Forecasting Chestnut Production and Export of Turkey Using ARIMA Model
Journal Title: Turkish Journal of Forecasting - Year 2018, Vol 2, Issue 2
Abstract
Turkey is one of main producers and exporter countries of chestnut in the world. It is essential to assess scientifically the accurate future production and export potentials of chestnut on the basis of past trends. This study focuses on forecasting the chestnut production and export of Turkey up to the year 2021 using Autoregressive Integrated Moving Average (ARIMA) model. The time series data for the chestnut production and export of Turkey were obtained from the Food and Agriculture Organization of the United Nations (FAO). Annual data for the period of 1961-2016 was used for the study. The study revealed that the best models for forecasting the chestnut production and export were ARIMA (1, 1, 1) and ARIMA (1, 2, 1), respectively. The ARIMA model showed that while the chestnut production of Turkey in 2021 would be 64.183 tonnes with lower limit of 38.946 tonnes and upper limit of 89420 tonnes. However, Turkey’s chestnut export in 2021 would be 7.962 tonnes with lower limit of 563 tonnes and upper limit of 15362 tonnes. The study concluded that Turkey’s chestnut production and export will increase in the forecasted years. The stakeholders of chestnut sector should take account these projections in their production and marketing decision.
Authors and Affiliations
Uğur BAŞER, Mehmet BOZOĞLU, Nevra ALHAS EROĞLU, Bakiye KILIÇ TOPUZ
An Enhanced Neural-based Bi-Component Hybrid Model for Foreign Exchange Rate Forecasting
Foreign exchange rates are among the most important economic indices in the international monetary markets. For large multinational firms, which conduct substantial currency transfers in the course of business, being abl...
Stock Market Prediction Using Nonparametric Fuzzy and Parametric GARCH Methods
Prediction of stock market value is one the most complicated issue during the past decades. Due to its importance, in this research, we consider the prediction of stock values based on non-parametric and parametric metho...
G-STAR Model for Forecasting Space-Time Variation of Temperature in Northern Ethiopia
Among many indicators of climate change, the temperature is a key indicator to take remedial action for world global warming. This finding provides application of space-time models for temperature data, which is selected...
Time Series Prediction with Direct and Recurrent Neural Networks
This article presents a comparative study of the prediction of time series for the Consumer Price Index (CPI) using a recurrent neural network (RNN). For this, three models are designed for recurrent networks, with chang...
Bayesian Learning based Gaussian Approximation for Artificial Neural Networks
In the nonlinear systems, the pre-knowledge about the exact functional structure between inputs and outputs is mostly either unavailable or insufficient. In this case, the artificial neural networks (ANNs) are useful too...