The economic impact of autonomous technologies and a model for the circular economy
Authors:   , Casas-Aljama Pablo 
Published: February 2024

This dissertation offers a comprehensive analysis of the wide-ranging economic implications and labour market consequences of autonomous technologies, while also considering the role of the circular economy in sustaining economic growth. Spanning three thematic areas across nine self-contained essays, the research provides a combination of macroeconomic modelling and microeconomic evidence. The thesis is divided into three main parts, leaving aside the introduction and the concluding remarks. The first part focuses on macroeconomic theoretical modelling of a dual traditional-autonomous economy, employing dynamic general equilibrium models to evaluate the impact of autonomous technologies on the economy. The second part provides microeconomic evidence regarding the influence of autonomous technologies on labour markets. Finally, the third part presents a novel perspective on the integration of circular economy concepts into a neoclassical dynamic general equilibrium model. The thesis initiates its exploration through the lens of a dual traditional-autonomous economy model to study the economic implications of automation, discovering that the effects are largely determined by the adoption rate of autonomous capital and its elasticity of substitution with traditional technology. A significant finding suggests the existence of an adoption rate threshold, beyond which the process of automation can lead to a complete shift from traditional capital and labour. Furthermore, the study uncovers the necessity for a profound reform of current tax systems by observing a reduction in the government’s size due to the substitution of traditional tax-bearing inputs with autonomous technology. Further exploration into the optimal tax policy for maintaining the social security contributions to GDP ratio by taxing autonomous capital suggests that a robots’ social security tax paid by employers of autonomous capital is the most efficient long-term strategy. The dissertation then pivots to provide microeconomic evidence, examining the impact of digitalization on labour markets, using data from the US and European countries. The research provides a view of the effects of digitalization on the US employment landscape, presenting mappings that classify occupations based on their relationship with automation and AI. The study also investigates the implications of the automation process and AI on early retirement decisions across 26 European countries, revealing a significant role of technological change in these decisions. Moreover, this part analyses the role of computerization, AI, machine learning, and occupational reorganization capacity in unemployment probabilities among older workers, indicating the heterogeneity in the impact of new technologies on the labour market. Finally, this section explores the implications of digitalization for worker mobility, illustrating a significant influence on the relocation of displaced workers. Finally, the thesis presents a novel mathematical description of a circular economy by incorporating the concept into a neoclassical dynamic general equilibrium linear economy model. The study reveals a positive S-shaped relationship between the optimal recycling rate and economic development, concluding that increasing the circularity of the economy is a necessary condition for enhancing social welfare in a growing economy. Overall, the dissertation presents a comprehensive examination of the broad economic impacts of autonomous technologies, while introducing the concept of the circular economy into macroeconomic modelling. The findings have important implications for policy-making, contributing to a better understanding of the technology-driven economic changes.