Abstract
The focus of this paper is on the role of human capital in explaining labor productivity variation among 198 European regions within a regression framework. Human capital is measured in terms of educational attainment using data for the active population aged 15 years and older that obtained tertiary education. The existence of unobserved human capital excluded from the model but likely to exhibit spatial dependence and non-zero covariance with the educational attainment variable, motivates the use of a spatial regression relationship that is known as spatial Durbin model. The paper outlines the model along with the associated methodology for estimating the impact of human capital on regional labor productivity, based upon LeSage and Pace’s approach to calculating scalar summary measures of impacts. A simulation approach with 10,000 draws is used to produce an empirical distribution of the model parameters needed for computing measures of dispersion for the impact estimates. The results obtained shed some interesting light on the contribution of human capital to labor productivity differences among European regions. A ceteris paribus increase in the level of human capital is found to have a significant and positive direct impact. But this positive direct impact is offset by a significant and negative indirect (spillover) impact leading to a total impact that is not significantly different from zero.
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