비관측요인모형을 이용한 한국의 국내총생산 분석Analysis of Korean GDP by unobserved components model
- Authors
- 성병찬; 이승경
- Issue Date
- Oct-2011
- Publisher
- 한국데이터정보과학회
- Keywords
- 구조적 시계열 모형; 상태공간모형; 확률적 추세; State space model; stochastic trends; structural time series model
- Citation
- 한국데이터정보과학회지, v.22, no.5, pp 829 - 837
- Pages
- 9
- Journal Title
- 한국데이터정보과학회지
- Volume
- 22
- Number
- 5
- Start Page
- 829
- End Page
- 837
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/27595
- ISSN
- 1598-9402
- Abstract
- 본 논문에서는 비관측요인모형을 이용하여 한국의 국내총생산 시계열 자료를 분석한다. 이 모형이 확률적 및 결정적 요인들을 모두 포괄할 수 있다는 점을 이용하여, 보다 다양한 형태로 시계열 자료의 모형화를 시도하였으며, 지수평활법 및 박스-젠킨스의 ARIMA모형과 예측력을 비교하였다. 국내 총생산 자료에 대한 2년간의 미래 예측에서 비관측요인모형이 보다 우수함을 보인다.
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.
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