Productivity growth and convergence: a stochastic frontier analysis

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. A β-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 a β-convergence equation for the obtained regional efficiency levels.

Citation

Cardoso, C.M.e.S. and Ravishankar, G. (2015), "Productivity growth and convergence: a stochastic frontier analysis", Journal of Economic Studies, Vol. 42 No. 2, pp. 224-236. https://doi.org/10.1108/JES-08-2013-0121