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

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  • Vega, Hugo

    (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.

Suggested Citation

  • Vega, Hugo, 2010. "Total factor productivity and signal noise volatility in an incomplete information setting," Working Papers 2010-014, Banco Central de Reserva del Perú.
    • Handle: RePEc:rbp:wpaper:2010-014
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    References listed on IDEAS

    as
    1. Collard, Fabrice & Dellas, Harris & Smets, Frank, 2009. "Imperfect information and the business cycle," Journal of Monetary Economics, Elsevier, vol. 56(S), pages 38-56.
    2. Olivier J. Blanchard & Jean-Paul L'Huillier & Guido Lorenzoni, 2013. "News, Noise, and Fluctuations: An Empirical Exploration," American Economic Review, American Economic Association, vol. 103(7), pages 3045-3070, December.
    3. Guido Lorenzoni, 2009. "A Theory of Demand Shocks," American Economic Review, American Economic Association, vol. 99(5), pages 2050-2084, December.
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