This paper analyses the link between technological product and processes innovations and expectations about future employment for different types of labour in manufacturing. The empirical model allows for endogeneity of the firm's innovation decision in the labour demand equations. The system of...

This paper analyses the link between technological product and processes innovations and expectations about future employment for different types of labour in manufacturing. The empirical model allows for endogeneity of the firm's innovation decision in the labour demand equations. The system of...

This paper analyses the link between technological product and processes innovations and expectations about future employment for different types of labour in manufacturing. The empirical model allows for endogeneity of the firm's innovation decision in the labour demand equations. The system of...

We present empirical evidence suggesting that technological progress in the digital age will be biased not only with respect to skills acquired through education but also with respect to noncognitive skills (personality). We measure the direction of technological change by estimated future...

Industrial policies are widespread, but evidence on their workforce effects remains limited. We present novel evidence on the impact of EU technology subsidies on employment and skill demand in Finnish SMEs, 1994-2018. The subsidies fund new machinery, including robots and CNC machines....

It has become common within the literature of skill-biased technological change to look at technologies, as well as their impact on the demand for labor as homogeneous across industries. This paper challenges this view. Using a linked employer-employee panel of Germany differentiated by...

This paper examines whether ICT substitute labour and reduce the demand for labour. We used firm-level comparable data separately for firms in manufacturing, services and ICT-producing sectors from seven European countries. We adopted a common methodology and applied it to a unique dataset...