Network calibration and metamodeling of a financial accelerator agent based model
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Otros documentos de la autoría: Bargigli, Leonardo; RICCETTI, LUCA; Russo, Alberto; Gallegati, Mauro
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Network calibration and metamodeling of a financial accelerator agent based modelFecha de publicación
2020-03-13Editor
SpringerCita bibliográfica
Bargigli, L., Riccetti, L., Russo, A. et al. Network calibration and metamodeling of a financial accelerator agent based model. J Econ Interact Coord 15, 413–440 (2020). https://doi.org/10.1007/s11403-018-0217-8Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://link.springer.com/article/10.1007/s11403-018-0217-8Versión
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Resumen
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 ... [+]
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?”. [-]
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