확률적 기법을 이용한 단수 불확실성 하에서의 곡물모형 구축

• 영문명: Modeling the Korean Crop Market under the Yield Uncertainty Using the Stochastic Approach
• 발행기관: 한국농업경제학회
• 저자명: 순병민(Byung-Min Soon) 김준호(Junho Kim) 서홍석(Hongseok Seo)
• 간행물 정보: 『농업경제연구』62권 3호, 37~54쪽, 전체 18쪽
• 주제분류: 경제경영 > 경제학
• 파일형태: PDF
• 발행일자: 2021.09.30

영문 초록

This study introduces a stochastic agricultural policy model to generate stochastic projection under uncertainty. To do that, we extract an uncertainty from the residual in the yield functions for rice, wheat, corn, soybean, and barley to consider the uncertainty of climate conditions. A copula function is used to reflect a correlation among variables. We then utilize a Monte Carlo simulation approach to generate 500 random draws representing residuals for the yield of individual crop in the future. We impose random draws into the stochastic model built based on the crop model in KREI-KASMO. Our stochastic projections show the possible range of prices that a deterministic model does not generate. These ranges imply that the possible range of prices under the uncertainty of climate conditions in the Korean crop market. Our study finds that the actual price of rice is out of the projected range, but soybean price is within the range of stochastic price projection. Our study provides the necessity of stochastic agricultural policy model and helps policy makers and market analysts who consider a future market.

목차

Ⅰ. 서론

Ⅱ. 선행연구

Ⅲ. 확률적 농업정책모형

Ⅳ. 결과

Ⅴ. 결론

키워드

Error extraction Error simulation Korean crop market Stochastic agricultural model