Paulo Bastos, Katherine Stapleton, Daria Taglioni and Hannah Wei
R&R at the Journal of International Economics
This study examines the role of multinational firms and global value chain linkages in the cross-country diffusion of emerging technologies. The analysis combines detailed information on the near-universe of online job postings in 17 countries with data on multinational networks and firm-to-firm linkages from 2014 to 2022. Online job postings are utilized to investigate how jobs related to emerging technologies spread through firm networks. The findings show that emerging technology jobs are highly concentrated within multinational firms and their supply chains. Approximately one third of all emerging technology job postings during this period come from Fortune 500 firms, their affiliates, buyers, suppliers, or innovation partners. Although the locations where these technologies originate exhibit a higher prevalence of technology job openings, this advantage diminishes over time as diffusion accelerates in wealthier and geographically closer countries and regions. The study highlights the significant role of firm-to-firm linkages in technology diffusion, with some linkages proving more influential than others. Firms that were previously buyers or innovation partners of establishments in technology-originating locations experienced faster growth in jobs related to these technologies. Moreover, relationships outside corporate boundaries play a particularly critical role, and these connections are influential beyond the factor of geographical distance.
Paulo Bastos, Jacob Greenspon, Katherine Stapleton and Daria Taglioni
This paper develops measures of the diffusion of a comprehensive range of low-carbon technologies in 35 countries from 2019 to 2022 using text analysis of job postings and earnings calls transcripts. It documents a rapid acceleration in the diffusion of low-carbon technologies in 2022. Rapid growth occurred in three quarters of the countries studied, although was fastest in Europe. Hiring for roles related to low-carbon technologies in these 35 countries doubled between the end of 2021 and end of 2022, for example. It studies the role of the global energy crisis in triggering this accelerated technology diffusion. It finds that countries that had a higher pre-crisis dependence on imports of natural gas or all energy sources, and were thus more exposed to the price shock, differentially increased hiring for low-carbon technology related roles from December 2021 onwards, with the differential increase in hiring peaking in the summer of 2022 at the same time as the peak in energy prices.
Katherine Stapleton & Michael Webb
Paper Media: VoxEU The Economist CEPR Podcast
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.
Beata Javorcik, Ben Kett, Katherine Stapleton and Layla O'Kane
Accepted at the Journal of the European Economic Association
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.
Beata Javorcik, Ben Kett, Katherine Stapleton and Layla O'Kane
Accepted at the Journal of International Economics
This paper uses data on the near universe of job adverts posted online in the US to study the impact of the 2018 trade war on US job opportunities. We develop measures of labor market exposure to three key channels of impact from the trade war: import protection for US producers, the higher cost of imported inputs for US producers, and exposure of US exporters to retaliatory tariffs. We find evidence that both tariffs on imported inputs and retaliatory tariffs led to a relative decline in online job postings in affected commuting zones. These effects were stronger for lower skilled postings than for higher skill postings. By contrast, we do not find any evidence of positive impacts of import protection on job openings. We estimate that the tariffs led to a combined effect of 175,000 fewer job postings in 2018, or 0.6 percent of the US total, with two thirds of this aggregate decline due to the imported input tariffs and one third due to retaliatory tariffs.
Alex Copestake, Max Marczinek, Ashley Pople & Katherine Stapleton
Paper Slides Media: The Economist IMF Research Perspectives
We document near-exponential growth in demand for artificial intelligence (AI)-related skills in India’s white-collar services sector since 2016, using a new dataset of online vacancies from India’s largest jobs website. We evaluate the impact of establishment-level demand for AI skills on the posting of non-AI positions in both the short term, using an event-study setup, and over the medium-term, using a shift-share design that exploits variation in exposure to new AI inventions. We find negative impacts of AI demand on posting of job adverts for non-AI positions and on non-AI wage offers. The effects are most pronounced in high-skilled, managerial and professional occupations, and for non-routine work, particularly complex analytical and communication tasks.
Katherine Stapleton & Layla O'Kane
Friedrich Bergmann & Katherine Stapleton