Presented by Max Nathan (Centre for Advanced Spatial Analysis (CASA), University College London)
A new wave of general-purpose technologies has emerged in the past decade. These technologies – such as cloud and machine learning/artificial intelligence – are held to be central for productivity and long-run economic growth, as well as driving regional disparities. The adoption of these technologies will be critical in shaping their future economic impact. In this webinar we combine rich job ads data and administrative sources to track and explain the diffusion of these ‘new wave’ technologies across UK firms and places over the 2010s. We focus on a specific economically and policy-relevant margin of diffusion: hiring. We first identify cloud and ML/AI jobs from ad text using keywords. We validate firm-level hiring-adoption links using survey data. We next explore patterns of hiring, and test for adoption drivers at firm and area level, including the relative roles of firm, industry and area characteristics; historic complements; and past technology waves. We use control functions and other methods to mitigate endogeneity concerns. Follow up work will explore links between these diffusion patterns and area-level wage inequality.
Max Nathan is Associate Professor in Applied Urban Sciences at CASA, University College London, and an Associate in the Urban Programme at the Centre for Economic Performance. He is an economic geographer with a background in public policy. His work looks at urban economic development, especially innovation systems and clusters; immigration and diversity; and urban public policy. Max co-founded the Centre for Cities and the What Works Centre for Local Economic Growth, and has over 15 years’ experience in think tanks, consultancy and government.