Human resources are an essential element in territorial development. When the same are characterized by a high level of training are enhancers of a series of effects which are essential in the relationship between territorial and social cohesion. In this regard, the existence of higher education institutions across the territory allows a delocalised qualification of human resources but, by itself, does not warrant the implantation of these resources in the various regions. So, is this paper we carry out as the main objective to analyse the spatial convergence of knowledge through the study of the evolution of the percentage of the population with a higher education level in the periods elapsed between the last two censuses in Portugal, i.e. between 1991-2001 and 2001-2011. In the majority of the empirical studies, regional (or spatial) economic convergence spatial) is studied from the viewpoint of the growth of per capita GDP. However, since human capital is a key factor in economic growth it seems to be important to know the spatial distribution of the that kind of capital and whether the regions have converged in terms of stock of qualified human resources. In fact, it is expected that a relevant spatial convergence of knowledge will be reflected in a spatial convergence in terms of economic growth, or even of unemployment rates. Portugal is, as is well known, an uneven country from a regional point of view, this also being true from the point of view of the location of its most skilled human resources. This paper showed that, despite the qualifications, measured by the percentage of resident population with higher education level, having risen considerably (from 1991 until 2011), in Portugal, the process of regional convergence (of knowledge) was of (very) little significance. This result is also applicable when gender differences are taken into account. In fact, despite the male population indicates to possess characteristics of greater mobility, the convergence process (in the period 2001-2011, i.e. when the data is available also by gender) did not alter significantly the relative position of the various NUTs about the proportion of their population possessing a higher education level. In terms of potential avenues to new analyses, it seems important to consider other variables that are also assignable to the potential effects of possessing a certain level of knowledge as, for example, productivity levels or unemployment rates (differentiated by level of education).
