Determinants of employment maintenance in times of Industry 4.0: the case of agriculture in Brazil

Abstract

The advent of information and communication technologies can lead to imbalances between labor supply and demand. Recent studies indicate that in Brazil, one of the sectors most likely to be affected by automation processes is agriculture. The objective is to investigate the factors that influence job retention in the agricultural sector, introducing an innovative explanatory factor: the probabilities of automation associated with different occupations, as proposed by Frey & Osborne (2013) and adapted to the Brazilian labor market by Lima et al. (2019). Our analysis used data from RAIS 2019. The results highlight that seniority and remuneration have a positive impact on the probability of an individual remaining employed. However, workers in occupations with a high probability of automation face an expected probability 6.66% lower to retain their jobs compared to those in low-probability automation occupations. Additionally, individuals with a degree have an 11.21% higher probability of maintaining employment compared to those with only a fundamental education. It is concluded that the estimates reinforce the need for investments in professional qualifications to provide workers with skills aligned with the contemporary agricultural needs.

Keywords:
logistic regression; Industry 4.0; job retention; automation