Understanding Automation’s Impact on Ecological Footprint: Theory and Empirical Evidence from Europe

As technological advancements continue to unfold, automation has emerged as a pivotal force in reshaping both production paradigms and lifestyles. This paper introduces a comprehensive general equilibrium framework that encapsulates both automation and ecological environment. Through comparative static analysis, it seeks to elucidate the influence of automation on the environment. Furthermore, employing 32 European nations from 2000 to 2019 as samples, this research empirically investigates the propositions using panel least squares regression alongside panel threshold regression methods. In addition, this study employs predictions generated by an LSTM model using data from 1993 to 1999 as instrumental variables to address endogeneity. The findings reveal two opposing impacts of automation on the environment: the Leisure Effect, which worsens ecological degradation, and the Conservation Effect, which improves environmental quality. When environmental awareness is high, the Conservation Effect dominates, significantly reducing the ecological footprint. Moreover, as automation technology level advances, its capacity to curtail the ecological footprint intensifies. Specifically, from the perspective of the full sample, the addition of one robot per thousand workers leads to a 0.13 unit reduction in the natural logarithm of ecological footprint; meanwhile, the suppressive effect varies by approximately 3 to 10 times before and after reaching certain thresholds of environmental awareness and technological advancement behind automation. Subsequent grouped regression analysis further elucidates that within European contexts, automation’s footprint-reducing effects are predominantly observed in nations with GDP per capita below $20,000, advanced digitalization, lower environmental dependence, reduced military spending, and strong government intervention.