FORECASTING PRODUCTION OF SOME OIL SEED CROPS IN TURKEY USING EXPONENTIAL SMOOTHING METHODS
K. Karadas, S. Celik, E. Eyduran and S. Hopoglu
Igdir University, Agricultural Faculty, Department of Agricultural Economics, Igdir, Turkey
Bingol University, Agricultural Faculty, Department of Animal Science, Bingol, Turkey
Igdir University, Agricultural Faculty, Department of Animal Science, Igdir, Turkey
Igdir University, Faculty of Economics and Administrative Sciences, Department of Economics, Igdir, turkey.
Corresponding Author’s email: firstname.lastname@example.org
The aim of the investigation was to forecast annual production of some oil seed crops (sesame, sunflower and soybean) in Turkey for the years 2016 through 2025 using annual production data for the period 1950-2015 and to give solid recommendation on production for producers, consumers and input providers. For this aim, three exponential smoothing methods, Holt, Brown and Damped Trend were executed to economically model the time series data. Goodness of fit criteria such as stationary R2, R2 and BIC criteria were adopted in the comparison of these exponential smoothing methods. Soybean, sunflower and sesame production amounts for the period 2016 -2025 were forecasted with high accuracy by using Holt exponential smoothing method with two parameters, which yielded the best result among exponential smoothing methods. Forecasted production amounts of soybean, sunflower and sesame from the period 2016- 2025 ranged from 162.878 to 179.784, 1.692.269 to 1.879.521 and 18.212 to 15.318 tons, respectively. We hope that the results from the time series data will provide baseline information for sustaining production and for guiding agricultural policy and exports of Turkey in terms of the above-mentioned plants in forthcoming years.
Key Words: Production Forecasting, Exponential Smoothing, Time Series Data, Oil Plants.