Essays on labor-substituting technologies

This thesis studies the effects of automation, artificial intelligence (AI) and robotics technologies on the capital-labor elasticity of substitution over time and in the presence of intellectual property products (IPPs) on the one hand and the news industry’s view on the relative potentials of these labor-substituting technologies on the other hand. The first chapter investigates two questions for the US manufacturing sector: first, have the estimates of the capital-labor elasticity of substitution changed over time? And second, how does capitalizing intellectual property products (IPPs) effect the estimates of the capital-labor elasticity of substitution? Using the data on input and output quantities and prices from the NBER-CES Database between 1958 and 2007, I estimated a normalized supply-side system of equations allowing for variation over time in the capital-labor elasticity of substitution. I found that capital and labor are gross-substitute and the estimates display a positive long-run linear trend, unconditional on capitalizing IPPs. Furthermore, I found there is no long-term equilibrium relationship between the user’s cost of capital and the capital output ratio. Both labor-augmenting and capital-augmenting technological change co-exist, with the former being sustainable in the long-run. The second chapter, extends the investigation of the time-trend of the capital-labor elasticity of substitution into the US non-manufacturing sectors. The central question here is whether the effects of labor-substituting technologies on the easiness to substitute labor for capital over time is different across non-manufacturing sectors. Using the data mainly from the Bureau of Economic Analysis (BEA) for the period going from 1955 to 2015, I found that the capital-labor elasticity of substitution does have a heterogeneous long-run time trend across US non-manufacturing sectors. This result, with the existing evidence on the sectoral heterogeneity of the effects of labor-substituting innovations suggests that sectors with the highest levels of penetration of automation technologies have experienced an increase in their easiness to substitute labor for capital whereas those with a high level of new created tasks where humans have comparative advantage, have experienced a decrease in their easiness to substitute labor for capital. With regards to the effects of IPPs capitalization, two results emerged: IPPs capitalization does not reverse the trend in the labor share of value-added in any sector while leaving the nature and the trend of the easiness to substitute labor for capital for the majority of sectors unaltered. The third chapter investigates how the news industry perceives the potentials of AI and robotics technologies. From a well defined set of articles in The New York Times archive, I constructed an index of the news industry tone on AI and robotics potentials, from 1980 to 2020. Firstly, the index displays a decreasing trend overtime, suggesting the existence of irrational exuberance in the valuation of labor-substituting technologies’ relative potentials. Secondly, for comparison purposes, I found that a similar tone index for the microprocessor technology displays an upwards trend during the same period. This points to an upwards updating of the valuation of the potentials of the microprocessor discovery in contrary to AI and robotics technologies. Finally, I found that the constructed news tone index on AI and robotics is correlated with the investment flow from venture capital going to AI and robotics projects in the US.