Estimating Poverty Measures using Truncated Distributions and its Applications
Nagwa Albehery1, Tonghui Wang2
1Nagwa Albehery, Department of mathematics and Applied Statistics and Insurance, Helwan University/ Faculty of Commerce and Business administration , Cairo, Egypt.
2Tonghui Wang, Department of Mathematics, New Mexico State University/ College of Sciences/ Las Cruces, United States of America.
Manuscript received on April 01, 2015. | Revised Manuscript Received on April 09, 2015. | Manuscript published on April 20, 2015. | PP: 28-32 | Volume-3 Issue-5, April 2015. | Retrieval Number: E0617043515/2015©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Poverty measures are used to measure poverty levels or degrees of poverty in a population. In this paper, we investigate the estimation of poverty measures using truncated log-normal, truncated gamma, and truncated epsilon-skew-normal distributions. For comparisons and illustrations, our results are applied to the real data sets collected in Egypt between 1995/1996 and 2008/2009.
Keywords: Poverty measures, Parametric estimation, Income distributions, Truncated distributions.