Gross Domestic Product Forecasting Using Box-Jenkins Methodology

Autor: Adrian Tamayo, Reynaldo O. Cuizon, Alben P. Sagpang
Rok vydání: 2014
Předmět:
Zdroj: SSRN Electronic Journal.
ISSN: 1556-5068
DOI: 10.2139/ssrn.2386395
Popis: This study employed the Box-Jenkins (BJ) methodology to develop a forecast model on the Philippine Gross Domestic Product (GDP). The BJ methodology requires four steps of analysis: identification, estimation, diagnosis of the model, and forecasting of the univariate series from 1995 to 2007. The test revealed that the data series was nonstationary, hence was converted to stationary series using Dickey - Fuller (DF) and the Augmented Dickey Fuller (ADF) test of stationarity. The series was also found to be an autoregressive and with a moving average characteristic. The estimate also revealed that the data fit an ARMA (1,1) class to forecast Philippine Gross Domestic Product.
Databáze: OpenAIRE