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Modelling the potential human capital on the labor market using logistic regression in R

Author

Listed:
  • Ana-Maria Ciuhu

    (Institute of National Economy, Romanian Academy; National Institute of Statistics)

  • Nicoleta Caragea

    (National Institute of Statistics; Ecological University of Bucharest)

  • Ciprian Alexandru

    (National Institute of Statistics; Ecological University of Bucharest)

Abstract

This paper exposes the methodology of creating the profile of two categories of potential human capital using logistic regression in R. The profiles were created based on some social and economic characteristics provided by the 2015 Labour Force Survey, assuring the representativeness of results at national and regional level. In this sense, the logistic regression was used to model the relationship between economically inactive persons who are seeking for a job, but are not immediately available to start working, respectively economically inactive persons who are not seeking for a job, but are immediately available to start working, and some socio-economic predictors. The aim is to identify the impediments which determine inactive people not to become active on the labour market.

Suggested Citation

  • Ana-Maria Ciuhu & Nicoleta Caragea & Ciprian Alexandru, 2017. "Modelling the potential human capital on the labor market using logistic regression in R," Romanian Statistical Review, Romanian Statistical Review, vol. 65(4), pages 141-152, December.
    • Handle: RePEc:rsr:journl:v:65:y:2017:i:4:p:141-152
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    References listed on IDEAS

    as
    1. James Obben & Hans-Jurgen Engelbrecht & V. Wesley Thompson, 2002. "A logit model of the incidence of long-term unemployment," Applied Economics Letters, Taylor & Francis Journals, vol. 9(1), pages 43-46.
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    Cited by:

    1. Valentina Vasile & Elena Bunduchi & Daniel Stefan & Calin-Adrian Comes & Razvan Vasile & Anamari-Beatrice Stefan, 2023. "Are We Facing a Radical Change in the Migration Behavior of Medical Graduates from Less Developed Countries? Demographic Profile vs. Social Push Factors," IJERPH, MDPI, vol. 20(6), pages 1-18, March.

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    More about this item

    Keywords

    R statistical software; labor force; logistic regression; odds ratio;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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