Modelling Customs Revenue in Ghana Using Novel Time Series Methods

Table 3

Summary of ARIMA error regression model.

Regression with ARIMA (1, 1, 1) errors
	Coefficients	SE
AR 1	0.3871	0.1250
MA 1		0.0661
Drift	7.1504	1.0025
EDR variable	19.3621	6.1251
CIF variable	0.0314	0.0067
estimate	1845.00
Log likelihood	551.95
AIC	1115.91
BIC	1131.95
Ljung–Box test -value of residuals	0.3019

Target: revenue generated by GRA-CD.