Trends and Cycles in Real-Time
AbstractThis paper compares the results of applying several detrending methods to the Chilean monthly economic activity index (IMACEC) that arise from using real-time data sets. We show that data revisions are extremely important and that they can lead to systematically inconsistent estimates of the trend component. Furthermore, most of the filters commonly used to detrend time series in practice, are highly unstable and unreliable for end-of-sample estimation.
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Bibliographic InfoPaper provided by Central Bank of Chile in its series Working Papers Central Bank of Chile with number 130.
Date of creation: Nov 2001
Date of revision:
Other versions of this item:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
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- St-Amant, P. & van Norden, S., 1997. "Measurement of the Output Gap: A Discussion of Recent Research at the Bank of Canada," Technical Reports 79, Bank of Canada.
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- Kishor, N. Kundan, 2009. "Data Revisions in India and its Implications for Monetary Policy," MPRA Paper 16099, University Library of Munich, Germany.
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