초록
영어
This paper studies the performance of various forecasting models for Korean inflation rates. The models studied in this paper are the AR(p) model, the dynamic predictive regression model with such exogenous variables as the unemployment rate and the term spread, the inflation target model, the random walk model, and the dynamic predictive regression model using estimated factors along with the unemployment rate and the term spread. The sampling period studied in this paper is 2000M11--2011M06. Among the studied models, the dynamic predictive regression model using estimated factors along with the unemployment rate and the term spread tends to perform best when the factors are extracted from I(1) series and the variables for the factor extraction are selected by the criterion of the correlation of each variable with the inflation rate.
한국어
본 논문은 한국인플레 예측을 위한 여러 모형들의 성과를 연구한다. 이 논문에서 연구된 모형들은 AR(p) 모형, 실업률 혹은 이자율차이를 외생변수로 갖는 동태적 회귀모형, 인플레 타겟 모형, 랜덤워크 모형, 실업률 혹은 이자율차이와 요소를 외생변수로 갖는 동태적 회귀모형 이다. 이중에서 요소가 I(1)변수로부터 추출되었을 경우, 실업률 혹은 이자율차이와 요소를 외생변수로 갖는 동태적 회귀모형이 가장 좋은 성과를 보임을 발견할 수 있다.
목차
1. Introduction
2. Data and methods for forecasting evaluation
3. Forecasts using benchmark and naive models
4. Factor-based forecasts
4.1 Forecasts using I(0) factors
4.2 Forecasts using I(1) factors
5. Results of the Diebold-Mariano test
6. Summary and conclusion
7. Appendix
References
초록