Climate Warming: Is There Evidence in Africa?

Table 4

Estimates of in the deseasonalized monthly data using a long memory model with white noise disturbances.

	No regressors	An intercept	A linear time trend
(a) South Africa
DURBAN	0.251 (0.201, 0.316)	0.251 (0.202, 0.317)	0.244 (0.198, 0.303)
PRETORIA	0.274 (0.215, 0.347)	0.274 (0.216, 0.349)	0.278 (0.218, 0.356)
CAPE TOWN	0.185 (0.137, 0.244)	0.185 (0.137, 0.244)	0.184 (0.136, 0.244)
(b) Côte d’Ivoire
BONDOUKOU	0.311 (0.263, 0.365)	0.309 (0.261, 0.367)	0.297 (0.244, 0.355)
GAGNOA	0.367 (0.303, 0.441)	0.370 (0.307, 0.455)	0.359 (0.282, 0.444)
ABIDJAN	0.330 (0.270, 0.404)	0.330 (0.270, 0.404)	0.330 (0.270, 0.404)
(c) Kenya
KISUMU	0.357 (0.296, 0.435)	0.360 (0.298, 0.434)	0.358 (0.291, 0.443)
MOMBASA	1.117 (0.949, 1.291)	1.116 (0.948, 1.290)	1.116 (0.948, 1.290)
NAIROBI	0.448 (0.353, 0.567)	0.452 (0.365, 0.576)	0.441 (0.336, 0.563)

In bold: the significant estimates according to the deterministic terms. In parenthesis: the 95% confidence bands of the estimates of .