농업경제연구

Korean Agricultural Economics Association

제목 확률적 기법을 이용한 단수 불확실성 하에서의 곡물모형 구축
저자 순병민, 김준호, 서홍석
발행정보 62권 3호 (2021년 9월) 페이지 37~54
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.
논문파일 KJAE(2021-Vol62No03)-Korean-03.pdf