기상변인을 고려한 채소가격 예측모형 개발

Developing Vegetable Price Forecasting Model with Climate Factors

Both farmers and consumers can benefit from the provision of more accurate price forecasting in unstable vegetable market. Focusing on the role of climate factors, which is expected to impact on vegetable price, this study develops price fore casting models for napa cabbage using Bayesian Structural Time Series (BSTS) and Vector Autoregressive (VAR) approaches. Across forecasting models, we show the consideration of climate factors enhances forecasting power significantly compared to pure time series models. BSTS and VAR can be used mutually complementarily by providing various forecasting scenarios based on market conditions.