Advanced SearchSearch Tips
A Study on Forecast of Oyster Production using Time Series Models
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
  • Journal title : Ocean and Polar Research
  • Volume 34, Issue 2,  2012, pp.185-195
  • Publisher : Korea Institute of Ocean Science & Technology
  • DOI : 10.4217/OPR.2012.34.2.185
 Title & Authors
A Study on Forecast of Oyster Production using Time Series Models
Nam, Jong-Oh; Noh, Seung-Guk;
  PDF(new window)
This paper focused on forecasting a short-term production of oysters, which have been farmed in Korea, with distinct periodicity of production by year, and different production level by month. To forecast a short-term oyster production, this paper uses monthly data (260 observations) from January 1990 to August 2011, and also adopts several econometrics methods, such as Multiple Regression Analysis Model (MRAM), Seasonal Autoregressive Integrated Moving Average (SARIMA) Model, and Vector Error Correction Model (VECM). As a result, first, the amount of short-term oyster production forecasted by the multiple regression analysis model was 1,337 ton with prediction error of 246 ton. Secondly, the amount of oyster production of the SARIMA I and II models was forecasted as 12,423 ton and 12,442 ton with prediction error of 11,404 ton and 11,423 ton, respectively. Thirdly, the amount of oyster production based on the VECM was estimated as 10,425 ton with prediction errors of 9,406 ton. In conclusion, based on Theil inequality coefficient criterion, short-term prediction of oyster by the VECM exhibited a better fit than ones by the SARIMA I and II models and Multiple Regression Analysis Model.
oyster;forecast;multiple regression analysis model;seasonal autoregressive integrated moving average model;vector error correction model;
 Cited by
시계열 분석을 이용한 굴 가격 예측에 관한 연구,남종오;노승국;박은영;

해양정책연구, 2012. vol.27. 1, pp.65-94
시계열 모형을 이용한 김 위판가격 예측에 관한 연구,남종오;백은영;노승국;

해양정책연구, 2014. vol.29. 2, pp.271-303
Analysis for Efficiency in the Oyster, Mussel Aquaculture Household using SFA, The Journal of Fisheries Business Administration, 2016, 47, 2, 1  crossref(new windwow)
강창완, 김대학 (2000) 쌀 예상 생산량 추정방법에 대한 연구. 응용통계연구 13(2):329-341

고성보 (2003) 생산형태별 감자의 수급예측모형 개발. 농업경제연구 44(4):221-222

국립해양조사원 (2011) 실시간 연안정보. Accessed 10 Oct 2011

기상청 (2011) 관측자료. Accessed 10 Oct 2011

김명직, 장국현 (2008) 금융시계열분석 제2판. 경문사, 822 p

김배성, 박미성, 조재환, 김태균 (2010) 중기선행관측을 위한 농축산물 작형별 수급모형 및 예측평가시스템 개발 연구. 한국농촌경제연구원, M103, 77 p

김현용 (2000) WTO 관세인하가 수산물 수급에 미치는 영향과 대책. 경제학박사 학위논문, 부경대학교, 134 p

남해안신문 (2012) 한파에 따른 저수온 우려.양식장 관리 비상 Accessed 14 Jan 2012

박철형, 이광남 (1997) 우리나라 연근해산 수산물의 생산량 예측에 관한 조사 연구. 수산업협동중앙회 수산경제연구원, 연구보고 97-1, 128 p

박해훈, 윤갑동 (1996) 시계열분석을 이용한 한국 명태어업의 어획량 예측. 어업기술연구 32(3):235-240

수산업관측센터 (2011) 굴 수산관측 244호, 257호. 한국해양수산개발원, 8 p

연합뉴스 (2011) 한파 장기화 양식장 저수온 피해 우려 Accessed 14 Jan 2012

이진희, 신기일 (2000) 조건부 자기회귀모형을 이용한 송이 버섯 생산량 예측. 응용통계연구 13(2):307-320

장석환 (2000) 주요 식량작물의 생산량 예측 모형에 관한 연구. 한국데이터정보과학회 11(1):47-48

전남일보 (2008) 굴 생산 급감…어민 "어떡하나" Accessed 16 Sep 2012

조용준 (2005) 수산물 생산량 예측모형 연구 : 시계열 모형을 중심으로. 수산업협동중앙회 수산경제연구원, 351 p

통계청 (2011) 어업생산동향조사. Accessed 2 Oct 201

한국농촌경제연구원 (1988) 수산재해에 따른 양식공제시험사업 설계 : 굴 수하식양식을 중심으로. 한국농촌경제연구원, 연구보고 176, 125 p

한국수산경제 (2008) 남해안 가을가뭄에 어심도 탄다 Accessed 8 Jan 2012

Chesoh S, Lim A (2008) Forecasting fish catches in the Songkhla Lake basin. Sci Asia 34:335-340 crossref(new window)

Czerwinski I, Gutierrex-Estrada J, Hernando-Casal J (2007) Short-term forecasting of halibut CPUE : Linear and non-linear univariate approaches. Fish Res 86:120-128 crossref(new window)

Diebold X, Mariano S (1995) Comparing predictive accuracy. J Bus Econ Statist 13:253-263

Koutroumanidis T. Iliadis L, Sylaios G (2006) Time-series modeling of fishery landings using ARIMA models and Fuzzy Expected Intervals software. Environ Modell Softw 21:1711-1721 crossref(new window)

Mendelssohn R (1981) Using Box-Jenkins Model to Forecast Fishery Dynamics : Identification, Estimation, and Checking. Fish B-NOAA 78(4):887-896

Noble A, Sathianandan TV (1991) Trend analysis in all- India mackerel catches using ARIMA models. Indian J Fish 38:119-122

Potter ECE, Crozier WW, Schön PJ, Nicholson MD, Maxwell DL, Prévost E, Erkinaro J, Gudbergsson G, Karlsson L, Hansen LP, Maclean JC, Maoiléidigh Ó, Prusov S (2004) Estimating and forecasting pre-fishery abundance of Atlantic salmon (salmo salar L.) in the Northeast Atlantic for the management of mixed-stock fisheries. ICES J Mar Sci 61:1359-1369 crossref(new window)

Stergiou K, Christou E, Petrakis G (1997) Modelling and forecasting monthly fisheries catches : Comparison of regression, univariate and multivariate time series methods. Fish Res 29:55-95 crossref(new window)

Wertheimer A, Orsi J, Fergusson E, Sturdevant M (2009) Forecasting Pink Salmon Harvest in Southeast Alaska from Juvenile Salmon Abundance and Associated Environmental Parameters : 2008 Returns and 2009 Forecast. NPAFC, 20 p