In this paper we investigate the labour content of complex products. By exploiting O*NET information on the skill and knowledge required by occupations, we find that the product complexity measure suggested by Hausmann and Hidalgo (2009) is highly intensive in STEM knowledge and in Science, Mathematics and Critical Thinking skill requirements. We then propose a new measure of occupational complexity based on these occupational features. Among other advantages, this indicator has the merit to measure complexity for service industries that, so far, has never been measured. In an empirical model of the growth of USA Metropolitan Areas (MSAs), we find that MSAs whose initial industrial structure embeds a higher level of occupational complexity experience higher real per capita GDP growth over the 2001–2017 period. The occupational complexity measure is a stronger predictor of growth than other metrics of industries’ occupational and task content as well as compared to indicators of local occupational and industrial composition. When we separately compute occupational complexity of service and manufacturing industries and delve into their specific role for long run growth, we find a prominent role of the occupation complexity embedded in local services with respect to the one embedded in local manufacturing. Our baseline evidence is corroborated in the context of the NUTS3 regions of France over the period 2010–2017.
|Stato di pubblicazione||Pubblicato - 2020|
- Occupational complexity
- Regional growth