Tsallis entropy of income share function under the constraint on generalized Gini index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 280-288.
    12. Ogwang, Tomson & Gouranga Rao, U. L., 1996. "A new functional form for approximating the Lorenz curve," Economics Letters, Elsevier, vol. 52(1), pages 21-29, July.
    13. Kwang Soo Cheong, 1999. "A Comparison of Alternative Functional Forms For Parametric Estimation of the Lorenz Curve," Working Papers 199902, University of Hawaii at Manoa, Department of Economics.
    14. Gholamreza Hajargasht & William E. Griffiths, 2016. "Inference for Lorenz Curves," Department of Economics - Working Papers Series 2022, The University of Melbourne.
    15. Rohde, Nicholas, 2009. "An alternative functional form for estimating the Lorenz curve," Economics Letters, Elsevier, vol. 105(1), pages 61-63, October.
    16. Thitithep Sitthiyot & Kanyarat Holasut, 2023. "A universal model for the Lorenz curve with novel applications for datasets containing zeros and/or exhibiting extreme inequality," Papers 2304.13934, arXiv.org.
    17. Enora Belz, 2019. "Estimating Inequality Measures from Quantile Data," Economics Working Paper Archive (University of Rennes & University of Caen) 2019-09, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    18. Melanie Krause, 2014. "Parametric Lorenz Curves and the Modality of the Income Density Function," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(4), pages 905-929, December.
    19. Florent Bresson, 2010. "A general class of inequality elasticities of poverty," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 8(1), pages 71-100, March.
    20. Genya Kobayashi & Kazuhiko Kakamu, 2019. "Approximate Bayesian computation for Lorenz curves from grouped data," Computational Statistics, Springer, vol. 34(1), pages 253-279, March.

    More about this item

    Keywords

    Cumulative distribution function; Probability density function; Mean; quantiles; Lorenz curve; Gini coefficient; Pietra index; Robin Hood index; Trapezium rule; Simpson´s rule; Regression models; Difference quotients; Derivative of Lorenz curve;
    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
    • E64 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Incomes Policy; Price Policy

    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:spt:stecon:v:10:y:2021:i:1:f:10_1_3. 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: Eleftherios Spyromitros-Xioufis (email available below). General contact details of provider: http://www.scienpress.com/ .

    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.