Endogenous Economic Resilience, Loss of Resilience, Persistent Cycles, Multiple Attractors, and Disruptive Contractions

Semmler, Willi; Della Rossa, Fabio; Orlando, Giuseppe; Rosario, Gabriel R. Padró; Koçkesen, Levent

doi:10.1007/16618_2023_76

Cited by 2 publications

(3 citation statements)

References 81 publications

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“…Higher dimensional models can also be studied where such thresholds exist, not as threshold points but as threshold surfaces. Moreover, existing work shows that the complex dynamics can generate steady states as a trapping region, as bad attractors, where the dynamics nearby can be trapped in a low-level equilibrium with features of persistent traps, as seen in Semmler et al (2023). They provide examples of this type arising from severe financial and climate disasters with extensive disruptions from normal business cycle dynamics, even for longer time periods.…”

Section: Discussionmentioning

confidence: 99%

“…The dynamics of the model of Equation (2) will be simulated below by choosing economically realistic parameters. For a more detailed discussion of the subsequent subsections, including the perturbation term, corridor stability cycles, and a limit cycle outside an asymptotically stable region, please refer to Semmler et al (2023).…”

Section: Analytical Model Variantsmentioning

confidence: 99%

“…There are, however, also factors such as resiliency destroyers that can undermine resilience and can lead to disruptive dynamics. In Semmler et al (2023), the theory of resilience is evaluated from the perspective of complex system dynamics across various time scales. Various model versions examine the concept of resilience as local resilience (corridor stability) and global resilience (global stability).…”

Section: Introductionmentioning

confidence: 99%

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Liquidity and Business Cycles—With Occasional Disruptions

Semmler,

Rosario,

Koçkesen

2023

Econometrics

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Some financial disruptions that started in California, U.S., in March 2023, resulting in the closure of several medium-size U.S. banks, shed new light on the role of liquidity in business cycle dynamics. In the normal path of the business cycle, liquidity and output mutually interact. Small shocks generally lead to mean reversion through market forces, as a low degree of liquidity dissipation does not significantly disrupt the economic dynamics. However, larger shocks and greater liquidity dissipation arising from runs on financial institutions and contagion effects can trigger tipping points, financial disruptions, and economic downturns. The latter poses severe challenges for Central Banks, which during normal times, usually maintain a hands-off approach with soft regulation and monitoring, allowing the market to operate. However, in severe times of liquidity dissipation, they must swiftly restore liquidity flows and rebuild trust in stability to avoid further disruptions and meltdowns. In this paper, we present a nonlinear model of the liquidity–macro interaction and econometrically explore those types of dynamic features with data from the U.S. economy. Guided by a theoretical model, we use nonlinear econometric methods of a Smooth Transition Regression type to study those features, which provide and suggest further regulation and monitoring guidelines and institutional enforcement of rules.

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Section: Discussionmentioning

confidence: 99%

Section: Analytical Model Variantsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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