Website: https://www.katherinestapleton.co/
Abstract
Firm Networks and Global Technology
Diffusion (with Paulo Bastos, Daria Taglioni, Hannah Wei)
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.
Automation, Trade and Multinational Activity: Micro Evidence from Spain (with 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.
Paper 2: https://drive.google.com/file/d/1gMoROdXvWWqDIxjXmk_hIYIahFDRHNGl/view
Did the 2022 Energy Crisis Accelerate the Diffusion of Low-carbon Technologies? (with Paulo Bastos, Jacob Greenspon, 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.
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