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The labour market and the distribution of earnings: an empirical analysis for Italy

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  • Fabio Clementi
  • Michele Giammatteo

Abstract

Using four waves of data from the Participation Labour Unemployment Survey, a database of information on the Italian labour market supply, we address the question of earnings dispersion by applying a 'nested' decomposition procedure of the Theil inequality measure, which combines into a unified framework the standard decompositions by population subgroups and income sources. The empirical evidence obtained points to the key role played by the self-employees in shaping labour income inequality, especially at the upper extreme of the earnings distribution, and the emergence of non-standard forms of employment as an important feature of the contemporary workplace.

Suggested Citation

  • Fabio Clementi & Michele Giammatteo, 2014. "The labour market and the distribution of earnings: an empirical analysis for Italy," International Review of Applied Economics, Taylor & Francis Journals, vol. 28(2), pages 154-180, March.
    • Handle: RePEc:taf:irapec:v:28:y:2014:i:2:p:154-180
    DOI: 10.1080/02692171.2013.838544
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    Citations

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    Cited by:

    1. Gianluca Busilacchi & Giovanni Gallo & Matteo Luppi, 2022. "I would like to but I cannot. The determinants of involuntary part-time employment: Evidence from Italy," Center for the Analysis of Public Policies (CAPP) 0177, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    2. Caselli, Mauro & Fracasso, Andrea & Marcolin, Arianna & Scicchitano, Sergio, 2021. "The reassuring effect of firms' technological innovations on workers' job insecurity," GLO Discussion Paper Series 938, Global Labor Organization (GLO).
    3. Mauro Caselli & Andrea Fracasso & Arianna Marcolin & Sergio Scicchitano, 2023. "Technological Innovations and Workers’ Job Insecurity: The Moderating Role of Firm Strategies," CESifo Working Paper Series 10673, CESifo.
    4. Oksana Nezhyvenko, 2018. "Informal Employment in Ukraine and European Union Transition Countries," Erudite Ph.D Dissertations, Erudite, number ph18-03 edited by Philippe Adair, February.
    5. Sauter, Caspar & Grether, Jean-Marie & Mathys, Nicole A., 2016. "Geographical spread of global emissions: Within-country inequalities are large and increasing," Energy Policy, Elsevier, vol. 89(C), pages 138-149.
    6. Esposito, Piero & Scicchitano, Sergio, 2020. "Educational mismatches, technological change and unemployment: evidence from secondary and tertiary educated workers," GLO Discussion Paper Series 465, Global Labor Organization (GLO).
    7. Berton, Fabio & Migheli Matteo, 2015. "Estimating the marginal rate of substitution between wage and employment protection," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201529, University of Turin.
    8. Bonacini, Luca & Gallo, Giovanni & Scicchitano, Sergio, 2020. "All that glitters is not gold. Effects of working from home on income inequality at the time of COVID-19," GLO Discussion Paper Series 541, Global Labor Organization (GLO).
    9. Luca Bonacini & Giovanni Gallo & Sergio Scicchitano, 2021. "Working from home and income inequality: risks of a ‘new normal’ with COVID-19," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 303-360, January.
    10. Paolo Di Caro, 2017. "The contribution of tax statistics for analysing regional income disparities in Italy," Journal of Income Distribution, Ad libros publications inc., vol. 25(1), pages 1-27, March.

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