Institute of Mathematical Statistics Lecture Notes - Monograph Series

Modeling macroeconomic time series via heavy tailed distributions

J. A. D. Aston

Full-text: Open access


It has been shown that some macroeconomic time series, especially those where outliers could be present, can be well modelled using heavy tailed distributions for the noise components. Methods for deciding when and where heavy-tailed models should be preferred are investigated. These investigations primarily focus on automatic methods for model identification and selection. Current methods are extended to incorporate a non-Gaussian selection element, and various different criteria for deciding on which overall model should be used are examined.

Chapter information

Hwai-Chung Ho, Ching-Kang Ing, Tze Leung Lai, eds., Time Series and Related Topics: In Memory of Ching-Zong Wei (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2006), 138-148

First available in Project Euclid: 28 November 2007

Permanent link to this document

Digital Object Identifier

Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 91B82: Statistical methods; economic indices and measures
Secondary: 62M10: Time series, auto-correlation, regression, etc. [See also 91B84]

seasonal adjustment outliers model selection t-distribution economic time series

Copyright © 2006, Institute of Mathematical Statistics


Aston, J. A. D. Modeling macroeconomic time series via heavy tailed distributions. Time Series and Related Topics, 138--148, Institute of Mathematical Statistics, Beachwood, Ohio, USA, 2006. doi:10.1214/074921706000001003.

Export citation