Abstract
This thesis develops an agent-based approach to macroeconomic modeling, focusing on the dynamics of labor and goods markets under different institutional arrangements. Rather than relying on the representative-agent assumption common to standard macro models, the analysis explicitly models heterogeneous agents interacting locally, allowing aggregate dynamics to emerge from the bottom up.
Applying insights from behavioral economics and search theory, the model analyzes how the economy responds to negative productivity shocks, and how local interaction structures shape the propagation and persistence of these shocks at the aggregate level.
Leveraging MultiVeStA — a Java-based tool for automated statistical analysis of agent-based models — the thesis identifies the emergence of self-sustaining shock resistance under certain parameters and conditions, offering a novel mechanism through which local heterogeneity can generate aggregate resilience.
Research Question
How do local interaction structures and agent heterogeneity in labor and goods markets shape the economy's aggregate response to negative productivity shocks?
Key Contributions
Methodology
Labor and goods markets are modeled with heterogeneous agents operating under different institutional arrangements, departing from the representative-agent assumption of standard macro models.
Agent decision rules incorporate insights from behavioral economics and search theory, improving the realism of matching and price-formation processes in the model.
Simulation outputs are analyzed using MultiVeStA, a Java-based statistical model-checking tool, enabling rigorous, automated analysis of how the economy responds to negative productivity shocks across parameter regimes.
Keywords
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