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A quantile approach to US GNP

Yuzhi Cai Orcid Logo

Economic Modelling, Volume: 24

Swansea University Author: Yuzhi Cai Orcid Logo

Abstract

In this paper we fitted a quantile self-exciting threshold autoregressive (QSETAR) time series model tothe growth rate of real US GNP. We also presented a forecasting method for QSETAR models. Thisforecasting method makes it possible to obtain the predictive quantiles and predictive distribution fun...

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Published in: Economic Modelling
Published: 2007
URI: https://cronfa.swan.ac.uk/Record/cronfa15293
Abstract: In this paper we fitted a quantile self-exciting threshold autoregressive (QSETAR) time series model tothe growth rate of real US GNP. We also presented a forecasting method for QSETAR models. Thisforecasting method makes it possible to obtain the predictive quantiles and predictive distribution functionof xt+m given xt for mN0, and hence any quantities of interest can be derived. Therefore, this new approachallows us to study the US GNP from a distribution point view, rather than from a mean point of view. Theresults obtained in this paper show that the method works very well in practice.© 2007 Elsevier B.V. All rights reserved.
Keywords: Bayesian inference; Predictive quantiles; Predictive density functions; QSETAR model; US GNP
College: Faculty of Humanities and Social Sciences
End Page: 979