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Some Methods Of Quantile Regression For Analysis Of The Poverty In Iraq

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  • Fadel HAMID HADI ALHUSSEINI

    (Department of Statistics and Informatics, University of Craiova)

Abstract

World Bank has mentioned that approximately half of the world’s poor people live in countries with high income and many of these countries are oil producer countries. In this paper we study some of the economic variables (unemployment, average monthly per capita income, average monthly per capita spending on basic food, the rise in prices of these basic food goods and average taxes imposed on the Iraqi citizen) that impact on the increasing number of poor households in Iraq. We employ a regression model based on classical quantile regression for building the models which represent the relationship between the response variable and the covariates, through five quantile lines (0.16, 0.33, 0.50, 0.66, 0.83). We also use Bayes Lasso quantile regression for variable selection. The data were taken from an economic survey made by the Central Bureau of Statistics in 2007. We use R packages quantreg and bayesQR

Suggested Citation

  • Fadel HAMID HADI ALHUSSEINI, 2016. "Some Methods Of Quantile Regression For Analysis Of The Poverty In Iraq," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 5(1), pages 67-85, JULY.
    • Handle: RePEc:aes:jsesro:v:5:y:2016:i:1:p:67-85
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    More about this item

    Keywords

    poverty line; quantile regression model; Bayesian Lasso quantile regression; average number of poor Iraqi households;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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