Beta
314437

Modeling the Household Income Expended on Food in Egypt: A Beta Regression Approach

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Last updated: 28 Dec 2024

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Abstract

The Beta distribution is a highly flexible parametric distribution, able to accommodate both unimodal and bimodal densities with varying severity of skewness. Beta regression is an increasing popular approach for modeling rates, proportions, concentration, i.e., the situations where the dependent variable is continuous and restricted to the unit interval (0,1). It is based on the assumption that the response variable is Beta-distributed and that its mean is related to a set of regressors through a linear predictor with unknown coefficients and a link function. Beta regression model is similar to the approach of generalized linear models due to McCullagh and Nelder (1989), except that the distribution of the response is not a member of the exponential family distributions. Beta regression combines the strength of generalized linear models with the flexibility of the Beta distribution providing utility in modeling skewed and/or bounded variable. In this paper, a Beta regression model is developed to perform inference in both fixed and variable dispersion Beta regression models using real data of food expenditure in Egypt (2011). The concentration is on modeling the proportion of income spent on food using Beta regression approach.

DOI

10.21608/esju.2014.314437

Keywords

Beta Distribution - Beta Regression - Household Income, rates, proportions

Volume

58

Article Issue

1

Related Issue

43134

Issue Date

2014-06-01

Publish Date

2014-06-01

Page Start

1

Page End

30

Print ISSN

0542-1748

Online ISSN

2786-0086

Link

https://esju.journals.ekb.eg/article_314437.html

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https://esju.journals.ekb.eg/service?article_code=314437

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1

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Original Article

Type Code

1,914

Publication Type

Journal

Publication Title

The Egyptian Statistical Journal

Publication Link

https://esju.journals.ekb.eg/

MainTitle

Modeling the Household Income Expended on Food in Egypt: A Beta Regression Approach

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Article

Created At

28 Dec 2024