Abstract
A number of Interdisciplinary literature highlights imperfect information as one possible explanation of skill mismatch, which in turn has implications for unemployment and informality rates. Despite the failures of information and its consequences, countries such as Colombia (where informality and unemployment rates are high) lack a proper labour market information system to identify skill mismatches and employers’ skill requirements. One reason for this absence is the cost of collecting labour market data. Recently, the potential use of online job portals as a source of labour market information has gained the attention of researchers and policymakers: since these portals can provide quick and relatively low-cost data collection. As such, these portals could be of use to Colombia. However, debates continue about the efficacy of this use, particularly concerning the robustness of the data collected. This thesis implements novel mixed-methods (such as web scraping, text mining, machine learning, etc.) to investigate to what extent a web-based model of skill mismatches can be developed for Colombia. The main contribution of this thesis is the finding that, with the proper techniques, job portals can be a robust source of labour market information. In doing so, it also contributes to current understanding by developing a conceptual and methodological approach to identify skills, occupations and skill mismatches using online job advertisements which would otherwise be too complex to collect and analyse via other means. In applying this novel methodology, this thesis provides new empirical data on the extent and nature of skill mismatches in Colombia for a considerable set of non-agricultural occupations in the urban and formal economy. Moreover, this information can be used as a complement to household surveys to monitor potential skill shortages. Thus, the findings are useful to policymakers, statisticians, policymakers, and education and training providers, amongst others.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have