Innovation and Employment: An Agent-Based Approach
Authored by Fabio Neves, Pedro Campos, Sandra Silva
Date Published: 2019
DOI: 10.18564/jasss.3933
Sponsors:
No sponsors listed
Platforms:
Python
Mesa
Model Documentation:
ODD
Mathematical description
Model Code URLs:
http://jasss.soc.surrey.ac.uk/22/1/8.html#appendixb
Abstract
While the effects of innovation on employment have been a controversial
issue in economic literature for several years, this economic puzzle is
particularly relevant nowadays. We are witnessing tremendous
technological developments which threaten to disrupt the labour market,
due to their potential for significantly automating human labour. As
such, this paper presents a qualitative study of the dynamics underlying
the relationship between innovation and employment, using an agent-based
model developed in Python. The model represents an economy populated by
firms able to perform either Product Innovation (leading to the
discovery of new tasks, which require human labour) or Process
Innovation (leading to the automation of tasks previously performed by
humans). The analysis led to three major conclusions, valid in this
context. The first takeaway is that the Employment Rate in a given
economy is dependent on the automation potential of the tasks in that
economy and dependent on the type of innovation performed by firms in
that economy (with Product Innovation having a positive effect on
employment and Process Innovation having a negative effect). Second, in
any given economy, if firms' propensity for product and process
innovation, as well as the automation potential of their tasks are
stable over time, the Employment Rate in that economy will tend towards
stability over time. The third conclusion is that higher levels of
Process Innovation and lower levels of Product Innovation, lead to a
more intense decline of wage shares and to a wider gap between employee
productivity growth and wage growth.
Tags
Agent-based model
Innovation
evolutionary model
Employment
growth
Needs
Automation