  In this paper, we capture the dynamic behaviour of hourly consumption of
electricity during the period of power crisis ("dumsor" period) in Ghana using
two-state Markov switching autoregressive (MS-AR) and autoregressive (AR)
models. Hourly data between the periods of January 1, 2014, and December 31,
2014 was obtained from the Ghana Grid company and used for the study. Using
different information criteria, the MS(2)-AR(4) is selected as the optimal
model to describe the dynamic behaviour of electricity consumption during
periods of power crisis in Ghana. The parameters of the MS(2)-AR(4) model are
then estimated using the expectation-maximization algorithm. From the results,
the likelihood of staying under a low electricity consumption regime is
estimated to be 87\%. The expected duration for a low electricity consumption
regime is 7.8 hours daily, and the high electricity consumption regime is
expected to last 2.3 hours daily. The proposed model is robust as compared to
the autoregressive model because it effectively captures the dynamics of
electricity demand over time through the peaks and significant fluctuations in
consumption patterns. Similarly, the model can identify distinct regime changes
linked to electricity consumption during periods of power crises.
