해운 운임 간 인과관계에 관한 연구
A Study on the Causal Relationship Between Shipping Freight Rates
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초록
본 연구의 목적은 VECM 모형(Vector Error Correction Model)을 활용해 해운 운임 간 인과관계를 분석하는 것이다. 분석에 사용된 해운 운임은 BDI(Baltic Dry Index), HRCI(Howe Robinson Containership Index), WS(World Scale rate), SCFI(Shanghai Containerized Freight Index)다. 분석 기간은 2013년 8월 2일부터 2019년 9월 6일까지이며 주간 데이터를 활용했다. VECM 모형 분석 결과, BDI는 일주일 전의 BDI에 많은 영향을 받는 것으로 분석되었으며, WS의 1% 상승은 일주일 후의 HRCI를 0.022% 상승시키는 것으로 분석되었다. HRCI 1% 상승은 일주일 후의 SCFI를 0.77% 상승시키며, WS는 일주일 전의 WS에 많은 영향을 받는 것으로 나타났다. 본 연구의 분석 결과는 각 해운시장의 해운 운임 예측에 도움을 주며, 이를 활용하여 의사결정자들이 올바른 의사결정을 할 수 있게 도움을 줄 수 있다고 사료된다.
Abstract
The purpose of the study was to utilize VECM(Vector Error Correction Model) and detect causal relationships among shipping freight rates. Shipping freight rates used in this study were BDI(Baltic Dry Index), HRCI(Howe Robinson Containership Index), WS(World Scale rate) and SCFI(Shanghai Containerized Freight Index). Using weekly data published since August 2nd, 2013 to September 6th, 2019, it was discovered that BDI and WS were heavily influenced by past week’s BDI and WS respectively. VECM also found that one percent increase in WS resulted in 0.022% increase in following week’s HRCI data. One percent increase in HRCI affects SCFI by 0.77% on the following week. This study believes that finding may help each shipping market of shipping freight rates estimates, thereby encouraging decision markers to exercise discretion and establish best interest decision.
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