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Assessing the Impact of Skilled Labor on Output Growth in South Africa: An ARDL Bound Testing Approach

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  • Tochukwu Timothy Okoli
  • Devi Datt Tewari
  • Eneh George N.O

Abstract

Economic theory emphasized the necessity of skill acquisition and conservation as a precondition for growth. This paper investigates the extent to which skilled labor can contribute to output growth in South Africa in the long run. The theoretical framework employed was based on Hicks neutral augmented CobbDouglas production function to account for the impact of technological progress on labor and capital. Skilled labor was measured with three parameters of experience (learning-by-doing), special training and educational attainments. The methodology employed the ARDL bound testing approach and found that whereas there is no short run causality running from the independent variables to the dependent variable, there was a long run causality running from the measures of skilled labor to growth. The coefficient of the ECT was both significant and negative; therefore, the system gets adjusted towards their long run equilibrium steady state at the speed of 23 percent annually. This means that the measures of skilled labor contribute to growth in the long run to the tune of 23 percent annually. The study therefore recommends investments in human capital through education and special trainings as well as to encourage knowledge transfer through globalization and from one generation to another to conserve skills.

Suggested Citation

  • Tochukwu Timothy Okoli & Devi Datt Tewari & Eneh George N.O, 2018. "Assessing the Impact of Skilled Labor on Output Growth in South Africa: An ARDL Bound Testing Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 10(2), pages 209-218.
    • Handle: RePEc:rnd:arjebs:v:10:y:2018:i:2:p:209-218
    DOI: 10.22610/jebs.v10i2(J).2230
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    References listed on IDEAS

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    2. Granger, C. W. J., 1988. "Causality, cointegration, and control," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 551-559.
    3. Alfred A. Haug, 2002. "Temporal Aggregation and the Power of Cointegration Tests: a Monte Carlo Study," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(4), pages 399-412, September.
    4. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    5. Kwabena Gyimah-Brempong & Oliver Paddison & Workie Mitiku, 2006. "Higher education and economic growth in Africa," Journal of Development Studies, Taylor & Francis Journals, vol. 42(3), pages 509-529.
    6. R. Santos Alimi, 2014. "ARDL Bounds Testing Approach to Cointegration: A Re-Examination of Augmented Fisher Hypothesis in an Open Economy," Asian Journal of Economic Modelling, Asian Economic and Social Society, vol. 2(2), pages 103-114, June.
    7. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
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