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Productivity growth and convergence: a stochastic frontier analysis

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  • Catarina Moura e Sa Cardoso
  • Geetha Ravishankar

Abstract

Purpose - – The purpose of this paper is to assess the effect of human capital development on regional productivity growth and convergence in the Spanish provinces over the period 1991-2006. Design/methodology/approach - – The stochastic frontier analysis (SFA) methodology is used to estimate production inefficiencies. This approach enables the assessment of the degree to which a given region’s observed output deviates from the maximal possible. Therefore, the resulting region specific productive efficiencies are modelled as outcomes of the level of human capital. Aβ-convergence equation for the regional efficiency levels is also estimated to detect any signs of regional catching-up. Findings - – The results show that increasing levels of human capital development are associated with lower regional inefficiency. All levels of education contributed to reduce the inefficiency levels, however, secondary schooling played a stronger role than primary and even higher education. There is also evidence of regional convergence towards the best practice frontier through a process that is beneficially aided by human capital development. Originality/value - – The paper combines the use of the SFA to study the effect of human capital on regional productivity with the estimation of aβ-convergence equation for the obtained regional efficiency levels.

Suggested Citation

  • Catarina Moura e Sa Cardoso & Geetha Ravishankar, 2015. "Productivity growth and convergence: a stochastic frontier analysis," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 42(2), pages 224-236, May.
    • Handle: RePEc:eme:jespps:v:42:y:2015:i:2:p:224-236
    DOI: 10.1108/JES-08-2013-0121
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    3. Qu, Jianying & Li, Ke & Ye, Ze & Shao, Shuai, 2022. "The impact of differential power pricing policy on firm productivity in China: Evidence from iron and steel firms," Journal of Asian Economics, Elsevier, vol. 80(C).

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