Demographics and Automation (as in Robots!)

From a new NBER Working Paper by Daron Acemoglu and Pascual Restrepo.

Abstract:

We argue theoretically and document empirically that aging leads to greater (industrial) automation, and in particular, to more intensive use and development of robots.  Using US data, we document that robots substitute for middle-aged workers (those between the ages of 36 and 55).  We then show that demographic change--corresponding to an increasing ratio of older to middle-aged workers--is associated with greater adoption of robots and other automation technologies across countries and with more robotics-related activities across US commuting zones.  We also provide evidence of more rapid development of automation technologies in countries undergoing greater demographic change.  Our directed technological change model further predicts that the induced adoption of automation technology should be more pronounced in industries that rely more on middle-aged workers and those that present greater opportunities for automation.  Both of these predictions receive support from country-industry variation in the adoption of robots.  Our model also implies that the productivity implications of aging are ambiguous when technology responds to demographic change, but we should expect productivity to increase and labor share to decline relatively in industries that are most amenable to automation, and this is indeed the pattern we find in the data. 

Gated NBER Working Paper #24421 available here. 

More on the automated economy from NBER

From a new NBER working paper, "Artificial Intelligence, Automation and Work,"  by Daron Acemoglu and Pascual Restrepo. 

Abstract:

We summarize a framework for the study of the implications of automation and AI on the demand for labor, wages, and employment.  Our task-based framework emphasizes the displacement effect that automation creates as machines and AI replace labor in tasks that it used to perform.  This displacement effect tends to reduce the demand for labor and wages.  But it is counteracted by a productivity effect, resulting from the cost savings generated by automation, which increase the demand for labor in non-automated tasks.  The productivity effect is complemented by additional capital accumulation and the deepening of automation (improvements of existing machinery), both of which further increase the demand for labor. These countervailing effects are incomplete.  Even when they are strong, automation increases output per worker more than wages and reduce the share of labor in national income.  The more powerful countervailing force against automation is the creation of new labor-intensive tasks, which reinstates labor in new activities and tends to increase the labor share to counterbalance the impact of automation.  Our framework also highlights the constraints and imperfections that slow down the adjustment of the economy and the labor market to automation and weaken the resulting productivity gains from this transformation:  a mismatch between the skill requirements of new technologies, and the possibility that automation is being introduced at an excessive rate, possibly at the expense of other productivity-enhancing technologies.

Fear the robots!

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