Murray, James (2011): Learning and judgment shocks in U.S. business cycles.
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This paper examines the role of judgment shocks in combination with other structural shocks in explaining post-war economic volatility within the context of a New Keynesian model. Agents form expectations using constant gain learning then augment these forecasts with judgment. These judgments may be interpreted as a reaction to current news stories or policy announcements that would influence people's expectations. I allow for the possibility that these judgments be informatively based on information about structural shocks, but judgment itself may also be subject to its own stochastic shocks. I estimate a standard New Keynesian model that includes these shocks using Bayesian simulation methods. To aid in identifying expectational shocks from other structural shocks I include data on professional forecasts along with data on output gap, inflation, and interest rates. I find judgment is largely not informed by macroeconomic fundamentals; most of the variability in judgment is explained by its own stochastic shocks. Impulse response functions from the estimated model illustrate how shocks to judgment destabilize the economy and explain business cycle fluctuations.
|Item Type:||MPRA Paper|
|Original Title:||Learning and judgment shocks in U.S. business cycles|
|Keywords:||Learning; judgment; add-factors; New Keynesian model; Metropolis-Hastings|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations; Cycles
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E31 - Price Level; Inflation; Deflation
E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E50 - General
|Depositing User:||James Murray|
|Date Deposited:||09. Mar 2011 07:53|
|Last Modified:||20. Feb 2013 21:47|
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