One theoretically plausible aspect of the technological innovation in terms of human capital effects is the expected impact of technology on demand for (and therefore supply of) different occupations. For example, we know that technology can act as a complement to or a substitute for labour.
In the former case, we can expect advancement of technology to create more jobs that are closely linked to enhancing technological innovation, deployment and productivity. In other words, we can expect more geeks. And we can expect – given lags in education and training – that as demand for geeks rises, their wages will rise in the short run before falling rather rapidly in the longer term.
In the latter case, there is a bit less certain, however. Yes, technology’s primary objective is to lower costs of production and increase value added. As a result, it is going to displace vast numbers of workers who can be substituted for via technological innovation. However, not all substitutable workers are made of the same cloth and not all technological innovation is capable of achieving unambiguous returns on investment necessary to sustain it. Take, for example, an expensive robot that costs, say, USD 600.000 a pop, but can only replace 3 lower skilled workers in a laundromat, earning USD16,000 per annum. So with benefits etc factored in, the cost of these 3 workers will be around USD70,000 per annum. It makes absolutely zero sense to replace these workers with new tech at least any time before the tech systems become fully self-replicating and extremely cheap. So, for really lower skills distributions, we can expect that jobs displacement by technology is unlikely to materialise soon. But for mid-range wages, consistent with mid-range skills, there is a stronger case for jobs displacement.
Liquidity moves markets!Click here to learn how you can follow the money.
All of which suggests that we are likely to see a U-shaped polarisation process arising when it comes to jobs distribution across the skills segments: higher wage segment rising in total share of employment, as complementarity effects drive jobs creation here; and the lower wage segment also rising in total employment, as robots-induced increase in value added across the economy translates into greater demand for low-skills jobs that cannot be efficiently displaced by technology, yet. In the middle, however, we are likely to witness a cratering of employment. Here, the workers are neither complementary to robots, nor are they earning low enough wages to make expensive robots non-viable as a replacement alternative for labour.
Interestingly, we are already witnessing this trend. In fact, we have been witnessing it since the early 1990s. For example, Harrigan, James and Reshef, Ariell and Toubal, Farid paper titled “The March of the Techies: Technology, Trade, and Job Polarization in France, 1994-2007”, published March 2016, by NBER (NBER Working Paper No. w22110: http://ssrn.com/abstract=2755382) looked into “employee-firm-level data on the entire private sector from 1994 to 2007” in France.
The authors “show that the labor market in France has polarised: employment shares of high and low wage occupations have grown, while middle wage occupations have shrunk.” So the story is consistent with an emerging U-shaped labour market response to technological innovation on the extensive margin (in headcount terms). And more, the authors also find that inside margin also polarised, as “…the share of hours worked in technology-related occupations (“techies”) grew substantially, as did imports and exports.”
However, the authors also look at a deeper relationship between technology and jobs polarisation. In fact, they find that, causally, “polarisation occurred within firms”, but that effect was “…mostly due to changes in the composition of firms (between firms). [And] …firms with more techies in 2002 saw greater polarization, and grew faster, from 2002 to 2007. Offshoring reduced employment growth. Among blue-collar workers in manufacturing, importing caused skill upgrading while exporting caused skill downgrading.”