November 2021. With Max Sina Knicker, Michael Benzaquen and Jean-Philippe Bouchaud
Note: Agent-Based Models (ABM) are computational scenario-generators, which can be used to predict the possible future outcomes of the complex system they represent. To better understand the robustness of these predictions, it is necessary to understand the full scope of the possible phenomena the model can generate. Most often, due to high-dimensional parameter spaces, this is a computationally expensive task. Inspired by ideas coming from systems biology, we show that for multiple macroeconomic models, including an agent-based model and several Dynamic Stochastic General Equilibrium (DSGE) models, there are only a few stiff parameter combinations that have strong effects, while the other sloppy directions are irrelevant. This suggest an algorithm that efficiently explores the space of parameters by primarily moving along the stiff directions. We apply our algorithm to a medium-sized agent-based model, and show that it recovers all possible dynamics of the unemployment rate. The application of this method to Agent-based Models may lead to a more thorough and robust understanding of their features, and provide enhanced parameter sensitivity analyses. Several promising paths for future research are discussed.
September 2021. With Michael Benzaquen, Dimitri Kroujiline, and Maxim Gusev
Note: We build a model of capital demand that captures bi-stable behaviors across business cycle timescales. The model has two attracting equilibria (contraction & expansion). This gives rise to quasi-periodic fluctuations, characterized by prolonged entrapment in an equilibrium with by rapid alternations between them. The underlying endogenous mechanism is a coherence resonance phenomenon. While the fluctuations can cause substantial excursions from the equilibrium growth path, such deviations vanish in the long run as supply and demand converge.
September 2021. With Federico Morelli, Michael Benzaquen, Marco Tarzi, Jean-Philippe Bouchaud
Note: In this work, we develop a multi-equilibrium behavioral business cycle model that accounts for demand or supply collapses due to abrupt drops in consumer confidence. Four qualitatively different outcomes can emerge, characterised by the frequency of capital scarcity and/or demand crises. In the absence of policy measures, the duration of such crises can increase by orders of magnitude when parameters are varied, as a result of the ``paradox of thrift''.