Time series modelling and forecasting of Sarawak black pepper price
AbstractPepper is an important agriculture commodity especially for the state of Sarawak. It is important to forecast its price, as this could help the policy makers in coming up with production and marketing plan to improve the Sarawak’s economy as well as the farmers’welfare. In this paper, we take up time series modelling and forecasting of the Sarawak black pepper price. Our empirical results show that Autoregressive Moving Average (ARMA) time series models fit the price series well and they have correctly predicted the future trend of the price series within the sample period of study. Amongst a group of 25 fitted models, ARMA (1, 0) model is selected based on post-sample forecast criteria.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 791.
Date of creation: 2000
Date of revision:
Time series; pepper (Piper nigrum L.); Autoregressive Moving Average model; forecasting; forecast accuracy;
Find related papers by JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
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