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Drivers of Income Inequality Across Italian Provinces: Unraveling the Role of Digitalisation and Labour Flexibility

Author

Listed:
  • Cirillo, Valeria
  • Divella, Marialuisa
  • Simone, Giuseppe

Abstract

This paper examines the drivers of income inequality across Italian provinces, focusing on the interaction between digitalisation and labour market flexibility. Using a novel provincial panel that combines Italian Labour Force Survey (LFS) data with detailed information on tasks from the INAPP-ISTAT Survey on Italian Occupations (ICP) and tax-based income records from Italian Ministry of Economics and Finance (MEF), we show that a higher incidence of non-standard employment reduces the labour share, lowers average employment income, and increases the gap between high- and low-income earners. Digitalisation, measured through the digital task intensity of local occupations, is associated with higher average incomes but also greater income polarisation. However, the income gains from digitalisation weaken and eventually disappear in provinces characterised by more precarious employment. Overall, the findings suggest that the digital transition, in the absence of stronger labour market protections, may reinforce rather than reduce territorial disparities.

Suggested Citation

  • Cirillo, Valeria & Divella, Marialuisa & Simone, Giuseppe, 2026. "Drivers of Income Inequality Across Italian Provinces: Unraveling the Role of Digitalisation and Labour Flexibility," GLO Discussion Paper Series 1816, Global Labor Organization (GLO).
    • Handle: RePEc:zbw:glodps:1816
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    References listed on IDEAS

    as
    1. Valeria Cirillo & Andrea Ricci, 2022. "Heterogeneity matters: temporary employment, productivity and wages in Italian firms," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 39(2), pages 567-593, July.
    2. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    3. Enrique Fernández-Macías & Martina Bisello, 2022. "A Comprehensive Taxonomy of Tasks for Assessing the Impact of New Technologies on Work," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(2), pages 821-841, January.
    4. Tito Boeri & Andrea Ichino & Enrico Moretti & Johanna Posch, 2021. "Wage Equalization and Regional Misallocation: Evidence from Italian and German Provinces [“Regional Wage Disparities and Migration.”]," Journal of the European Economic Association, European Economic Association, vol. 19(6), pages 3249-3292.
    5. Fana, Marta & Giangregorio, Luca, 2024. "The role of tasks, contractual arrangements, and job composition in explaining the dynamics of wage inequality: Evidence from France," Labour Economics, Elsevier, vol. 87(C).
    6. Angela Stefania Bergantino & Giulio Fusco & Mario Intini & Gianluca Monturano, 2026. "Digital divide and income inequality: causal evidence from Italian provinces," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 75(1), pages 1-45, March.
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    Keywords

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    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J41 - Labor and Demographic Economics - - Particular Labor Markets - - - Labor Contracts
    • J42 - Labor and Demographic Economics - - Particular Labor Markets - - - Monopsony; Segmented Labor Markets
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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