Models with Time-varying Mean and Variance: A Robust Analysis of U.S. Industrial Production

Charles Bos and Siem Jan Koopman

No 10-017/4, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions depending on dynamic stochastic processes can be sufficiently robust against changes in their dynamic properties. We further show that the implementation of the treatment is relatively straightforward. An illustration is given for monthly U.S. Industrial Production. The empirical results including estimates of time-varying means and variances are discussed in detail.

Keywords: Common stochastic variance; Kalman filter; State space model; unobserved components time series model (search for similar items in EconPapers)
JEL-codes: C22 C51 C53 E23 (search for similar items in EconPapers)
Date: 2010-02-03
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