Abstract/Sommario: In the aftermath of the financial and economic crisis, large shares of working-age individuals in Italy either did not work or only to a limited extent. As the employment rate bottomed out in 2013, 32% were without employment during the entire year, and a further 7% had weak labour-market attachment, working only a fraction of the year, or on restricted working hours. This paper applies a novel method for measuring and visualising employm ...; [Leggi tutto...] In the aftermath of the financial and economic crisis, large shares of working-age individuals in Italy either did not work or only to a limited extent. As the employment rate bottomed out in 2013, 32% were without employment during the entire year, and a further 7% had weak labour-market attachment, working only a fraction of the year, or on restricted working hours. This paper applies a novel method for measuring and visualising employment barriers of individuals with no or weak labour-market attachment, using household micro-data.

Abstract/Sommario: This literature review takes stock of what is known about the impact of artificial intelligence on the labour market, including the impact on employment and wages, how AI will transform jobs and skill needs, and the impact on the work environment. The purpose is to identify gaps in the evidence base and inform future OECD research on AI and the labour market.

Abstract/Sommario: This paper provides a comprehensive discussion of the labour market security dimension of the OECD’s job quality framework, thereby complementing the analysis in Chapter 3 of the OECD Employment Outlook 2014 and Chapter 5 of the OECD Employment Outlook 2015. It makes three main contributions. First, it provides an in-depth discussion of the definition and measurement of labour market security. and discusses in detail the various methodological issues surrounding its measurement. Second ...; [Leggi tutto...] This paper provides a comprehensive discussion of the labour market security dimension of the OECD’s job quality framework, thereby complementing the analysis in Chapter 3 of the OECD Employment Outlook 2014 and Chapter 5 of the OECD Employment Outlook 2015. It makes three main contributions. First, it provides an in-depth discussion of the definition and measurement of labour market security. and discusses in detail the various methodological issues surrounding its measurement. Second, it offers a comprehensive statistical portrait of labour market security across countries, socio-economic groups and over time. Third, it investigates the statistical relationship between labour market insecurity and subjective measures of well-being. Importantly, we find that the risk of unemployment has a detrimental effect on the well-being of employed workers, and that this reflects to an important extent the risk of staying unemployed for a prolonged period of time. Policymakers should therefore focus not only on reducing the level of unemployment, but also on speeding up unemployment turnover at a given level of unemployment. Unemployment insurance also mitigates the adverse effect of unemployment risk, and particularly that of long-term unemployment, on the well-being of the employed.

Abstract/Sommario: Technological developments are one of the major forces behind the need for retraining, but they can also be part of the solution. In particular, Artificial Intelligence (AI) has the potential to increase training participation, including among currently underrepresented groups, by lowering some of the barriers to training that people experience and by increasing motivation to train. Moreover, certain AI solutions for training may improve the alignment of training to labour market needs ...; [Leggi tutto...] Technological developments are one of the major forces behind the need for retraining, but they can also be part of the solution. In particular, Artificial Intelligence (AI) has the potential to increase training participation, including among currently underrepresented groups, by lowering some of the barriers to training that people experience and by increasing motivation to train. Moreover, certain AI solutions for training may improve the alignment of training to labour market needs, and reduce bias and discrimination in the workplace. In order to realise the benefits of AI for training and ensure that it yields benefits for all, it will be necessary to address potential drawbacks in terms of changing skills requirements, inequalities in access to data, technology and infrastructure and important ethical issues.