글로벌 무역 환경 충격이 국내 물가 및 생산에 미치는 영향의 경로 분석: Bayesian Network 모델을 중심으로

초록

This study aims to identify the channels through which global trade condition shocks affect domestic prices and production. Therefore, Bayesian network analysis was conducted using eight data sets reflecting global trade conditions, such as the Trade Policy Uncertainty Index and the Baltic Dry Index, and 34 data sets reflecting domestic price and production levels, including the Consumer Price Index, Producer Price Index, and Industrial Production Index. This study examines the domestic economic situation that interacts with the various global trade conditions from two perspectives: production and prices. Variables reflecting the domestic economic situation were analyzed by distinguishing them into overall indices and industry-specific indices, thereby identifying the specific industries driving interactions among the overall indices for all items. The analysis results identified, at the aggregate level network, a price shock pathway where global trade price shocks and oil price shocks propagate through the import price index and export price index to the producer price index and consumer price index. Simultaneously, it showed that production has a separate, direct shock pathway distinct from prices. At the industry level network, different pathways for global trade condition shocks were confirmed across sectors, with the service sector emerging as a key variable for domestic variables. Global trade condition shocks also exerted direct effects on both the Consumer Price Index (CPI) and Producer Price Index (PPI), not only the indirect effects transmitted through import and export prices. Regarding production, industry-level results indicate that the manufacturing production index was directly linked to export value as a parent node, while other sector production indices were indirectly linked to the export price index as child nodes.

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