Forecasting of Palay and Fishery Production
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Abstract:
The Bureau of Agricultural Statistics (BAS) releases two-quarter forecasting of rice production using data from the Rice and Corn Production Survey (RCPS). The survey is being conducted quarterly, hence estimates for a three-quarter forecasting or greater is difficult to be measured. On the other hand, forecast estimates for fishery production and aquaculture are hindered by the lack of data on factors affecting commercial and marine production. With these challenges, this paper was motivated to determine the appropriate methods in computing forecasting estimates for rice and fish production using regression techniques, i.e, regression, ARIMA modelling and exponential smoothing. It was also given priority to assess periodic changes in the time series data of palay and fish production by comparison of annual and quarterly growth rates between the actual data and forecast data. Frameworks for palay and fish production were studied to determine which factors to include in developing regression models. For the conclusion of this study, appropriate regression techniques which give the lowest number of errors were recommended for forecast estimates.
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