Forecasting of oilseeds production: Applications of UCM model using SAS

In India, annual production of oilseeds is around 27.51 million tons and it grown in around 25.59 million hectares of area (Agricultural Statistics at a Glance 2016). Present study focused on forecasting of oilseeds production in India using Unobserved Component Models. The present paper is to discuss structural time series methodology utilized for modeling time-series data in the presence of trend, seasonal and cyclic and irregular fluctuation has been discussed. Structural time series model are formulated in such a way that their components are stochastic, i.e. they are related as being driven by random disturbances. A number of methods of computing Maximum Likelihood Estimators are considered. These include direct maximization of various times domain likelihood function. Once a model estimated, its suitability can be assessed using goodness of fit statistics and model used to predict for ten leading years. In the study the model developed for oilseeds production, from the forecasting available. Afteranalysis of production of oilseeds by structural time series model using SAS, oilseeds production forecast for the year 2025 to be near about 35.00 million tones with upper and lower confidence limit 27.21 and 42.80 million tonnes respectively and it shows that there is an increasing trend for production of oilseeds in India.