청과물 가격 변동의 시계열 분석 } : 한국농촌경제연구원

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연구보고서

청과물 가격 변동의 시계열 분석

2006.11 55407

과제성격

연구보고(R537)
저자

이용선, 최병옥; 심송보
등록일

2006.11
연구주제

농산물 생산 및 유통

원문보기 좋아요

제1장 서론
1. 연구의 필요성 1
2. 연구 목적 2
3. 선행 연구 검토 3
4. 연구 내용과 방법 6
제2장 청과물 가격의 시계열 특성
1. 가격 자료의 개요 9
2. 청과물 가격의 안정성 17
3. 청과물 가격의 계절효과 25
제3장 단변량 모형에 의한 시계열 분석
1. 단변량 모형 개요 29
2. 단변량 모형에 의한 추정 및 예측 결과 33
제4장 다변량 모형에 의한 시계열 분석
1. 다변량 모형 개요 53
2. 다변량 모형에 의한 추정 및 예측 결과 58
3. 예측 모형간 비교·평가 81
제5장 요약 및 결론 87
부록 92
Abstract 95
표·그림 차례 97
참고 문헌 102

요약문

Prices of fruits and vegetables do not only fluctuate between years but also vary considerably between seasons. The purpose of this study is to investigate the patterns (characteristics) of price variation over time and find appropriate models for forecasting future prices.
The study deals with prices of four vegetables, two fruits, and four fruit-bearing vegetables. The study tests stationarity of price series and analyze seasonal effects in them. It applies mainly time-series methods - ARIMA, GARCH, VAR, and the transfer function approach - to model the movements of produce prices.
The main results are summarized as follows:
First, since systematic differences between monthly produce prices are found, price data should be differentiated between monthly figures (seasonal differences) on a year-to-year basis. And Chusok (the harvest festival) is found to have a holiday effect on the prices of apples and pears, whose prices increase by ten to twenty percent.
Second, the coefficients of seasonal autoregressive terms are found to be significantly negative and less than one in absolute value in most models. This implies that prices fluctuate but converge to the equilibrium level following the cobweb theory.
Third, according to ex-post forecasting, the study finds a model whose forecast errors are less than 15 percent for most items. In most cases, the ARIMA/GARCH and transfer function models outperform VAR models.
Lastly, the inclusion of an exogenous variable (supply quantity) into a pure time-series model increases the explanative and forecast power. This implies that the incorporation of a regression method into the time-series method would be beneficial in modeling the price of produce.
Researchers: Yong-Sun Lee, Byung-Ok Choi, and Song-Bo Sim
E-mail Address: yslee@krei.re.kr; bochoi@krei.re.kr; simsb@krei.re.kr