August 17, 2023 - Written By Tim Hatton | Blog Archive
If we want not just productivity, but widely shared productivity, we need to have robots in places where right now they’re not as common.
Erik Brynjolfsson – Director, Stanford Digital Economy Lab
Laying the foundation
The researchers’ findings weren’t limited to solely identifying robot hubs, though. Data from the ASM also included information on the size and age of surveyed establishments and their workforces.
From this data, the researchers found that higher robotics use correlated with higher capital expenditures, particularly in information technology. The research suggests that companies willing to pay the price for robots are also more likely to spend more on other innovations and improvements, leading to enhanced automation and digitalization.
That kind of investment creates a spillover effect throughout surrounding local economies, just like the manufacturing output of the robots does. If the use and integration of robots creates better economic outcomes, then a stark divide between robot hubs and everywhere else could challenge overall growth.
Brynjolfsson raises this possible divide as a legitimate concern. “Having robots so concentrated could lead to a separation, where some manufacturing becomes much more high-tech and robust, and other parts get left behind—so it’s valuable to understand what drives the adoption and, ultimately, the diffusion of robots,” he said. “If we want not just productivity, but widely shared productivity, we need to have robots in places where right now they’re not as common.”
Understanding why companies are adopting robots in certain areas and not others will help guide future development throughout the manufacturing industry. Researchers, data agencies, policymakers, and industry stakeholders can all leverage the paper’s insights to work toward a more balanced and inclusive deployment of robotics.
The research team realizes that their work is just the beginning of a long line of research into understanding the impact of robotics in manufacturing. The authors propose several avenues that future researchers could pursue—one looks into the relationship between robot hubs and international trade, while another explores the link between robot adoption and other investments. “Our hope is that the patterns in the data that we document in our paper spark further research in this area that is of use to scholars, practitioners, and policymakers,” the researchers wrote.
Future researchers can also better understand the advantages and obstacles of robotics in manufacturing by examining the influence of robots on productivity and wages in manufacturing establishments. A more collaborative environment will make it easier to enable economic growth and tech advancement in the manufacturing sector—and beyond.
“Our examination of the cross-sectional data indicates that robot adoption is positively associated with the share of production workers but negatively associated with earnings per worker,” said Li. “However, what we can say about causality and the mechanism behind our findings is still limited without longitudinal data and exogenous shocks. I expect that as new waves of survey data become accessible, there will be an increase in research exploring the impact of robots on the US manufacturing sector.”
Any opinions and conclusions expressed herein are those of the authors and do not represent the views of the U.S. Census Bureau. Disclosure review numbers CBDRB-FY22-ESMD011-003, CBDRB-FY23-ESMD011-003, CBDRB-FY22-192, and CBDRB-FY23-ESMD011-004 (DMS# 7508509). We are grateful to the Hewlett Foundation, Kauffman Foundation, National Science Foundation, Stanford Digital Economy Lab and Tides Foundation for generous funding. We thank Jim Bessen, participants at the 2023 AEA Annual Meeting, and Emin Dinlersoz for valuable comments and feedback. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
The authors are grateful to the Hewlett Foundation, Kauffman Foundation, Markle Foundation, National Science Foundation, Stanford Digital Economy Lab, and Tides Foundation for generous funding.