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

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Kakwani, Nanak, 1980. "On a Class of Poverty Measures," Econometrica, Econometric Society, vol. 48(2), pages 437-446, March.
    4. 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.
    5. Rohde, Nicholas, 2009. "An alternative functional form for estimating the Lorenz curve," Economics Letters, Elsevier, vol. 105(1), pages 61-63, October.
    6. 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.
    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. Johan Fellman, 2012. "Estimation of Gini coefficients using Lorenz curves," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 1(2), pages 1-3.
    9. Gupta, Manash Ranjan, 1984. "Functional Form for Estimating the Lorenz Curve," Econometrica, Econometric Society, vol. 52(5), pages 1313-1314, September.
    10. 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.
    11. 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.
    12. Chotikapanich, Duangkamon, 1993. "A comparison of alternative functional forms for the Lorenz curve," Economics Letters, Elsevier, vol. 41(2), pages 129-138.
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    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

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