Modelling Customs Revenue in Ghana Using Novel Time Series Methods

Table 2

Summary of ARIMA (0, 1, 1) model.

ARIMA (0, 1, 1) with drift
	Coefficients	SE
MA 1		0.0933
Drift	8.6917	2.5850
Sigma^2 estimate	2245.00
Log likelihood	563.75
AIC	1133.50
BIC	1141.52
Ljung–Box test p-value of residuals	0.01469