Income distribution is a fundamental aspect of economic systems, reflecting the distribution of resources within a society. Traditional economic models often assume simple distributions, such as the Gaussian distribution, which may not capture the complexity observed in real-world income distributions. It is based on this complexity that the integration of physics into the field of economics, using its appropriate tools. The field of economics offers a unique perspective by applying concepts from statistical physics and complex systems theory to the study of income distributions, with the aim of uncovering underlying mechanisms and emergent behaviors that can contribute to a deeper understanding of these distributions. The primary objective of this thesis is the development and analysis of a model of income distribution economy. Specifically, the model seeks to capture the dynamics of income generation, wealth accumulation and wealth exchange within a heterogeneous population of agents. Through simulation and analysis, we aim to understand how the individual ability to acquire wealth and achieve profitable exchanges affect the shape and stability of the income distribution of the entire population of such agents. This paper will begin with an overview of the theoretical foundations of economics and its relevance to the study of income distributions. Chapter 1 introduces us to network theory and its concepts and explains the model based on simulation through an agent wash. Chapter 2-3 will review the existing literature on income distributions in economics and finance, highlighting key findings and methodologies. Chapter 4 will introduce the proposed model of income distribution economics, detailing its assumptions, equations and computational implementation. Chapter 5 will present the results of simulations carried out with the model, exploring the effects of different parameters and scenarios on income distributions. Finally, Chapter 6 will conclude the thesis with a summary of key findings, limitations and recommendations for further study; it will discuss the implications of the findings, including potential policy insights and avenues for future research.
Δημήτριος Α. Αγρογίαννης (Wed,) studied this question.