Del 154 i serien Lecture Notes in Statistics

Measuring Business Cycles in Economic Time Series

Häftad, Engelska, 2000

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The purpose of the manuscript is to outline and demonstrate problems with the use of the HP filter, and to propose an alternative strategy for inferring cyclical behavior from a time series that features seasonal, trend, cyclical and noise components. The main innovation of the alternative strategy involves augmenting the series in question with forecasts and backcasts obtained from an ARIMA model, and then applying the HP filter to the augmented series. Comparisons presented in the paper using artificial and actual data demonstrate the superiority of the alternative strategy.

Produktinformation

Utgivningsdatum2000-11-17
Mått155 x 235 x 12 mm
Vikt318 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Statistics
Antal sidor190
FörlagSpringer-Verlag New York Inc.
ISBN9780387951126

Tillhör följande kategorier

1 Introduction and Brief Summary.- 2 A Brief Review of Applied Time Series Analysis.- 2.1 Some Basic Concepts.- 2.2 Stochastic Processes and Stationarity.- 2.3 Differencing.- 2.4 Linear Stationary Process, Wold Representation. and Auto-correlation Function.- 2.5 The Spectrum.- 2.6 Linear Filters and Their Squared Gain.- 3 ARIMA Models and Signal Extraction.- 3.1 ARIMA Models.- 3.2 Modeling Strategy, Diagnostics and Inference.- 3.3 Preadjustment.- 3.4 Unobserved Components and Signal Extraction.- 3.5 ARIMA-Model-Based Decomposition of a Time Series.- 3.6 Short-Term and Long-Term Trends.- 4 Detrending and the Hodrick-Prescott Filter.- 4.1 The Hodrick-Prescott Filter: Equivalent Representations.- 4.2 Basic Characteristics of the Hodrick-Prescott Filter.- 4.3 Some Criticisms and Discussion of the Hodrick-Prescott Filter.- 4.4 The Hodrick-Prescott Filter as a Wiener-Kolmogorov Filter.- 5 Some Basic Limitations of the Hodrick-Prescott Filter.- 5.1 Endpoint Estimation and Revisions.- 5.2 Spurious Results.- 5.3 Noisy Cyclical Signal.- 6 Improving the Hodrick-Prescott Filter.- 6.1 Reducing Revisions.- 6.2 Improving the Cyclical Signal.- 7 Hodrick-Prescott Filtering Within a Model-Based Approach.- 7.1 A Simple Model-Based Algorithm.- 7.2 A Complete Model-Based Method; Spuriousness Reconsidered.- 7.3 Some Comments on Model-Based Diagnostics and Inference.- 7.4 MMSE Estimation of the Cycle: A Paradox.- References.- Author Index.

From the reviews: MATHEMATICAL REVIEWS "Altogether this book is more on the mathematical side, it is well written following the same idea throughout and contains many exercises which complete the different topics. The text concentrates on the approach of the authors...I enjoyed reading this nicely written book which can certainly be recommended to all mathematically oriented statisticians interested in the subject."