Decentralized Markets in a Two-Sector Economy - An Agent Based Simulation

My work concerns the realization of two Agent-Based simulation Models (ABMs) of a two-sector economy, consisting of heterogeneous agents. The purpose is to develop a fist model of equilibrium good markets and compare it with a second one characterized by decentralized markets, and based upon a disequilibrium setting. In particular, we will assess simulation runs of both models with respect to the consistency of inferences from generated time series with the underlying model structure. The argumentation is structured as follows: In chapter one we will review some of the main methodological issues concerning economic modeling, inference, and the role of explanation in Economics. Moreover, we will critically review some features of Dynamic Stochastic General Equilibrium (DSGE) models and compare them with those proper of a disequilibrium framework, as defined by Franklin M. Fisher and Frank Hahn. In chapter two, insights from Behavioral Economics and Neuroeconomics are explored, in order to infer their possible implications for economic theory and modeling of agents' \emph{behavior}. We will then report the Making of the simulation model and describe how the two versions have been developed, by making use of the Swarm-Like Agent Protocol in Python (SLAPP). Chapter three is devoted to the development of version one, which is characterized by equilibrium good prices. Moreover, we will generalize version one by applying a variable-wage determination mechanism and allow for wage fluctuations. In chapter four, we describe version two, which consists of a pure disequilibrium model of the over mentioned economy. We explain differences with respect to version one and outline modeling choices for agent behavioral rules. After the description, model dynamics are outlined in chapter five and model outcome assessed and compared.