Wenxuan Yang (p)

Amnon Frenkel

Human capital is an important driver of the economy. The regional distribution of human capital affects the development process of the economy. This paper applies Markov chain and its spatial form extensions to China’s human capital index over the 1985-2019 period and calculates the transition probabilities between different human capital levels. Results from this paper show that China’s regional human capital is uneven distributed, and this distribution is in dynamic change. Moreover, by comparing the results of non-spatial and spatial Markov chains, this study confirms the effect of regional spatial dependence on the change of human capital distribution, i.e., rich neighbors increase the probability that one region mo¬¬ves up to the higher class, and conversely, poor neighbors increase the probability that one region falls into a lower class. This article highlights the importance of incorporating the spatial effects into China's regional human capital.

José Manuel Casado Díaz, Hipólito Simón, Raquel Simón Albert (p), Matías Mayor Fernández

Tatiana Blinova

This study analyses the effect that the characteristics of the labour market of residence have on female participation and employment rates in Spain in order to identify the regional aspects that favour or hamper the good employment performance of this group, as well as to verify the possible spatial relationships. To this end, the Spanish LMAs are used as the reference territorial unit and spatial econometric techniques are applied to identify the interactions between regions and the influence of their own characteristics and those of neighbouring regions. Specifically, neighbourhood relationships have been considered within a radius of 50 kilometres. The evidence obtained indicates the presence of notable territorial differences in the distribution of participation and employment rates. In this sense, the econometric estimation shows that the female participation rate in a given market is influenced by its own internal characteristics, as well as by a spatial autoregressive process in the residuals. The employment rate, on the other hand, has a pattern of local spatial dependence, being influenced not only by its own characteristics but also by the characteristics and shocks derived from neighbouring regions, thus justifying the good delimitation of the LMAs. It should be noted that extending the neighbourhood criterion to allow the Madrid LMA to have at least one neighbour modifies the conclusions reached. In this case, the employment rate of a market is influenced by its own characteristics, by the characteristics of neighbouring regions and by the employment rate of the latter. Taking into account the economic and political importance of Madrid, considering its spatial relationship with neighbouring regions may hide other relationships of lesser intensity, as well as generate a fictitious spatial dependence between smaller LMAs.