Learning and Macro-Economic Dynamics

Landini, Simone; Gallegati, Mauro; Stiglitz, Joseph E.; Li, Xihao; Guilmi, Corrado Di

doi:10.1007/978-3-319-07470-2_8

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…see Foley (1994), Aoki (1998Aoki ( , 2004, Lux (2008), Yoshikawa (2011), Landini, Gallegati, andStiglitz (2014a), Landini, Gallegati, Stiglitz, Li, and Di Guilmi (2014b), among others. This type of work considers the state of the system from meso-level, and derives the dynamics of the system by depicting the transition rate with technique such as FokkerPlanck equation or master equation, which refers to an implicit application of the concept of transition matrix to depict the structural change on meso-level.…”

Section: Related Literaturementioning

confidence: 98%

Stock-Flow Dynamic Projection

Gallegati

2015

SSRN Journal

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Borrowing from our experience in agent-based computational economic research from 'bottom-up', this paper considers economic system as multilevel dynamical system that micro-level agents' interaction leads to structural transition in meso-level, which results in macro-level market dynamics with endogenous fluctuation or even market crashes. By the concept of transition matrix, we develop technique to quantify meso-level structural change induced by micro-level interaction. Then we apply this quantification to propose the method of dynamic projection that delivers outof-sample forecast of macro-level economic variable from micro-level big data. We testify this method with a data set of financial statements for 4599 firms listed in Tokyo Stock Exchange for the year of 1980 to 2012. The Diebold-Mariano test indicates that the dynamic projection has significantly higher accuracy for one-period-ahead out-of-sample forecast than the benchmark of ARIMA models.

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