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Phillips, P.C., and Perron, P. “Testing for a unit root in time series regression”, Biometrika, 75(2), 335-46, 1988.

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Article

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

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


American Journal of Applied Mathematics and Statistics. 2016, Vol. 4 No. 5, 136-148
DOI: 10.12691/ajams-4-5-1
Copyright © 2016 Science and Education Publishing

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.

Correspondence to: Chaido  Dritsaki, Department of Accounting and Finance, University of Applied Sciences of Western Macedonia, Kozani, Greece. Email: dritsaki@teiwm.gr

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.

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