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Fuzzy multiple regressions for Cross-Section and Panel data

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  • Belhadj, Besma

Abstract

A classical multiple regression is a framework defined a priori verifying several limiting assumptions and easily misused. We propose a fuzzy alternative approach to classical multiple regressions for cross-sectional and panel data. As illustration, we estimate and analyze the effect of the annual GDP growth rate, unemployment rate, inflation rate and annual population growth rate on poverty in the Middle East and North Africa (MENA) region.

Suggested Citation

  • Belhadj, Besma, 2024. "Fuzzy multiple regressions for Cross-Section and Panel data," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    • Handle: RePEc:eee:soceps:v:91:y:2024:i:c:s0038012123002732
    DOI: 10.1016/j.seps.2023.101761
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    References listed on IDEAS

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    1. D'Urso, Pierpaolo, 2003. "Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 47-72, February.
    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.
    Full references (including those not matched with items on IDEAS)

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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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