DSGE 모형을 이용한 추세와 경기순환변동분의 분해
Trend/Cycle Decomposition Using DSGE Models
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초록
본 논문은 간단한 동태적 확률 일반균형(DSGE) 모형과 탄력적 추세를 고려한 비관측인자 모형을 결합하여, DSGE 모형의 추정과 추세/순환변동분의 분해를 동시에 시도하였다. 이를 통해 추정된 GDP 순환변동분은 공식 경기순환 국면과 상당 정도 부합하는 등 전반적으로 경기순환을 잘 반영하는 것으로 나타났다. 하지만 변동성과 지속성의 측면에서 통상적 필터링 방법을 이용한 경우와는 적지 않은 차이가 있었으며, 특히 GDP의 추세분은 상당한 변동성을 보이며 경기순응적 모습을 보였다. 추정된 순환변동분의 성격을 변수별로 살펴보면, GDP와 이자율의 경우는 HP 필터의 결과와 유사한 반면, 인플레이션의 경우는 (불규칙 변동분을 추가로 제외한 경우) BK 필터를 이용한 결과와 상대적으로 더 유사한 것으로 나타났다. 이는 분석대상 변수들에 임의의 단일한 필터링 방법을 적용할 경우, 경기순환분의 성격이 잠재적으로 왜곡되어 추출될 우려가 있음을 보여준다. 습관 및 가격연동을 포함한 확장모형을 고려한 경우, 습관은 경기변동의 지속성을 설명함에 있어 중요한 요소인 것으로 평가된 반면, 가격연동은 그 중요성이 제한적인 것으로 나타났다. 이러한 모형의 개별 요소들에 대한 평가 결과는, 사전 필터링된 자료를 이용하여 추정한 경우와 적지 않은 차이를 보여, 자료의 필터링과 모형의 추정을 분리하여 고려하는 일반적인 DSGE 모형의 추정 및 분석은 잠재적으로 오류의 가능성이 있음을 시사한다.
Abstract
This paper decomposes and estimates trend/cyclical components of some key macro variables–GDP, inflation, and interest rate, using a simple DSGE model along with flexible trend specification. The extracted cyclical components of output and interest rate are similar to HP-filtered counterparts, despite some differences in persistence and volatility, while inflation resembles that from BK filtering. This implies that the usual practice of applying a single filtering method to the data of interest may be problematic. When the baseline model is extended to incorporate consumption habit and price indexation, habit turns out to be important in explaining the persistence of business cycles. Comparison of several alternative models shows that the usual practice of estimation of DSGE model using filtered data leads to biased results. Finally, various sensitivity analyses illustrate that (1) allowing for correlation between structural cyclical shocks and trend shocks and (2) including irregular components (in inflation rate) may deliver interesting/important implication for gap estimates.
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