Efectos de la automatización en el empleo en Chile

Tiare Rivera

doi:10.4067/S0718-88702019000100003

Authors

Tiare Rivera Universidad Alberto Hurtado

DOI:

https://doi.org/10.4067/S0718-88702019000100003

Keywords:

Automation, labor, jobs, technology, robots, productivity

Abstract

This paper analyzes the effects of new technologies oriented to automation in the Chilean labor market. A general equilibrium model is used, in which the investment in robotic capital and the investment in traditional capital are considered separately, allowing the study of the effects of complementarity and substitution that are verified in relation to the labor factor. In particular, the model treats robotic capital as a direct substitute for labor, while incorporating traditional capital as complementary to it. By subjecting the economy to shocks in robotic capital prices, the effects on consumption, employment, wages and GDP can be studied. The results indicate that a fall in the international purchase price of robotic capital has a negative impact on employment as well as on the product. The exercises carried out in this study indicate that a decrease in the international price of robotic capital by 1%, under conditions of high replacement rates between employment and robots, produces a drop in employment and wages of 0.05% if the change is transitory and of 0.25% if it is permanent due to an increase in imports of robotic capital.

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References

Acemoglu, D., & Restrepo, P. (2017). Robots and jobs: Evidence from US labor markets (NBER Working Paper). National Bureau of Economic Research.

Acemoglu, D., & Restrepo, P. (2018a). Artificial intelligence, automation and work (Working Paper). National Bureau of Economic Research. https://doi.org/10.7208/chicago/9780226613475.003.0008

Acemoglu, D., & Restrepo, P. (2018c). Demographics and automation [Informe técnico]. National Bureau of Economic Research.

Acemoglu, D., & Restrepo, P. (2018d). Low-skill and high-skill automation. Journal of Human Capital, 12(2), 204–232. https://doi.org/10.1086/697242

Aghion, P., Jones, B. F., & Jones, C. I. (2017). Artificial intelligence and economic growth [Informe técnico]. National Bureau of Economic Research.

Almeida, R., Fernandes, A. M., Viollaz, M., & Almeida, R. K. (2017). Does the adoption of complex software impact employment composition and the skill content of occupations? Evidence from Chilean firms. World Bank.

Alvarez, R. (2016). The impact of R&D and ICT investment on innovation and productivity in Chilean firms [Informe técnico]. Inter-American Development Bank.

Benavente, J. M., Bravo, D., & Montero, R. (2011). Wages and workplace computer use in Chile. The Developing Economies, 49(4), 382–403. https://doi.org/10.1111/j.1746-1049.2011.00144.x

Berg, A., Buffie, E. F., & Zanna, L.-F. (2018). Should we fear the robot revolution? (The correct answer is yes) (IMF Working Paper). International Monetary Fund.

Bravo, J., Garcia, M. A., & Schlechter, H. (2018). Automatización e inteligencia artificial, desafíos del mercado laboral [Automation and artificial intelligence, labor market challenges] [Informe técnico]. CLAPES UC.

Brussevich, M., Dabla-Norris, E., Kamunge, C., Karnane, P., Khalid, S., & Kochhar, K. (2018). Gender, technology and the future of work (IMF Staff Discussion Note). International Monetary Fund.

Brynjolfsson, E., & McAfee, A. (2012). Race against the machine: How the digital revolution is accelerating innovation, driving productivity, and irreversibly transforming employment and the economy. Brynjolfsson and McAfee.

Brynjolfsson, E., Mitchell, T., & Rock, D. (2018). What can machines learn, and what does it mean for occupations and the economy? AEA Papers and Proceedings, 108, 43–47.

Carrillo, F. (2018). Formación de competencias para el trabajo en Chile [Skills training for work in Chile] [Informe técnico]. Comisión Nacional de Productividad.

Comin, D., & Gertler, M. (2006). Medium-term business cycles. American Economic Review, 96(3), 523–551. https://doi.org/10.1257/aer.96.3.523

Correia, I., Neves, J. C., & Rebelo, S. (1995). Business cycles in a small open economy. European Economic Review, 39(6), 1089–1113. https://doi.org/10.1016/0014-2921(94)00105-9

David, H., & Dorn, D. (2013). The growth of low-skill service jobs and the polarization of the US labor market. American Economic Review, 103, 1553–1597.

Eden, M., & Gaggl, P. (2015). On the welfare implications of automation. World Bank.

Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280.

Lin, T. T., & Weise, C. L. (2018). A New Keynesian model with robots: Implications for business cycles and monetary policy (SSRN Working Paper N.º 3064229). Social Science Research Network.

Manyika, J. (2017). A future that works: AI, automation, employment, and productivity [Informe técnico]. McKinsey Global Institute.

Paiva, O. A., & Prevedello, L. M. (2017). The potential impact of artificial intelligence in radiology. Radiologia Brasileira, 50(5), V–VI. https://doi.org/10.1590/0100-3984.2017.50.5e1

Peralta-Alva, A., & Agustin, R. (2018). Technology and the future of work (IMF Working Paper N.º WP/18/207). International Monetary Fund.

PwC. (2018). The macroeconomic impact of artificial intelligence. PricewaterhouseCoopers.

Rojas, A. (1997). Descomposicion del diferencial de tasas de interes entre Chile y el extranjero: 1992 a 1996 [Decomposition of the interest rate differential between Chile and abroad: 1992 to 1996] (Documento de Trabajo). Banco Central de Chile.

Salehi, H., & Burgueño, R. (2018). Emerging artificial intelligence methods in structural engineering. Engineering Structures, 171, 170–189. https://doi.org/10.1016/j.engstruct.2018.05.084

Zeira, J. (1998). Workers, machines, and economic growth. The Quarterly Journal of Economics, 113(4), 1091–1117. https://doi.org/10.1162/003355398555847