This study provides a forward-looking simulation analysis of economy-wide and distributional
implications associated with alternative pathways for the development of the electricity sector
in Ghana and Kenya. It is part of a wider research project that seeks to identify the binding
constraints to economically viable investments in renewable energy and to analyse the political
feasibility of a transition to a sustainable low carbon energy path in the two countries.
From an economic perspective, significant shifts in the power mix of an economy as well as
policy measures to induce or support such shifts are bound to affect the structure of domestic
prices across the whole economy with repercussions for the growth prospects of different
production sectors and for the real income growth paths of different socio-economics groups.
Understanding these economy-wide repercussions is crucial for a study concerned with the
obstacles to - and political feasibility of - adopting a low-carbon growth strategy. The analysis
requires the adoption of a multi-sectoral general equilibrium approach that allows to capture
the input-output linkages between the electricity sector and the rest of the economy as well as
the linkages between production activity, household income and expenditure and government
policy.
Thus, the present study develops purpose-built dynamic computable general equilibrium
(CGE) models for Ghana and Kenya with a detailed country-specific representation of the
power sector to simulate the prospective medium-run growth and distributional implications
associated with a shift towards a higher share of renewables in the power mix up to 2025.
The following section explains the methodological approach and describes the key features of
the CGE models in a non-technical manner. Each model is calibrated to a social accounting
matrix (SAM) which reflects the observed input-output structure of production, the commodity
composition of demand and the pattern of income distribution for the country at a disaggregated
level at the start of the simulation horizon. Section 3 spells out the data sources for the
construction of the social accounting matrices and outlines the model calibration process.
Sections 4 and 5 present the results of the dynamic simulation analysis for Kenya and Ghana
respectively. In each case, we first develop a stylised baseline scenario that simulates the
evolution of the economy under current power sector expansion plans up to 2025 and then
contrast these baselines with alternative lower carbon energy scenarios. Furthermore, the
sensitivity of results to alternative projections for world market fossil fuel prices is explored.
Section 6 draws conclusions.