Outlier Detection in Structural Time Series Models: The Indicator Saturation Approach

46 Pages Posted: 24 Aug 2014

See all articles by Martyna Marczak

Martyna Marczak

University of Hohenheim

Tommaso Proietti

University of Rome II - Department of Economics and Finance

Date Written: August 8, 2014

Abstract

Structural change affects the estimation of economic signals, like the underlying growth rate or the seasonally adjusted series. An important issue, which has attracted a great deal of attention also in the seasonal adjustment literature, is its detection by an expert procedure. The general-to-specific approach to the detection of structural change, currently implemented in Autometrics via indicator saturation, has proven to be both practical and effective in the context of stationary dynamic regression models and unit-root autoregressions. By focusing on impulse- and step-indicator saturation, we investigate via Monte Carlo simulations how this approach performs for detecting additive outliers and level shifts in the analysis of nonstationary seasonal time series. The reference model is the basic structural model, featuring a local linear trend, possibly integrated of order two, stochastic seasonality and a stationary component. Further, we apply both kinds of indicator saturation to detect additive outliers and level shifts in the industrial production series in five European countries.

Keywords: Indicator saturation, seasonal adjustment, structural time series model, outliers, structural change, general-to-specific approach, state space model

JEL Classification: C22, C51, C53

Suggested Citation

Marczak, Martyna and Proietti, Tommaso, Outlier Detection in Structural Time Series Models: The Indicator Saturation Approach (August 8, 2014). CEIS Working Paper No. 325. Available at SSRN: https://ssrn.com/abstract=2477743 or http://dx.doi.org/10.2139/ssrn.2477743

Martyna Marczak

University of Hohenheim ( email )

Schloss, Museumsfluegel
Stuttgart, 70593
Germany

HOME PAGE: http://labour.uni-hohenheim.de/

Tommaso Proietti (Contact Author)

University of Rome II - Department of Economics and Finance ( email )

Via Columbia, 2
Rome, 00133
Italy

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