address other regulatory issues.<sup>13</sup> But both of these areas go beyond the scope of this paper and are hence not reviewed here.

# _3.1.1. Energy_

The literature on this sector is growing fast but it has many common features. We identified almost 30 papers, reported in Table 2, covering full systems, generation only or distribution only. Most of the papers are on the electricity sector. Only two deal with the gas sector in developing or transition economies and both are on Argentina, the only country in which a tariff revision including a discussion of the revision of the cap actually took place.<sup>14</sup> Most papers focus on a single output. In most cases, they focus on the production side of the business but cost data are much more difficult to obtain. DEA is the most common approach. There is an unusually large number of papers relying on both nonparametric and parametric approaches to check the robustness of the results or of the policy conclusions.

Most of them (over 50% of the papers) rely on country specific data. This is because in many countries, the reforms have created many business units which can be compared with each other. Among developing countries, Latin America is the most studied region, reflecting the payoff of the efforts made by the Latin American Association of Energy Regulators to generate comparable data.

In general, when authors focus on the cost side of the business, the main difference across papers comes from the differences of the expenditure type they focus on: operational, capital expenditures or total expenditures. The papers focusing on the production side deal with either the number of clients served or total energy sold. Since in many countries the operators tend to control more the energy supplied than the number of customers--in general operators are subject to connection obligations, not necessarily to service obligations at any tariff-- the most common proxy for output is energy sold.

As in all other sectors, the choice on the input side is generally driven as much by data availability as it is by economic principles. The number of employees is the standard labor input and is easily obtained. For the capital inputs, however, the options are more difficult. Transformer capacity is widely accepted as a required variable. Many authors also consider kilometers of distribution lines, which measure (with some approximation) the amount of network capital. There is however a recognition that it can reflect geographical dispersion of consumers as much as differences in productive efficiency. The main lesson is that network capital can thus be treated as an output or as an input but it is necessary to control for geographical dispersion. Generally, with a single equation production frontier, it is treated as an input.<sup>15</sup> As suggested by Kumbhakar and

> 13 The conceptual framework is presented in the book by Gasmi et al. (2002) and their 2000 article. An illustration for Argentina is provided in Benitez et al (2001).

> 14 This section is to a large extent a major update of the papers reviewed in Jamasb and Pollitt (2001). 15 Since physical measures of capital (as the ones used in this study) cannot capture all the capital equipment used in the production process (aside of the difficulties to account for differences in asset quality, age and composition), an alternative is to represent all capital in a single monetary measure. However, creating monetary measures of capital is problematic because accounting methods and revaluation policies are not uniform within organizations. Furthermore, there is still debate over the correct method of calculating the monetary value of capital.

6