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New fuzzy multiple regressions for the instantaneous and panel data “The determinants of Poverty in the Countries MENA”

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  • Belhadj, Besma

Abstract

Habitually, to determine the effect of certain economic and social variables on poverty in MENA, a classical multiple regression with a framework defined a priori verifying several limiting assumptions and easily misused is used. We propose, in this paper, a fuzzy alternative approach to classical multiple regressions with cross-sectional and panel data and explain how the proposed fuzzy methods works in a simple setting. As illustration, we estimates and analyze the effect of the annual GDP growth rate, unemployment rate, inflation rate and the annual population growth rate on poverty in MENA.

Suggested Citation

  • Belhadj, Besma, 2023. "New fuzzy multiple regressions for the instantaneous and panel data “The determinants of Poverty in the Countries MENA”," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    • Handle: RePEc:eee:phsmap:v:615:y:2023:i:c:s0378437123001206
    DOI: 10.1016/j.physa.2023.128565
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    References listed on IDEAS

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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Besma Belhadj, 2011. "A new fuzzy unidimensional poverty index from an information theory perspective," Empirical Economics, Springer, vol. 40(3), pages 687-704, May.
    3. Besma Belhadj & Firas Kaabi, 2020. "New membership function for poverty measure," Metroeconomica, Wiley Blackwell, vol. 71(4), pages 676-688, November.
    4. D'Urso, Pierpaolo & Gastaldi, Tommaso, 2000. "A least-squares approach to fuzzy linear regression analysis," Computational Statistics & Data Analysis, Elsevier, vol. 34(4), pages 427-440, October.
    5. World Bank, 2018. "Global Financial Development Report 2017/2018," World Bank Publications - Books, The World Bank Group, number 28482.
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    Cited by:

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    More about this item

    Keywords

    Fuzzy endogenous regressor; Fuzzy parameters; Fuzzy mathematical modeling; Cross-sectional data; Panel data;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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