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Is the Covid-19 Pandemic Fast-Tracking Automation in Developing Countries? Evidence from Colombia


  • Leonardo Bonilla-Mejía
  • Luz A. Flórez
  • Didier Hermida
  • Francisco Lasso-Valderrama
  • Leonardo Fabio Morales
  • Juan J. Ospina-Tejeiro
  • José Pulido


This paper assesses whether the Covid-19 pandemic accelerated automation in developing countries. We studied the case of Colombia, a country with low R&D and productivity and with high labor informality and unemployment. We estimated event-study models to assess the differential effect of the pandemic on job openings and salaried employment by the potential degree of automation of each occupation. Our results suggest that both vacancies and salaried employment fell more in highly automatable occupations during the pandemic and have since experienced a slower recovery. The effect of the pandemic on automation is mostly driven by sectors that were affected by mobility restrictions. We also found heterogeneous effects by age and gender. The acceleration of automation is mainly affecting the labor market for females and individuals over the age of 40. Finally, we explored the differential effect on occupations with wages around the minimum wage. We found that occupations with wages close to the minimum wage exhibit the highest effect, especially at the onset of the pandemic. **** RESUMEN: Este documento evalúa si la pandemia del Covid-19 aceleró el proceso de automatización en países en desarrollo. El estudio se enfoca en Colombia, un país con baja inversión en Investigación y Desarrollo (I&D), baja productividad, además de una alta informalidad laboral y desempleo. Se estima un modelo de estudio de eventos para evaluar si durante la pandemia se presentó un efecto diferencial en la demanda laboral de acuerdo al grado potencial de automatización de las ocupaciones. Nuestros resultados sugieren que, durante la pandemia, tanto las vacantes como el nivel de empleo asalariado cayeron más en ocupaciones con alto potencial de automatización y, desde entonces, han presentado una recuperación mucho más lenta. Este efecto se ha observado principalmente en los sectores que se vieron afectados por las restricciones de movilidad. Igualmente encontramos efectos heterogéneos por edad y género, donde el mercado laboral de las mujeres y los individuos mayores de 40 años han sido los más afectados. Finalmente, exploramos el efecto diferencial en las ocupaciones con salarios alrededor del salario mínimo; los resultados indican que las ocupaciones con salarios más cerca al salario mínimo son las más afectadas, especialmente al inicio de la pandemia.

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  • Leonardo Bonilla-Mejía & Luz A. Flórez & Didier Hermida & Francisco Lasso-Valderrama & Leonardo Fabio Morales & Juan J. Ospina-Tejeiro & José Pulido, 2022. "Is the Covid-19 Pandemic Fast-Tracking Automation in Developing Countries? Evidence from Colombia," Borradores de Economia 1209, Banco de la Republica de Colombia.
  • Handle: RePEc:bdr:borrec:1209
    DOI: 10.32468/be.1209

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    More about this item


    Automation; pandemic Covid-19; vacancies; employment; Automatización; pandemia Covid-19; vacantes y empleo.;
    All these keywords.

    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • J60 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - General

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