The Rise of the Machines: Automation, Horizontal Innovation and Income Inequality

Abstract

We construct an endogenous growth model of directed technical change with automation-the introduction of machines which replace low-skill labor and complement high-skill labor-and horizontal innovation-the introduction of new products, which increases demand for both types of labor. Machines are produced with the same technology as the consumption good. The level of technology in the economy is characterized by the number of products and the share of these that are automated. For general processes of technology, we demonstrate that although low-skill wages can drop during periods of increasing automation intensity the asymptotic growth rate is positive, though lower than that of the economy. We then endogenize the evolution of technology and derive an asymptotic steady state. Through numerical simulations, we show that the transitional path follows three phases. First, wages are low such that few machines are used and low-skill wages keep pace with the growth rate of the economy. Then, as wages grow the share of automated products increases and the economy substitutes towards the use of machines which depresses the growth rate of low-skill wages, potentially to negative. Finally, as the economy reaches steady state the share of automated products is constant and the relative growth rate of low-skill wages picks up though it remains lower than that of the economy. We extend the model to include middle-skill workers and demonstrate that the model endogenously captures two important characteristics of the U.S. income distribution over the past 50 years: initially a monotone dispersion of the income distribution, and thereafter a wage growth polarization, in which middle-skill workers experience the lowest wage growth. Finally, in an extension we allow machines to be produced with a different technology than the consumption good. This allows for faster productivity growth for machines which can potentially lead to permanently negative growth of low-skill wages.

Paul Romer: Ideas, Nonrivalry, and Endogenous Growth

“…Acemoglu et al (2012) consider environmental damage and study a world in which firms can invent "clean" or "dirty" technologies. Finally, Hemous and Olsen (2016) and Acemoglu and Restrepo (2018) study the effects of automation on economic growth, unemployment, and inequality.…”

A Multi-Factor Uzawa Growth Theorem And Endogenous Capital-Augmenting Technological Change

“…Separate from the accounting literate, models of economic growth with capital-augmenting technical change would be useful in the study of automation, artificial intelligence, and laborsaving technical change, topics that have recently received a great deal of attention in the growth literature (e.g., Benzell et al, 2015;Hémous and Olsen, 2016;McAfee, 2012, 2014).…”

Innovation and Top Income Inequality

“…8 In particular, Katz and Murphy (1992) and Goldin and Katz (2008) have shown that technical change has been skill-biased in the 20 th century. Acemoglu (1998Acemoglu ( , 2002Acemoglu ( and 2007 sees the skill distribution as determining the direction of technological change, while Hémous and Olsen (2014) argue that the incentive to automate low-skill tasks naturally increases as an economy develops. Several papers (Aghion and Howitt, 1997;Caselli, 1999;Galor and Moav, 2000) see General Purpose Technologies (GPT) as lying behind the increase in inequality, as the arrival of a GPT favors workers who adapt faster to the detriment of the rest of the population.…”

“…32 We chose to present the results only for the top 1% and for the instrument using the number of seats at the Senate. Adding the number of seats occupied at the House of Representative shows consistent results but decreases the first stage F stat.…”

“…We thus control for highways and also for the share of the federal military funding allocated to the various states. 32 As we have a long time series for each state, we are not concerned about 'short T ' bias in panel data IV. We apply instrumental variables estimator directly to equation (14).…”