concentrated rural, and low-density rural (“rural expansion”). These costs were annualized over 30 years to yield annualized capex at a real discount rate of 12 percent, yielding 2.1, 2.2, 4,7, 4,6, 3.2, and 4.9 U.S. cents per kWh billed, respectively. The regulator allows T&D losses of 10 percent, the same as the benchmark losses in this study. For simplicity, this study took costs for median-density urban and the two rural areas for urban and rural, respectively, adjusted the discount rate to 10 percent, and added an additional 25 percent to capture higher costs in SSA. These adjustments yielded 2.3 U.S. cents and 4.2 U.S. cents per kWh billed at benchmark performance for urban and rural areas, respectively. For discount rate sensitivity, these costs were adjusted upward or downward accordingly depending on the discount rate tested. The split between urban and rural delivery of electricity was approximated by taking the share of the total numbers of people connected to electricity (grid or otherwise) in urban and rural areas in 2012 in each study country according to the estimation provided in _Global Tracking Framework 2015_ (World Bank 2015). These figures were scaled according to the share of low voltage sales in each country. Where sales breakdown is provide by category, LV sales are estimated by removing sales to industry, mining and export customers from total sales. Where no breakdown of sales is available, a share of 65 percent was assumed except in the Central African Republic, Comoros, and The Gambia where 100 percent of sales are assumed to be supplied at low voltage. Finally, these figures were adjusted upward or downward to account for actual T&D losses in each country.

For meters, ownership and responsibility for installation was assumed to rest with the distribution utility. A cost estimate of US$100 for new meter installation in Kenya in 2015 was used for all countries. Costs were assumed to be paid through cash flow rather than debt-financed. Annual cost of new meters was calculated by multiplying the number of new customers by US$100, where the number of new customers was taken to be the difference between the number of customers in the reference year and the year earlier. Information on the number of customers was not available for seven countries in the sample (Burundi, Central African Republic, Comoros, The Republic of Congo, Nigeria, the Seychelles, and Sudan).

# A1.5 Procedures and assumptions applied to account for sector structure

As described in section 2.3, sector structure is key for estimating opex and capex. To estimate the opex to the main utility, the starting point is the financial statement of the main utility, listed in annex 2. The procedures and assumptions applied to take account of sector structure are outlined in this section.

In the simplest case of one dominant state-owned vertically integrated utility, only one financial statement needs to be analyzed. For utilities that provide multiple services such as electricity and water, if the accounting systems do not break down costs by product line (8 out of 9 utilities), shared costs are pro-rated according to the share of electricity sales in total revenues from product sales. Relevant assumptions are detailed in annex 2 (see for example The Gambia).

In cases with more than one utility, the following procedures were applied:

- Payments for majority-private generation companies are assumed to be cost-reflective<sup>9</sup> and treated as 100-percent opex for the main utility. Power purchases are typically—but not always—cost-reflective, with an allowed return satisfactory to both the regulating body and the private investor. Imports and regional SPVs are also assumed to be cost-reflective. Identifying

> 9 This assumption is not valid in Nigeria, but a different methodology was followed for Nigeria, as explained below.

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