Abstract
We extend sociodynamic modeling of the financial business cycle to the Euro Area andJapan. Using an opinion-formation model and machine learning techniques we find stable modelestimation of the financial business cycle using central bank lending surveys and a few selectedmacroeconomic variables. We find that banks have asymmetric response to good and bad economicinformation, and that banks adapt to their peers’ opinions when changing lending policies.
Highlights
In Post-Keynesian economic thought money is endogenously determined by economic activity in a modern economy: “loans create deposits” and “deposits generate reserves.” New money is created by lending and is destroyed when loans are paid back
We extend sociodynamic modeling of the financial business cycle to the Euro Area and Japan
Our analysis employs the opinionformation model introduced by Weidlich (1972) and later elaborated by Weidlich and Hagg (1983) with which the social psychology of economic agents can be included in the dynamics of economic incentives.† Our analysis develops earlier work on the sociodynamics of lending (Hawkins, 2011) through the use of simulation developed by Lux (1997, 2009a,b) and recently applied to the problem of lending opinion formation by Ghonghadze and Lux (2012, 2016)
Summary
In Post-Keynesian economic thought money is endogenously determined by economic activity in a modern economy: “loans create deposits” and “deposits generate reserves.” New money is created by lending and is destroyed when loans are paid back. Lenders interact within a social structure that has norms for group members’ common behaviors and network mechanisms controlling the flow of information They rely on other lenders to justify their economic actions and this gives rise to the phenomenon of “social embeddedness” in banking (Granovetter, 2005). In this paper we provide further evidence of the importance of social psychology in the generation of the financial business cycle in a capitalist economy by modeling the evolution of lending in terms of psychological and economic drivers that matter to bankers. The work of Ghonghadze and Lux (2016) is of particular interest as it demonstrates that a rich set of lending-opinion data – the Federal Reserve’s Senior Loan Officer Opinion Survey on Bank Lending Practices (SLOOS) – can be successfully incorporated into the opinion-formation model.
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