**Table 2: Typology of losses**

||**T&D losses (up to the point of sale)**|**Bill collection losses (after point of sale)**|
|---|---|---|
|**Technical**|Technical losses including transmission losses,<br>substation losses, under-billing due to inaccurate<br>meters due to lack of maintenance, primary and<br>secondary distribution losses|Not applicable|
|**Nontechnical**|Unmetered consumption due to theft, lack of meters,<br>meter tampering, faulty meter reading|Under-collection of bills due to faulty bill distribution<br>and inadequate systems to manage bill collections|

_Source_ : World Bank staff.

For underpricing, benchmark tariffs are needed against which existing tariffs are compared. There is a large and rich literature on what would be efficient utility pricing. While setting prices at marginal costs is efficient, there are increasing returns to scale in the power sector, which could result in the average cost being higher than the marginal cost. Using a single price equal to the marginal cost could result in large financial losses for the utilities. Coase (1946) argued that multi-part pricing would provide efficient pricing under such circumstances, whereby additional units (of electricity) are purchased at the marginal cost, and the utility recovers full costs by levying a service charge in addition. When averaged over all consumers, the average tariff per kWh would equal the total unit cost. Applying these principles would require computing the cost of service based on a least-cost, long-term expansion plan. Such modeling for each country in SSA is beyond the scope of this study.

For simplicity, this study assumes that underpricing is the difference between revenues reflecting prudently and reasonably incurred expenses for efficient management of the power supply chain (but before optimizing the power generation mix and associated transmission infrastructure using least-cost, long-term, sector-wide planning) on the one hand and revenues currently charged (but not necessarily collected) on the other. This study, as the AICD, assumes that efficient operation would allow for total losses of 10 percent of total electricity dispatched to the grid before billing and zero under-collection of bills.<sup>5</sup> To compute underpricing on a unit basis—per kWh so billed—the computed average price needs to be compared with the volume-weighted average of the tariffs being charged. An accurate calculation of the volume received by each consumer category would be difficult if there are large commercial losses. The assumption about optimal staffing levels in this study is different from that in the AICD, as explained below.

# 2.2 Methodology in the present study

This study follows the same approach as that used in the AICD.<sup>6</sup> A quasi-fiscal deficit is the difference between the net revenue of an efficient utility (Rbenchmark) and the net current revenue (Rcurrent). Let capex designate benchmark capital expenditure, which is equivalent to current capex in this study. Let opexbenchmark designate benchmark operating expenditure, and Q designate dispatched kWh. The tariff at benchmark performance, tariffbenchmark, in this study is (capex + opexbenchmark)/0.9Q and the revenue of an efficient utility is tariffbenchmarkx0.9Q, where 0.9 accounts for combined transmission, distribution, and billing losses of 10 percent (level considered for benchmark performance). Its net revenue is Rbenchmark –

> 5 In effect, this assumption is equivalent to a total combined revenue loss of 10 percent from T&D and bill collection losses. If T&D losses are smaller than 10 percent, bill collection efficiency can be lower than 100 percent as long as the combined loss is 10 percent.

> 6 The methodology used in the AICD is described in section A1.1 in annex 1.

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