Mapping ICT skills demand: a latent transition analysis of online job advertisements in Italy

Integrating traditional statistical sources on the labour market with online data availability is challenging as, together with ofcial statistics, online inormation oers detailed and timely inormation about the specic skills required by businesses. In the light o this, online job advisements (OJAs) data carried out by Lightcast or Italy or ICT proessionals, rom the year 2019 to 2022, are used to analyse the evolution o skills required, paying particular attention to skill type and regional detail. From a methodological point o view, a latent class transition analysis is applied. Skills are classied by using as indicator variables the importance o each skill in order to: (i) classiy skills into homogenous classes characterised by dierent levels o importance, (ii) assess whether changes in latent class membership occurred over time, and (iii) evaluate the eect o skill type and region where job is required on the latent status membership and transition probability. Empirical ndings uncovered three latent statuses o skills importance rom the low to the high intensity. The levels o skill importance remain quite stable over the period considered, but some interesting changes are detected or some skill types and some Italian regions.