Being one of the macroeconomic indicators, economic growth is a significant indicator, which shows development level of countries and welfare level of people living within the border of a country. Economic growth has a great importance especially for policy makers. Therefore, forecasting economic growth of a country is of vital importance in taking decisions such as long-term investment, employment etc. and developing, regulating and revising the policies of countries. The study aims to compare the selected exponential smoothing methods used in forecasting of Turkey’s economic growth indicators and determine the most appropriate technique. To this end, economic growth rate of Turkey between 1998 and the second quarter of 2018 was addressed and economic growth rate for the third and fourth quarters of 2018 was forecasted depending on the economic growth rate in the second quarter of 2018. Forecasts were carried out by using Winters’ seasonality exponential smoothing method based on the characteristics of time series and model selection criteria and additive Holt-Winters’ seasonality exponential smoothing method in the Cell B-2 of Pegels’ classification. It has been found out that the most appropriate method for the relevant forecasts is the additive Holt-Winters’ seasonality exponential smoothing method. It has been concluded that there would be 11,995% increase in the third quarter and 6,415% increase in the fourth quarter depending on the economic growth rate in the second quarter of 2018.
Yayımlanma Tarihi : 30 Eylül 2019
|APA||Oral, İ . (2019). Comparison of The Winters’ Seasonality Exponential Smoothing Method With The Pegels’ Classification: Forecasting of Turkey's Economic Growth Rates . Anadolu Üniversitesi Sosyal Bilimler Dergisi , 19 (3) , 275-294 . DOI: 10.18037/ausbd.632023|