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Prepared by Gerard Almekinders, Souvik Gupta, and Umang Rawat (all APD).
High-tech manufacturing includes chemicals and chemical products; pharmaceutical and biological products; computer, electronic and optical products; and electrical equipment. Modern services include information and communications; finance and insurance; and business services. Between 1980 and 2016, the combined share of hightech manufacturing and modern services sector increased from 25 percent of GDP to 40 percent of GDP.
They call a task routine “if it can be accomplished by machines following explicit programmed rules.” In contrast, nonroutine tasks are those “for which rules are not sufficiently well understood to be specified in computer code and executed by machines.”
Earlier literature has focused on technological change that increases the supply of some factor in efficiency units. In this formulation, skill-biased technological change exacerbates wage inequality if the elasticity of substitution (EOS) between low- and high-skill labor exceeds unity. Similarly, capital-augmenting technological progress lowers or raises labor’s share in national income depending on whether the EOS between capital and labor is above or below unity. IMF (2017a) finds that on average, the EOS for the aggregate economy is larger than one for advanced economies, while it is less than one for EMDEs. Sachs and Kotlikoff (2012) show that when the elasticity of substitution between robots and unskilled labor is sufficiently high, an improvement in robot productivity reduces the demand for unskilled workers. This results in lower investment in human capital and robots as well as reduced welfare of the current young generation and all future generations.
High skill jobs are defined as ISCO groups 1 (managers), 2 (professionals) and 3 (technicians and associate professionals); medium-skill jobs include ISCO groups 4 (clerks), 5 (service and sales workers), 6 (skilled agricultural and fishery workers), 7 (craft and related trade workers) and 8 (plant and machine operators and assemblers); and low-skill occupations consists of ISCO group 9 (elementary occupations).
Acemoglu and Restrepo (2016) consider the economic response to automation by accounting for the creation of new more complex tasks that only human labor can perform. The short- to medium-run impact on absolute labor demand is unclear in their model, but in the long run, labor’s share in national income returns to its original level. When labor is divided into high- and low-skill workers, the same restrictions ensure that the skill premium increases in the short run but not in the long run. In contrast, Berg and others (2017) analyze various variants of a model with automation and find robust finding that automation is good for growth, but bad for equality.