Total factor productivity and signal noise volatility in an incomplete information setting

Hugo Vega

No 2010-014, Working Papers from Banco Central de Reserva del Perú

Abstract: Imperfection 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.

Date: 2010-12
New Economics Papers: this item is included in nep-cta and nep-dge
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