Network calibration and metamodeling of a financial accelerator agent based model
We introduce a simple financially constrained production framework in which heterogeneous firms and banks maintain multiple credit connections. The parameters of credit market interaction are estimated from real data in order to reproduce a set of empirical regularities of the Japanese credit market. We then pursue the metamodeling approach, i.e. we derive a reduced form for a set of simulated moments \(h(\theta ,s)\) through the following steps: (1) we run agent-based simulations using an efficient sampling design of the parameter space \(\Theta \); (2) we employ the simulated data to estimate and then compare a number of alternative statistical metamodels. Then, using the best fitting metamodels, we study through sensitivity analysis the effects on h of variations in the components of \(\theta \in \Theta \). Finally, we employ the same approach to calibrate our agent-based model (ABM) with Japanese data. Notwithstanding the fact that our simple model is rejected by the evidence, we show th at metamodels can provide a methodologically robust answer to the question “does the ABM replicate empirical data?”.
We thank all the participants of the DISEI Department seminar of University of Florence held on November 17th 2015, the DISES Department seminar of Polytechnic University of Marche held on March 3rd 2016, the CEF2016 conference held on June 26–28 2016 in Bordeaux for their useful comments. A special thanks to Yoshi Fujiwara for providing the Japanese credit market data. All the usual disclaimers apply.
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