Advances and Applications in Statistics
Volume 47, Issue 3, Pages 225 - 246
(December 2015) http://dx.doi.org/10.17654/ADASDec2015_225_246 |
|
STATISTICAL MODEL OF EGYPTIAN ECONOMIC GROWTH PREDICTION
Medhat Mohamed Ahmed Abdelaal and Saeed Farouk Saber Mohamed
|
Abstract: This paper aims to suggest a statistical model in order to estimate the economic growth rate in Egypt as measured by the gross domestic product (GDP) growth rate and to determine the most important variables that have an influence on GDP growth rate. The study covers the period from 1977 to 2012 using quarterly data. Three statistical models have been investigated: autoregressive integrated moving average model (ARIMA) with and without explanatory variables, vector autoregressive model (VAR), and support vector machine regression (SVR), to predict the GDP growth rate in Egypt. The comparison of the three techniques based on the criteria of root mean square error (RMSE), it was determined that the univariate ARIMA model can forecast the GDP growth rate with lower error than the other forecasting models. |
Keywords and phrases: economic growth, GDP growth rate, ARIMA, VAR, SVR. |
|
Number of Downloads: 444 | Number of Views: 1264 |
|