Shweta Grover (p), Ajay Sharma

In this paper, we analyze the role of worker and firm side characteristics of job on the wage dispersion in the labour market. We use the concept of education-occupation mismatch to explain the wage dispersion in the context of developing countries. We use the statistical approach (Realized Method) to measure the extent of over and under education as per the occupation category of the workers. Using the Mincerian approach to wage determination, we analyze the impact of worker, firm and labour market characteristics in explaining wage dispersion, while correcting for sample selection bias in employment choice and occupational choice. We use quantile regression method to understand the effect of education-occupation mismatch on wage distribution. We find that over and under education is penalized in the labour market in terms of lower returns to education (either surplus or deficit). Interestingly, over and under education have higher effect on the lower end of the wage distribution as compared to top end. Thus mismatch between education-occupation leads to higher wage dispersion due to its regressive effects.

Victor-Raul Lopez-Ruiz, José-Luis Alfaro-Navarro, Domingo Nevado-Peña (p)

The technological factor is a key element for the development of cities and regions, an element that must be clearly influenced by the existing human development. In this work, the relationship between the capacities of the citizens of a region and its effective technological development is proposed as a working hypothesis. Thus, the relationship between the capacities of citizens and the technological development of a region must be important to strengthen the implementation of the so-called Smart cities or regions. Considering these two elements as the most important in the development of a region, in this paper we analyse the existing relationships between the capacities of citizens and the technological development of a region. Specifically, the NUTS 2 regions in Europe are analysed with official information available in Eurostat. To measure human development we propose the definition of a ‘Smart Human’ index based on a synthetic indicator obtained from the available information. To establish this index, we consider three key elements in the human development of a region: the capacity for cultural openness; the education; and the culture of citizens. In this way we define an indicator for each of the dimensions and a global indicator. On the other hand, when analysing technological development we consider information, separately, regarding the use and technological capacity of a region, to establish an indicator for each of the dimensions and another indicator of the technological development of the regions. The way of weighing each of the variables considered in the final indicator has been used a Principal Component Analysis (PCA) that allows assigning weights in an objective manner and through a re-scaling of the indicators we have been able to obtain indexes whose maximum value is 100 and minimum 0 to facilitate interpretation. Finally, a correlation analysis is developed that allows us to determine the relationships between human development of a region and the use and capacity of technologies, without establishing a causal relationship due to the complexity of the same, which we understand in a simultaneous system.

Marco Delogu (p), Michel Beine , Lionel Ragot

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This paper studies the determinants of international students’ mobility at the university level, focusing specifically on the role of tuition fees. We first develop an original Random Utility Maximization model of location choice for international students in the presence of capacity constraints of the hosting institutions. The last layer of the model gives rise to a gravity equation. This equation is estimated using new data on student migration flows at the university level for the U.K. We control for the endogeneity of tuition fees by taking benefit of the institutional constraints in terms of tuition caps ap-
plied in the UK to European students at the bachelor level. The estimations support a negative impact of tuition fees and stress the need to account for the endogenous nature of the fees in the empirical identification of their impact. The estimations also support an important role of additional destination-specific variables such as host capacity, the
expected return of education and the cost of living in the vicinity of the university.