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Pierre Guérin

19 February 2014
WORKING PAPER SERIES - No. 1637
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Abstract
This paper uses a two-step approach to characterize the evolution of US macroeconomic and financial variables during episodes of very high uncertainty. First, we identify episodes of very high uncertainty using a regime-switching model. Second, we assess the behaviour of macroeconomic and financial variables during these episodes of very high uncertainty. This methodology is analogous to the approach followed by Baele et al. (2013), who study episodes of flights to safety in financial markets. We find that very high uncertainty episodes are associated with a weaker growth performance and sharp declines in stock prices. However, we find that this relation is non-linear in that uncertainty does not seem to matter during periods characterized by medium or low uncertainty.
JEL Code
C24 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Truncated and Censored Models, Switching Regression Models
D80 : Microeconomics→Information, Knowledge, and Uncertainty→General
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E66 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→General Outlook and Conditions
4 October 2011
WORKING PAPER SERIES - No. 1384
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Abstract
The paper focuses on the estimation of the euro area output gap. We construct model-averaged measures of the output gap in order to cope with both model uncertainty and parameter instability that are inherent to trend-cycle decomposition models of GDP. We first estimate nine models of trend-cycle decomposition of euro area GDP, both univariate and multivariate, some of them allowing for changes in the slope of trend GDP and/or its error variance using Markov-switching specifications, or including a Phillips curve. We then pool the estimates using three weighting schemes. We compute both ex-post and real-time estimates to check the stability of the estimates to GDP revisions. We finally run a forecasting experiment to evaluate the predictive power of the output gap for inflation in the euro area. We find evidence of changes in trend growth around the recessions. We also find support for model averaging techniques in order to improve the reliability of the potential output estimates in real time. Our measures help forecasting inflation over most of our evaluation sample (2001-2010) but fail dramatically over the last recession.
JEL Code
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications