Combining SARIMA and EGARCH Models for Modeling and Analyzing Real GDP Data in Albania

Gross domestic product (GDP) is an important measure that reflects the development of the national economy and supports relevant sectors in formulating informed policies and strategic decisions. The purpose of this study is to analyze the trend and volatility of the real GDP time series from 2000 to 2024 in Albania. The model incorporates both a SARIMA ( 2 , 1 , 2 ) ( 0 , 0 , 1 ) 4 (Seasonal Autoregressive Integrated Moving Average) process to capture the conditional mean and a GARCH (1,1) process to model the conditional volatility. The results indicate that the real GDP series exhibits strong autoregressive behavior, characterized by very persistent volatility. By capturing precise economic outcomes, such as real GDP growth rates and the shift of this research provides a framework for decision makers. From the forecasting findings, it is evident that Albania's GDP will continue to expand steadily. The following suggestions are made to support Albania's economic development: (1) optimizing and improving the economic structure; (2) strengthening competition in the market.

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Journal
WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS
Published
2026-10-01
DOI
https://doi.org/10.37394/23207.2026.23.133
Primary Topic
Forecasting Techniques and Applications
Type
article
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Combining SARIMA and EGARCH Models for Modeling and Analyzing Real GDP Data in Albania

Agim Ndregjoni, Arif Murrja
WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS
Forecasting Techniques and Applications
article

Combining SARIMA and EGARCH Models for Modeling and Analyzing Real GDP Data in Albania

Agim Ndregjoni, Arif Murrja
article en

Abstract

Gross domestic product (GDP) is an important measure that reflects the development of the national economy and supports relevant sectors in formulating informed policies and strategic decisions. The purpose of this study is to analyze the trend and volatility of the real GDP time series from 2000 to 2024 in Albania. The model incorporates both a SARIMA ( 2 , 1 , 2 ) ( 0 , 0 , 1 ) 4 (Seasonal Autoregressive Integrated Moving Average) process to capture the conditional mean and a GARCH (1,1) process to model the conditional volatility. The results indicate that the real GDP series exhibits strong autoregressive behavior, characterized by very persistent volatility. By capturing precise economic outcomes, such as real GDP growth rates and the shift of this research provides a framework for decision makers. From the forecasting findings, it is evident that Albania's GDP will continue to expand steadily. The following suggestions are made to support Albania's economic development: (1) optimizing and improving the economic structure; (2) strengthening competition in the market.

WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICSVol. 23
European University of Tirana (AL), Aleksandër Moisiu University (AL)
Decent work and economic growth
Openalex Percentile: Top 8%
Forecasting Techniques and Applications
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