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The Impact of Education on the Behaviour of Labor Supply in Cameroon: an Analysis using the Nested Multinomial Logit Model

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  • Nga Ndjobo, Patrick Marie
  • Abessolo, Yves André

Abstract

This article renders an analysis of the impact of education on labour supply behaviour, particularly in terms of participation decision and the level of employment and unemployment of the active population in the labour market in Cameroon, through the nested logit model. Using data obtained from the database of ECAM III carried out in 2007, we find that individuals who constitute the labour supply being faced with four alternatives (domestic activities, the informal, the public and the private formal sectors) choose to work in the sectors which best values their education. Thus, for these individuals, it is more likely to choose to practice in the sectors associated with lower levels of education than other sectors. Also, these individuals have the tendency of orientating their choices primarily to sectors in which the average level of education is at most equivalent to theirs. Therefore, signals sent by job-seekers to employers, requesting access demand to certain sectors instead of others are obviously determine by their various levels of education. Moreover, participation in a sector of the job market in Cameroon is a decreasing function of average charged income and average worked hours that are established.

Suggested Citation

  • Nga Ndjobo, Patrick Marie & Abessolo, Yves André, 2013. "The Impact of Education on the Behaviour of Labor Supply in Cameroon: an Analysis using the Nested Multinomial Logit Model," MPRA Paper 51158, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:51158
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    References listed on IDEAS

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    2. Jacob A. Mincer, 1974. "Introduction to "Schooling, Experience, and Earnings"," NBER Chapters, in: Schooling, Experience, and Earnings, pages 1-4, National Bureau of Economic Research, Inc.
    3. Silberhorn, Nadja & Boztuğ, Yasemin & Hildebrandt, Lutz, 2006. "Estimation with the nested logit model: Specifications and software particularities," SFB 649 Discussion Papers 2006-017, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. George Psacharopoulos & Harry Anthony Patrinos, 2004. "Returns to investment in education: a further update," Education Economics, Taylor & Francis Journals, vol. 12(2), pages 111-134.
    5. Jacob A. Mincer, 1974. "Schooling, Experience, and Earnings," NBER Books, National Bureau of Economic Research, Inc, number minc74-1, June.
    6. McFadden, Daniel, 1987. "Regression-based specification tests for the multinomial logit model," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 63-82.
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    More about this item

    Keywords

    education; labor supply; nested multinomial logit; public formal; private formal and informal sectors; ECAMIII; Cameroon;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D1 - Microeconomics - - Household Behavior
    • I2 - Health, Education, and Welfare - - Education
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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