Unravelling Deep Integration: Local Labour Market Effects of the Brexit Vote
Beata Javorcik, Ben Kett, Katherine Stapleton and Layla O'Kane
This paper uses high frequency data on the near universe of job adverts posted online in the UK to study the impact of the Brexit referendum on labour demand between January 2015 and December 2019. We develop measures of local labour market exposure to the threat of trade barriers on both goods and services exports if the UK were to leave the EU without a trade deal. We find that regions that were more exposed to potential barriers on professional services exports saw a differential decline in online job adverts in the period after the referendum, particularly for higher-skilled jobs. This effect was distinct from the impact of the exchange rate depreciation, uncertainty surrounding future immigration policy and the threat of future barriers on trade in goods.
Automation, trade and multinational activity: Micro evidence from Spain
Katherine Stapleton & Michael Webb
We use a rich dataset of Spanish manufacturing firms from 1990 to 2016 to shed new light on how automation in a high-income country affects trade and multinational activity involving lower-income countries. By exploiting supply side improvements in the capabilities of robots over time, as described in patents, we show that contrary to the speculation that automation will cause 'reshoring', the use of robots in Spanish firms actually had a positive impact on their imports from, and number of affiliates in, lower-income countries. Robot use causes firms to expand production, increase productivity and increases the probability that they start importing from, or opening affiliates in, lower-income countries. The sequencing of automation and offshoring has important consequences for the impact of automation, however. For firms that were offshoring to lower-income countries before they starting to use robots, robot adoption had no effect on the value of imports from lower-income countries, but decreased the share of imports sourced from lower-income countries. By contrast, for firms that had not already offshored to lower-income countries, robot adoption made them more likely to start doing so. We show that these findings can be explained in a framework that incorporates firm heterogeneity, the choice between automation, offshoring and performing tasks at home and where automation and offshoring both involve upfront fixed costs, such that their sequencing matters.
AI, firms and wages: Evidence from India
Alex Copestake, Ashley Pople & Katherine Stapleton
We examine the impact of artificial intelligence on hiring and wages in the service sector using a novel dataset of 15 million vacancy posts from India’s largest jobs website. We first document a rapid rise in demand for AI skills since 2016, particularly in the IT, finance and professional services industries. Vacancies demanding AI skills list substantially higher wages, but require more education and are highly concentrated in the largest firms and a small number of high-tech clusters. Exploiting plausibly exogenous variation in exposure to advances in AI technologies, we then examine the impacts of establishment demand for AI skills as a proxy for AI adoption. We find that growth in AI demand has a direct negative impact on the growth of non-AI and total job posts, and reduces the growth of wage offers across the distribution
Work in Progress
Artificial Intelligence and Services Offshoring
Katherine Stapleton & Layla O'Kane
This paper constructs detailed measures of the demand for Machine Learning (ML) skills in UK firms, local labour markets and industries using a dataset of the majority of all job adverts posted online in the UK between 2012 and 2017. The demand for ML skills has risen rapidly in this period and the growth has been prevalent across a wide range of industries. We combine these measures with data on UK services trade to explore how the deployment of ML in the UK has affected services offshoring. By exploiting technical advances in the task-specific capabilities of ML, which have affected some occupations relatively more than others, we show that ML deployment has led to an increase in services offshoring, particularly to lower-income countries, rather than high-income countries. This increase has mainly been in ICT-related and Business and Professional Services and India has been the main beneficiary country. In the UK, ML deployment has had a weakly positive impact on labour demand for non-ML roles, particularly for lower skilled occupations.
Technology and Global Value Chains: Evidence from Denmark
Friedrich Bergmann & Katherine Stapleton
There is a growing debate over whether the path of manufacturing-led development will remain viable for developing countries, or whether the advanced capabilities of robots will render labour cost differentials obsolete, leading to a decline in offshoring to developing countries or ’reshoring’ of manufacturing production. To date, there is relatively little empirical evidence on this question. In this paper we shed new light on the relationship between automation and offshoring using data on the universe of Danish firms, employees and trade transactions. Exploiting supply side improvements in the capabilities of robots, we show that robot exposure leads firms to increase offshoring to both high income and low and middle income countries, with an even greater increase for the latter. However, the increase to low and middle income countries only occurs for countries that are existing offshoring destinations, while for high income countries firms start offshoring to new countries as well.