Journal of Finance and Economics
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Journal of Finance and Economics. 2017, 5(3), 145-155
DOI: 10.12691/jfe-5-3-7
Open AccessArticle

Stochastic Models for Forecasting Inflation Rate: Empirical Evidence from Greece

Chaido Dritsaki1, and Leonidas Petrakis2

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

2Department of Mechanical Engineering, Western Macedonia University of Applied Sciences, Kozani, GREECE

Pub. Date: June 12, 2017

Cite this paper:
Chaido Dritsaki and Leonidas Petrakis. Stochastic Models for Forecasting Inflation Rate: Empirical Evidence from Greece. Journal of Finance and Economics. 2017; 5(3):145-155. doi: 10.12691/jfe-5-3-7


The main aim of the macroeconomic policy of every country is to achieve a continuously high economic development combined with low inflation rates. A low, stable inflation level together with a sustainable budget deficit, a realistic exchange rate and a suitable real interest rate, consist indices of a stable macroeconomic environment. The diverse economic policies applied in Greece during the period under consideration, led to high inflation periods and guided the country to IMF since 2010. The high inflation rate in Greece was mainly generated by the increasing money supply. The present paper is an effort for the development of a stochastic model which will enable us to forecast inflation, taking into consideration the economic periods Greece went through. For this reason, we use the Box-Jenkins methodology by constructing a seasonal ARIMA model in order to represent the mean component using the past values. Then we incorporate a GARCH model to represent its volatility. The results of all tests reveal that the seasonal SARIMA(2,1,2)(0,1,1)12-EGARCH(1,1) model with the distribution of the generalized error (GED) and the Marquardt algorithm is the most suitable for forecasting the inflation in Greece. The forecasting results of this model showed that inflation in the following months will range from 0 to 1%.

inflation rate SARIMA-EGARCH model Box-Jenkins methodology forecasting Greece

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