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The Italian Regional Dualism: A MARS and Panel Data Analysis

Author

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  • Iacopo Odoardi

    (National Foundation of Accountants - Economics and Statistical Office, Rome)

Abstract

The income gap between the richest and the poorest areas in Italy has increased in the last decades. We study the sources of regional wealth that can explain the differences in income and compare rich and poor areas to provide suggestions on how to bridge the gap. A multivariate adaptive regression splines (MARS) analysis is used to detect the relevant GDP determinants, and a fixed effects model is used to investigate the regional characteristics. The effects of the 2007 crisis are evident in all regions, and some structural weaknesses in the less wealthy areas limit the opportunities to exit the recession and close many socioeconomic gaps with the wealthiest regions.

Suggested Citation

  • Iacopo Odoardi, 2018. "The Italian Regional Dualism: A MARS and Panel Data Analysis," The Review of Regional Studies, Southern Regional Science Association, vol. 48(3), pages 323-346, Winter.
    • Handle: RePEc:rre:publsh:v48:y:2018:i:3:p:323-346
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    Citations

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    Cited by:

    1. Berigel, Muhammet & Boztaş, Gizem Dilan & Rocca, Antonella & Neagu, Gabriela, 2023. "A model for predicting determinants factors for NEETs rates: Support for the decision-makers," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    2. Iacopo Odoardi, 2020. "Can parents’ education lay the foundation for reducing the inactivity of young people? A regional analysis of Italian NEETs," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(1), pages 307-336, April.
    3. Silvia Emili & Federica Galli, 2022. "Self-perceptions and perceptions of peers: their role in understanding expenditure behaviours," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4573-4597, December.
    4. Berigel, Muhammet & Boztaş, Gizem Dilan & Rocca, Antonella & Neagu, Gabriela, 2024. "Using machine learning for NEETs and sustainability studies: Determining best machine learning algorithms," Socio-Economic Planning Sciences, Elsevier, vol. 94(C).
    5. Cristina Bernini & Silvia Emili & Federica Galli, 2021. "Does urbanization matter in the expenditure‐happiness nexus?," Papers in Regional Science, Wiley Blackwell, vol. 100(6), pages 1403-1428, December.
    6. Alice Guerra & Emanuela Randon & Antonello E. Scorcu, 2022. "Gender and deception: Evidence from survey data among adolescent gamblers," Kyklos, Wiley Blackwell, vol. 75(4), pages 618-645, November.
    7. Ensar Yılmaz & Zeynep Kaplan, 2022. "Regional polarization in Turkey," Growth and Change, Wiley Blackwell, vol. 53(1), pages 410-431, March.

    More about this item

    Keywords

    North-South problem; regional inequality; MARS; panel data; regional policy;
    All these keywords.

    JEL classification:

    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure

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