Robots, Human Capital Investment, Welfare, and Unemployment in a Digital World Economy

Karl Farmer and Matthias Schelnast
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Matthias Schelnast: University of Graz

Chapter 10 in Growth and International Trade, 2021, pp 223-255 from Springer

Abstract: Abstract Intelligent machines (robots) might have vastly destructive consequences for future human welfare and employment. Following Frey and Osborn (The future of employment: How susceptible are jobs to computerization? University of Oxford, 2013), popular media predict that during the next 10 to 20 years, 50% and more of contemporary human jobs will be replaced by robots. Thus, it is natural to ask the question of whether investments in human capital can ameliorate the threatening loss of jobs involving even middle- and high-skilled tasks. Policy advisors mainly recommend public expenditures in order to foster digital competences among the population. However, there might also be an avenue for more traditional human capital investments by individuals and governments. Capital investments in a broader range of human activities than only digital competences might namely ameliorate the rivalry between traditional and digital production in Sachs et al.’s (Robots: Curse or blessing: A basic framework, 2015) overlapping generations (OLG) model. The model focuses on an economy in which final goods are produced by machines without human labor (robots) and by human labor and traditional capital. One key finding is “that an increase in robotic productivity will temporarily raise output, but, by lowering the demand for labor, can lower wages and consumption in the long run. In what we term a paradox of robotic productivity (italics in original), innovations that increase the productivity of robotic investment can, after a generation, lower robotic and total output, and lower the well-being (lifetime utility) of all future generations” (Sachs et al., Robots: Curse or blessing: A basic framework, 2015, 1). Young households in the OLG economy of Sachs et al. (Robots: Curse or blessing: A basic framework, 2015) invest their savings either in robots or traditional capital but nobody invests in human capital. Thus, it remains as the first open question whether Sachs et al.’s (Robots: Curse or blessing: A basic framework, 2015) negative long-run welfare consequences of digitalization also arise when the government as an agent of young households invests in human capital with the aim to counteract the decrease in labor productivity resulting from the substitution of robots for traditional capital. Second. Sachs et al. (Robots: Curse or blessing: A basic framework, 2015) assume full employment while many fear unemployment as a consequence of more productive robots. Thus, the second question is whether robots raise or diminish existing unemployment. The chapter answers both questions by extending the OLG model of Sachs et al. (Robots: Curse or blessing: A basic framework, 2015) through human capital accumulation in line with Glomm and Ravikumar (Journal of Political Economy, 100, 818–834, 1992) and involuntary unemployment in accordance with Magnani (The Solow growth model revisited. Introducing Keynesian involuntary unemployment, 2015). It will be shown which basic model parameters are conducive for beneficial or immiserizing technological change and whether more productive robots will raise or decrease involuntary unemployment.

Keywords: Robots; Human capital; Welfare; Involuntary unemployment; Digital OLG model (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/978-3-662-62943-7_10

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