베이지안 내생적 국면전환 모형을 이용한 한국의 경기변동 분석
Analysis on Korean Business Cycle using Bayesian Endogenous Markov-switching Model
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초록
본 연구에서는 베이지안 내생적 국면전환 모형을 활용하여 1990년부터 COVID-19 기간을 포함한2021년까지의 한국의 경기변동에 내생적인 전환 여부를 분석한다. 내생적 국면전환 모형은 성장률의충격과 국면 사이의 상관관계를 고려함으로써 한국의 경기변동을 보다 효율적으로 식별할 수 있다. 게다가 이 연구에서 사용된 베이지안 모형 비교 방법은 국면의 수와 그 변화가 외생적인지 내생적인지를 정확하게 비교할 수 있다. 실증분석으로 한국의 전산업생산지수 성장률 자료에 모형과 방법론을적용한 결과, 한국의 경기변동은 3가지 국면(정상, 불황, 회복)으로 나뉘며, 모든 국면전환은 내생적임을확인할 수 있었다. 특히, 성장률에 오는 충격과 국면전환 충격 사이의 상관관계가 국면이 전환되는 상태에 따라 다르게 나타났다. 이는 예측 오차의 관점에서 한국의 전산업생산지수 성장률이 가지고 있는자료의 특성을 반영한 결과라고 볼 수 있다.
Abstract
In this paper, I study Korean business fluctuations using the Bayesian endogenous regime switching model from 1990 to 2021 including the COVID-19 period. Compared to exogenous switching models, the endogenous Markov-switching models identify Korean business cycle more efficiently by considering the correlation between the regression disturbance of economic growth rate and the regime switches. In addition, the Bayesian model comparison method used in this study allows to compare the number of regime and whether the shifts are exogenous or endogenous. I apply the model and method to Korean industrial production index growth rate. According to the empirical findings, Korean economic fluctuation is subject to three state regimes (normal, recession, and recovery), and all regime changes are endogenous. In particular, the correlation between the regression shocks on the industrial production growth rate and the regime shifts are different depending on the states. There characteristics are captured by the prediction error of the Korean industrial production index growth rate.
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