중기선행관측을 위한 농축산물 작형별 조기예보지수 개발 연구 } : 한국농촌경제연구원

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연구보고서

중기선행관측을 위한 농축산물 작형별 조기예보지수 개발 연구

2010.04.01 36767

과제성격

기타연구(M104)
저자

김배성, 박미성
등록일

2010.04.01
연구주제

농업정책일반

요약문

The purpose of this study was to construct an early warning system for chinese cabbage, green onion, white radish, onion, pork and chicken. An introduction of early warning system in Korean agriculture is expected to help producers, consumers and policy makers as well in that it will expect to increase the efficiency of a supply-demand stabilization policy of agricultural product prices.
The literature on early warning system usually focuses on the mean of probability distribution and its deviation from the mean in identifying critical points for constructing relevant stages of early warning system: normal-attention-care-warning-seriousness. In contrast, this study utilizes the "median" of probability distribution and associated probability density in constructing such a stage. This is quite appropriate given asymmetric nature of probability distribution of agricultural product prices.
This study uses daily price data for agricultural products mentioned earlier for identifying critical points. Specifically, daily prices of 5 recent years are considered. The analysis is done in a monthly base to incorporate seasonality issues in agricultural product prices. The results reveal that identified critical points and their associated ranges are wider from the mean in the cases of vegetables such as chinese cabbage, green onion, white radish, and onion compared to those of livestock products including pork and chicken. For example, in the case of chinese cabbage, the stage for seriousness is identified when its price is fallen below -62% from its mean and its price is increased above 172% from its mean, whereas in the case of pork, the stage for seriousness is identified in a narrow fashion (below -24% and above 41% from its mean).

Researchers: Baesung Kim, Misung Park, Kwansoo Kim, Donghwan An
Research period: 2010. 2. - 2010. 4.
E-mail address: bbskim@krei.re.kr, mspark@krei.re.kr, imk@snu.ac.kr, dha@snu.ac.kr