had the same demographic trends as Germany, the gap in robot adoption between the two countries would be 50% smaller. This magnitude suggests, for instance, that if the U.S. A 10 percentage point increase in our aging variable is associated with 1.6 more robots per thousand workers-compared to the average increase of 3 robots per thousand workers observed during this period. Aging alone explains about 35% of the cross-country variation in robot adoption. We estimate a very similar pattern when we instrument demographic changes by past birthrates, thus purging aging from the response of immigration and emigration to technological changes and show that the relationship between demographic change and robot adoption is not mediated by and is robust to controlling for changes in educational attainment and female labour force participation.
These correlations are not driven by reverse causality or omitted characteristics (such as human capital or labour market institutions). We also confirm that, consistent with theoretical expectations, it is not past but current and future demographic changes that predict robot adoption. We first use country-level data on the stock of robots per thousand workers between 19 from the International Federation of Robotics (IFR) and document a strong and robust association between aging-measured as an increase in the ratio of workers above 56 to those between 21 and 55-and robot adoption. Our results point to a sizable impact of aging on the adoption of robots and other automation technologies. The bulk of the article investigates these predictions empirically. Aging-induced automation can also undo some of the adverse economic consequences of demographic change. 2 This effect is predicted to be particularly pronounced in industries that rely more on middle-aged workers and those that have greater technological opportunities for automation.
#History of automation scholar manual
We assume (and later empirically document) that middle-aged workers have a comparative advantage relative to older workers in manual production tasks, which require physical activity and dexterity, and document that demographic changes that reduce the ratio of middle-aged to older workers increase labour costs in production, and encourage the adoption and development of automation technologies. We start with a simple model of technology adoption and innovation to clarify how demographic change affects incentives to develop and use automation technologies. Rather, we document that this pattern reflects the response of firms to the relative scarcity of middle-aged workers, who typically perform manual production tasks and are being replaced by robots and industrial automation technologies. This is not because of automation in services in aging societies-our focus is on the manufacturing sector and industrial automation, and we do not find similar effects of aging on other technologies. In fact, aging alone accounts for close to a half of the cross-country variation in the adoption of robots and other automation technologies. In this article, we advance the hypothesis that the development and adoption of robots and other industrial automation technologies have received a big boost from demographic changes in several countries, most notably Germany, Japan, and South Korea. lags behind Germany and Japan in the production of robots-a single major producer of industrial robots is headquartered in the U.S., compared to six in each of Germany and Japan ( Leigh and Kraft, 2018). stands at 8.4 in 2014, while the same number is considerably higher in countries undergoing rapid demographic change, such as Japan (13.8), Germany (17.1), and South Korea (19.7). For example, the number of industrial robots per thousand industrial workers in the U.S. Indeed, automation technologies have made much greater inroads in countries with more rapidly-aging populations.
#History of automation scholar driver
Though there is undoubtedly some truth to this narrative, we argue that it ignores another powerful driver of automation: demographic change. The most common narrative sees automation as the natural next step in the technological developments based on the silicon chip (Brynjolfsson and McAfee, 2012). Brynjolfsson and McAfee, 2012 Ford, 2016 Graetz and Michaels, 2018 Acemoglu and Restrepo, 2020). Automation and robotics technologies are poised to transform the nature of production and work, and have already changed many aspects of modern manufacturing ( e.g.