Total factor productivity and signal noise volatility in an incomplete information setting
AbstractImperfection information models where agents solve some kind of signal extraction problem are multiplying and developing fast. They have commonly been used to study the impact of imperfect information on the business cycle and the importance of news versus noise shocks. This paper attempts to apply the framework to a di¤erent, albeit related, question: that of the e¤ect of volatility (both in news and noise) on the economy, from a long and short run perspective. An RBC model where the agent faces imperfect information regarding productivity is developed and calibrated in order to address the question, coming to the conclusion that the long run e¤ect is insigni cant while further development is required to address the short run conclusively.
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Bibliographic InfoPaper provided by Banco Central de Reserva del Perú in its series Working Papers with number 2010-014.
Date of creation: Dec 2010
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-01-16 (All new papers)
- NEP-CTA-2011-01-16 (Contract Theory & Applications)
- NEP-DGE-2011-01-16 (Dynamic General Equilibrium)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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