Modelling Customs Revenue in Ghana Using Novel Time Series Methods

Table 1

Sample of the study data.

Month	CIF	ZE	ECIF	EDR	IDREV	TOTREV	XCHR
Jan-10	943.19	352.88	590.31	6.63	68.33	143.25	1.42
Feb-10	1229.56	659.64	569.92	4.68	67.85	142.04	1.42
Mar-10	1368.67	670.93	697.74	5.18	83.46	172.98	1.42
Apr-10	1134.18	543.99	590.19	5.27	73.44	155.29	1.41
May-10	1078.69	481.63	597.06	5.79	71.67	154.25	1.41
Jun-10	1226.05	530.87	695.18	5.83	78.24	166.14	1.41
Jul-10	1172.36	451.14	721.22	6.42	83.7	180.08	1.42
Aug-10	1398.91	610.02	788.89	5.9	89.96	191.62	1.42
Oct-11	1830.22	671.21	1159.01	6.6	138.93	290.17	1.53
Nov-11	1814.09	686.87	1127.22	6.64	146.74	308.04	1.54
Dec-11	1974.15	912.32	1061.83	5.89	152.06	317.41	1.56
Oct-19	3725.87	1346.75	2379.12	7.27	432.25	840.9	5.32
Nov-19	3200.34	983.87	2216.48	8.19	438.93	855.19	5.39
Dec-19	3510.3	1102.26	2408.04	8.2	481.24	934.93	5.53

The revenue figures presented in the table are in millions of Ghanaian cedis.