STATISTICAL MODEL OF EGYPTIAN ECONOMIC GROWTH PREDICTION

Medhat Mohamed Ahmed Abdelaal, Saeed Farouk Saber Mohamed

ADVANCES AND APPLICATIONS IN STATISTICS(2016)

引用 1|浏览1
暂无评分
摘要
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.
更多
查看译文
关键词
economic growth,GDP growth rate,ARIMA,VAR,SVR
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要