Using fuzzy statistical models to estimate upper and lower bounds of Gini coefficient
Walaa Jabbar Al-ObaidiWlajbar93@gmail.comDepartment of StatisticsFaculty of Mathematical SciencesUniversity of TabrizTabriz, IranView full profile → , *Ramin Imany-NabiyyiCorresponding authorimany@tabrizu.ac.irDepartment of StatisticsFaculty of Mathematical SciencesUniversity of TabrizTabriz, IranView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 08 Jan 2024
- Published Online:
- 05 Aug 2024
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JSMS-1274
- Pages:
- 985–995
Abstract
Keywords
Subject Classifications
References
[1] Al-Qudaimi, A. Kaur, K. and Bhat, SH. Triangular fuzzy numbers multiplication: QKB method. Fuzzy Optimization and Modelling 2(2), 34-40 (2021).
[2] Buckley, J. Fuzzy Probability and Statistics. Springer-Verlag Berlin Heidelberg (2006).
[3] Dagum, C. A New Model of Income Distribution, the Lorenz Curve and the Gini Concentration Ratio, forth comming paper (1977).
[4] Chotikapanich, D.William Griffiths,Hajargasht. G. Using the GB2 Income Distribution. econometrics, 21, 1-24 (2018).
[5] Dagum, C. The generation and distribution of income, the Lorenz curve and the Gini ratio, Economic Applique’s, 33, 327–67 (1980).
[6] Dagum, C. A New Model of Personal Income Distribution: Specification and Estimation. Springer (1980).
[7] Ganjoei, R.A. Akbarifard, H. Mashinchi, M. and Jalaee, A. M. Estimation of upper and lower bounds of Gini coefficient by fuzzy data. Data in brief, 29, 212-224 (2020).
[8] Golden, J. A simple geometric approach to approximating the Gini coefficient. J. Economic Education, 39(1), 68-77 (2008).
[9] Fellman, J. Estimation of Gini coefficients using Lorenz curves. Journal of Statistical and Econometric Methods. 1(2), 31-38 (2012).
[10] Kleiber, C. and Kotz, S. Statistical Size Distributions in Economics and Actuarial Sciences, John Wiley and Sons, New York (2003).
[11] Kakamu, K. Simulation s tudies comparing Dagum and Singh-Maddala income distributions. Computational Economics, 48(4), 593-605 (2016).
[12] iber, C. Dagum versus Singh–Maddala income distributions, Economics Letters, 53, 265–8 (1996).
[13] McDonald J.B. and M. R. Ransom, An analysis of the bounds for the Gini coefficient, Journal of Econometrics, 17, 177-188 (1981).
[14] McDonald, J. B. Some generalized functions for the size distribution of income, Econometrica, 52 (1984),
[15] McDonald, J. B. and Mantrala, A. The distribution of income: revisited, Journal of Applied Econometrics, 10, 201–4 (1995).
[16] McDonald, J. B. and Xu, Y. J. A generalization for the beta distribution with applications, Journal of Econometrics, 66, 133–52 (1995).
[17] perez, G.C and Alaiz, P. Using Dagum model to explain changes in personal income distribution. Applied Economic, (43), 77-86 (2011).
[18] Pena, J. B., Callealta, J. Casas, J. M., Merediz, A. and Nunez, J. Distribution Personal de la Renta en Espana, Piramide, Madrid (1996).
[19] Salem, S. K. and Mount, G. S. A convenient descriptive model of income distribution: the gamma distribution, Econometrica, 42, 115–27 (1974).
[20] Victoria-Feser, M. P. Robust Methods For Personal Income Distribution Models with Applications to Dagum’s models, in Reasearch on Economic Inequality, Vol. 1 (Eds) C. Dagum and A. Lemmi, JAI Press, Greenwich, CT, pp. 123–57 (1995).
[21] Victoria-Feser, M. P. Robust methods for the analysis of income distribution, inequality and poverty, International Statistical Review, 68, 277–93 (2000).
[22] Zimmerman H. J. Fuzzy set theory and its applications. 4th ed. Boston: Kluwer Nih off (2001).
