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Analysis of Korean GDP by unobserved components model  

Seong, Byeong-Chan (Department of Applied Statistics, Chung-Ang University)
Lee, Seung-Kyung (Department of Statistics, Chung-Ang University)
Publication Information
Journal of the Korean Data and Information Science Society / v.22, no.5, 2011 , pp. 829-837 More about this Journal
Abstract
Since Harvey (1989), many approaches for applying unobserved components (UC) models to both univariate and multivariate time series analysis have been developed. However, practitioners still tend to use traditional methods such as exponential smoothing or ARIMA models for modeling and predicting time series data. It is well known that the UC model combines the flexibility of ARIMA models and the easy interpretability of exponential smoothing models by using unobserved components such as trend, cycle, season, and irregular components. This study reviews the UC model and compares its relative performances with those of the other models in modeling and predicting the real gross domestic products (GDP) in Korea. We conclude that the optimal model is the UC model on basis of root mean squared error.
Keywords
State space model; stochastic trends; structural time series model;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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