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Inequality of Opportunity in the Labour Market Entry of Graduates in Italy


  • Patrizia Luongo

    () (University of Bari)


The aim of the study is to test for equality of opportunity at the en- try into the national labour market of Italian graduates. By using an Italian survey data on the transition from university to work, we focus on the probability to get a job within three years from the graduation, and we find significant differences across individuals with different family background. In an attempt to explain whether these differences refiect op- portunity inequality, we adopt the Gomulka-Stern decomposition method. This method allows us to decompose differences in the probability to find a job between groups of people with different family background into two additive components. The first component can be attributed to differ- ences between groups in the distribution of individualsfi characteristics. The second component is a residual difference which can be attributed to opportunity inequality under the assumption that there is no unobserved heterogeneity between groups. In the presence of unobserved heterogene- ity, this residual component gives us a biased estimation for the difference in probability explained by opportunity inequality.

Suggested Citation

  • Patrizia Luongo, 2010. "Inequality of Opportunity in the Labour Market Entry of Graduates in Italy," SERIES 0030, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised May 2010.
  • Handle: RePEc:bai:series:economia-series30

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    References listed on IDEAS

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    More about this item


    Inequality of Opportunity; Higher Education; Gomulka-Stern Decomposition.;

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • I2 - Health, Education, and Welfare - - Education
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities


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