With job search activities increasingly migrating online, researchers now have new avenues to study the labour market, especially the job matching process, at an unprecedented level of detail. Using data from MyCareersFuture.sg, we study the different dimensions of mismatches between jobseekers and the jobs they applied for at the point of application, and find that skills mismatch is the most significant mismatch dimension.Segmenting skills mismatch into generic and non-generic skills mismatch, we find that non-generic skills mismatch is a more significant factor than generic skills mismatch.

Next, we apply machine learning approaches to identify the factors that have the greatest effect on labour market application outcomes. The two outcomes examined are the likelihood of unemployed jobseekers securing a successful job match and the risk of unemployed jobseekers becoming long-term unemployed. Our findings again suggest that skills mismatch is an important driver of these outcomes. Apart from skills mismatch, other factors that have a significant impact on application outcomes include the job search effort on the part of the jobseeker.

The views expressed in this paper are solely those of the authors and do not necessarily reflect those of the Ministry of Trade and Industry or the Government of Singapore.

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