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Uncertainty and Sentiment-Driven Equilibria / Jess Benhabib, Pengfei Wang, Yi Wen.

By: Contributor(s): Material type: TextTextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w18878.Publication details: Cambridge, Mass. National Bureau of Economic Research 2013.Description: 1 online resource: illustrations (black and white)Subject(s): Online resources: Available additional physical forms:
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Abstract: We construct a model to capture the Keynesian idea that production and employment decisions are based on expectations of aggregate demand driven by sentiments, and that realized demand follows from the production and employment decisions of firms. We cast the Keynesian idea into a simple model with imperfect information about aggregate demand and we characterize the rational expectations equilibria of this model. We find that the equilibrium is not unique despite the absence of any non-convexities or strategic complementarity in the model. In addition to multiple fundamental equilibria, there can be serially correlated stochastic equilibria driven by self-fulfilling consumer sentiments. Furthermore, these sentiment-driven equilibria are not based on randomizations of the fundamental equilibria
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March 2013.

We construct a model to capture the Keynesian idea that production and employment decisions are based on expectations of aggregate demand driven by sentiments, and that realized demand follows from the production and employment decisions of firms. We cast the Keynesian idea into a simple model with imperfect information about aggregate demand and we characterize the rational expectations equilibria of this model. We find that the equilibrium is not unique despite the absence of any non-convexities or strategic complementarity in the model. In addition to multiple fundamental equilibria, there can be serially correlated stochastic equilibria driven by self-fulfilling consumer sentiments. Furthermore, these sentiment-driven equilibria are not based on randomizations of the fundamental equilibria

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