Open AccessAnalysis and forecast of Turkey unemployment rate
Author(s) -
Hakan Yıldırım,
Hülya Başeğmez
Publication year - 2016
Publication title -
global journal of mathematical analysis
Language(s) - English
Resource type - Journals
ISSN - 2307-9002
DOI - 10.14419/gjma.v5i1.6841
Subject(s) - exponential smoothing , econometrics , statistics , autoregressive integrated moving average , moving average , mathematics , unemployment , unemployment rate , seasonal adjustment , exponential function , periodogram , smoothing , mean squared error , forecast error , variable (mathematics) , time series , economics , macroeconomics , mathematical analysis
This research develops techniques which are useful in forecasting single variable time series data. The techniques used in this study are moving averages (MA), Single Exponential Smoothing (SES), Adaptive Response Rate Exponential Smoothing (ARRES), Holt’s Linear and Holt-Winter’s Trend and Seasonality. For the purpose of this study, secondary data of Turkey Unemployment Rate covering the period 1996 up to 2015 was obtained from the Turkish Statistical Institute (TurkStat). From the result obtained, Adaptive Response Rate Exponential Smoothing (ARRES) was found to be the best method to forecast the Turkey Unemployment rate since it produces the lowest Mean Square Error (MSE) value which is 1.519.