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Modelling Income Drivers in Peripheral Municipalities: The Case of Italian Inner Areas

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  • Luca Romagnoli

    (Department of Economics, University of Molise, 86100 Campobasso, Italy)

  • Paola Di Renzo

    (Department of Economics, University of Molise, 86100 Campobasso, Italy)

  • Luigi Mastronardi

    (Department of Biosciences and Territory, University of Molise, 86090 Pesche, Italy)

Abstract

The paper provides new evidence on the relationship among per capita incomes, local expenditures and territorial economic structure in Italian inner areas. The study area comprises the municipalities belonging to three Italian regions, namely, Marche, Abruzzo and Molise. The methodology employed involves a panel multilevel regression model, in order to investigate both on territorial and time changes. The period under analysis covers 2008–2016, the years following the outbreak of the global crisis. The results highlight the importance of three public expenditure categories—Environment protection and planning, Tourism, and Cultural heritage—on the growth of per capita incomes. Regional economic structure also plays an important role, especially through the rate of employees in the industrial sector. In order to increase the effectiveness of local public policies, a re-allocation of global expenditures among its various components might be recommended. Another suggestion concerns the implementation of integrated policies oriented both to tourism and to the enhancement of territorial assets.

Suggested Citation

  • Luca Romagnoli & Paola Di Renzo & Luigi Mastronardi, 2022. "Modelling Income Drivers in Peripheral Municipalities: The Case of Italian Inner Areas," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:14754-:d:967477
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    Cited by:

    1. Ivan Blečić & Arnaldo Cecchini & Emanuel Muroni & Valeria Saiu & Serafino Scanu & Giuseppe Andrea Trunfio, 2023. "Addressing Peripherality in Italy: A Critical Comparison between Inner Areas and Territorial Capital-Based Evaluations," Land, MDPI, vol. 12(2), pages 1-14, January.
    2. Angelo Leogrande & Carlo Drago & Massimo Arnone, 2024. "Analyzing Regional Disparities in E-Commerce Adoption Among Italian SMEs: Integrating Machine Learning Clustering and Predictive Models with Econometric Analysis," Working Papers hal-04700413, HAL.
    3. Perugini, Francesco, 2024. "Local government efficiency and economic growth: The Italian case," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).

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