Theoretical and Practical Approaches for Determining Trend Output: an Application to Chile
Abstract
This article presents alternative output trend theories and discusses different estimations for Chile’s GDP, using quarterly data from 1986 to 2001. Among methods considered are the Hodrick-Prescott filter, Quadratic and Gaussian kernels, the wavelets filter, and structural vector autoregressive models (SVAR). Output trend estimates are very sensitive to idiosyncratic assumptions. However, the Hodrick-Prescott filter and SVAR models look more accurate for generating output gaps related to variables such as inflation. We also present confidence intervals for these two methodologies.
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