Education, routine, and complexity-biased Knowledge Enabling Technologies: Evidence from Emilia-Romagna, Italy

We analyze the relationship between the use of Key Enabling Technologies (KETs) and the demand for occupations, tasks, and skills in the local labour market areas (LLMAs) of Emilia-Romagna, Italy. We merge three data sources, and we compute both the share of highly educated employees, or of employees accomplishing low- versus high-routine tasks, and three novel indicators measuring the complexity of occupations, tasks, and skills. Our panel estimates show that a larger share of KETs not only stimulates a higher demand for workers holding a tertiary education degree, or accomplishing less routinary tasks, but also a higher demand for a wider, and more exclusive, set of occupations, tasks, and skills. These results are also robust to unobserved heterogeneity and reverse causality.