Term Spread와 Credit Spread의중국 실물경제 예측력 비교 연구
Comparative Study on Chinese Real Economy Predictive Power of Term Spread and Credit Spread
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참고문헌
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초록
표본 내 예측(In Sample Forecasting)에서는 종속변수를 경기불황, GDP변화율 두 가지로 놓고 이에 대한 예측력을 여러 가지 모형의 비교를 통해서 진행하였다. 결과에 의하면 Credit Spread와 Term Spread는 모두 통계적으로 매우 유의하게 중국경제 변화를 예측하는 것으로 나타났다. 하지만 단기에 있어서 Term Spread의 예측력은 유의하지 않은 것으로 나타났고 선행지수(Leading Indicator)가 유의한 것으로 나타났다. 이를 통해 보았을 때 단기에 있어서는 Term Spread와 선행지수가 비슷한 정보를 가지고 있는 것을 알 수 있으며, Credit Spread는 이들과는 다른 정보를 가지고 있다는 것을 알 수 있다. 표본 외 예측(Out of Sample Forecasting)에서는 Term Spread와 Credit Spread를 각각 비교했을 때는 Credit Spread의 예측력이 중장기에 있어 통계적으로 우월했고, AR(1)모형과 비교했을 때는 Credit Spread만 AR(1)모형에 통계적으로 우월한 예측력을 보였다. 그리고 Term Spread와 Credit Spread를 같이 사용했을 때가 각자 따로 사용했을 때보다 우월한 예측력을 갖고 있는 것으로 나타났다. 마지막으로 PMI와 선행지수에 Term Spread와 Credit Spread를 각기 추가해서 모형을 구성했을 때에는 Credit Spread를 추가했을 때의 예측력이 유의하게 높은 것으로 나타났다. 그리고 시간에 따른 (Time Varing) t-value의 변화값은 Credit Spread의 경우 모든 시점에서 통계적으로 유의했고, Term Spread의 경우 일부 구간에서 유의하지 않아 Credit Spread의 예측력이 더 강건한(robust)한 것으로 나타났다.
Abstract
According to recent studies, it is shown that both Term Spread and Credit Spread have more predictive power than PMI and Leading Indicator in predicting changes of Chinese real economy. If so, which of the Term Spread and Credit Spread has more predictive of the economy? Otherwise, is it possible to use only one of them, or is it more efficient to use the two together to predict the Chinese economy? This study started from the curiosity of these topics. In-Sample-Forecasting takes the economic recession and the GDP change rate as the dependent variables, and the predictive power on them is compared through various models. The results reveal that both the Credit Spread and Term Spread predict statistically significant changes in the Chinese economy. However, it is shown that in the short term the predictive power of Term Spread is not significant, but that of Leading Indicator is so. Consequently, in the short term, it can be seen that Term Spread and Leading Indicator have similar information and Credit Spread has different information from them. As for Out-of-Sample-Forecasting, when Term Spread and Credit Spread are compared respectively, the predictive power of Credit Spread is statistically superior in the mid to long term. When compared with AR(1) model, only Credit Spread shows statistically superior predictive power to AR(1) model. In addition, it is revealed that when Term Spread and Credit Spread are used together, they have superior predictive power to respective use of them. Finally, when the model is established by adding Term Spread and Credit Spread to the PMI and Leading Indicator, it is shown to have significantly high predictive power, with Credit Spread added. In respect of change value of t-value according to Time Varying, Credit Spread is statistically significant at all times while Term Spread is not so in some sections, which discloses that Credit Spread has more robust predicative power.
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