Graph Configuration Model based Evaluation of the Education-Occupation Match
Laszlo Gadar and Janos Abonyi
We developed a graph-based model of education to work transition. To extract the hidden structure of the career paths we analyzed the degree distributions of the bipartite graphs of educational programs and professions, and we modified the Newman modularity measure to evaluate their matching. The proposed network model is based on the integration of the databases of the National Tax Administration, the National Health Insurance Fund, and the data warehouse of the Hungarian higher education. To demonstrate the information content of this administrative database, we presented a brief analysis of gender pay gap and the spatial distribution of over-education. The calculated matching measures and clusters can support policymakers to fine-tune the fragmented program structure of the Hungarian higher education.
The R code that generates all the results (and figures) is also avaliable in this repository.
The CSV file is based on the integration of the databases of the National Tax Administration, the National Health Insurance Fund, and the data warehouse of the Hungarian higher education. The analyzed administrative data covers 15 thousand people graduated in 2009/2010 school year and worked in 2012 May. Based on the data of 7402 bachelor students we defined a bipartite graph of 110 bachelor programs and 113 occupations encoded by the third level of International Standard Classification of Occupations (ISCO) code system.