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American Journal of Applied Mathematics and Statistics. 2016, 4(5), 136-148
DOI: 10.12691/AJAMS-4-5-1
Original Research

Forecast of Sarima Models: Αn Application to Unemployment Rates of Greece

Chaido Dritsaki1,

1Department of Accounting and Finance, University of Applied Sciences of Western Macedonia, Kozani, Greece

Pub. Date: September 29, 2016

Cite this paper

Chaido Dritsaki. Forecast of Sarima Models: Αn Application to Unemployment Rates of Greece. American Journal of Applied Mathematics and Statistics. 2016; 4(5):136-148. doi: 10.12691/AJAMS-4-5-1

Abstract

The low unemployment rate is one of the main targets of macroeconomic policy for each government. Forecasting unemployment rate is of great importance for each country so as the government can draw up strategies for fiscal policy. The aim of the paper is to find the most suitable model which is adjusted on unemployment rates of Greece using Box-Jenkins methodology and to examine the precision of forecasting on this model. Models’ estimation was made using the non-linear Maximum likelihood optimization methodology (maximum likelihood–ML), whereas covariance matrix is estimated with OPG method using the numerical optimization of Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. Forecasting unemployment rate was made both with dynamic and static process using all criteria of forecasting measures.

Keywords

unemployment, SARIMA, Box-Jenkins methodology, forecasting, Greece

Copyright

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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