Institute of Mathematical Statistics Lecture Notes - Monograph Series
- Lecture Notes--Monograph Series
- Volume 52, 2006, 138-148
Modeling macroeconomic time series via heavy tailed distributions
Abstract
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
Source
Dates
First available in Project Euclid: 28 November 2007
Permanent link to this document
http://projecteuclid.org/euclid.lnms/1196285971
Digital Object Identifier
doi:10.1214/074921706000001003
Subjects
Primary: 91B82: Statistical methods; economic indices and measures
Secondary: 62M10: Time series, auto-correlation, regression, etc. [See also 91B84]
Keywords
seasonal adjustment outliers model selection t-distribution economic time series
Rights
Copyright © 2006, Institute of Mathematical Statistics
Citation
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. http://projecteuclid.org/euclid.lnms/1196285971.
