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- Springer Journals
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- Copyright © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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- 1661-8289
- DOI
- 10.1007/s11786-022-00523-w
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Abstract
The slow recovery of many developed economies to the recent financial crisis, and the largest fall in aggregate demand since WWII caused by the COVID-19 Pandemic with its foreseeable negative and persistent effects on the aggregate supply, has generated renewed interest in the subject of hysteresis. The presence of significant hysteresis effects has important theoretical and policy implications. First, there is no unique and predetermined long-run equilibrium level of aggregate employment, as the equilibrium is permanently changed by temporary shocks. Second, as the economic system is not self-adjusting, substantial, timely, and sustained expansionary monetary and fiscal policy should be applied to mitigate the impact of shocks, including the temporary ones. Although it is not possible to quantify hysteresis effects in real time, we can use historical data to shed some light on the possible long-term economic consequences of the COVID-19 pandemic. For that purpose, we use the linear play-hysteresis model in the context of two equation system to analyses the join hysterical dynamics of aggregate employment and investment. We implement the model empirically by means of a new algorithm for the simultaneous equations system applied to Portuguese data that separates the effects of large and small changes in aggregate demand on aggregate employment and investment using an endogenous determined switching parameter as reference.
Journal
Mathematics in Computer Science – Springer Journals
Published: Mar 1, 2022
Keywords: Play hysteresis modeling; Computational mathematics; Switching regression; Employment; Investment; 62P20; 65C60; 91B02; 91B40; 91G70