that are likely to have included a growth or scale effect, while performance indicators, such as the percentage of transmission and distribution losses, that are unlikely to experience trend effects are included.

For the calculations on the effect of PSP on the selected indicators, most studies used a semi-log or double-log functional form, in which the log of the indicator was regressed on the policy dummy and on other variables. If the coefficient on the dummy variable is δ, then the percentage impact of the policy introduction (from 0 to 1) is equal to (exp [δ] −1). To convert a % change into an absolute number measuring the impact of policy it is necessary to multiply it by the mean value of the indicator before the policy was applied. The subset of studies that included data on the mean of the performance indicators did so only for the whole period (i.e. both pre- and post-reform) and some studies did not present any data on the mean. Studies that were carried out using a linear formulation yield the predicted change in performance, and this can be converted into a percentage change if the mean is available.

- (i) **Andrés et al. (2006)** analyzed a sample of distribution utilities pre- and post-privatization using a semi-log transformation. The study distinguished a transition period and a postreform period. The regression coefficients, implicit % changes, and mean values (for the whole sample) for the six indicators with significant results are shown in table 9.

Table 9: Impact of privatization on performance (Andrés et al. 2006)

|Performance measure|Mean|Transitio|n period|Post-transi|tion period|
|---|---|---|---|---|---|
|||Coefficient|% change|Coefficient|% change|
|Connections per employee|559|0.442|56|0.810|125|
|Energy sales per employee (MWh)|2343|0.474|61|0.819|127|
|Distribution losses %|15.3|−0.031|−3|−0.172|−19|
|Duration of interruptions (hours/year)|25.3|−0.144|−15|0.488|−62|
|Frequency of interruptions/year|22.6|−0.107|−11|−0.415|−51|
|Coverage Residential connections/100<br>households|75|0.053|5|0.810|14|

The materiality of the results can be judged by comparing the overall mean values with the increase (or decrease) implied by the % change figures. For example, connections per employee rose by 56% (relative to pre-reform values) in the transition period, and by 125% relative to the pre-reform value in the post-reform period. Given that the mean connections per employee over the whole period were 559, the post-privatization value increased by 700. In fact, since the pre-reform mean will have been lower than the post-reform mean (because of this increase in performance) and hence lower than the overall mean, the value of 700 is an overestimate. Nevertheless, an increase of 125% of the pre-reform connections per employee is a very substantial change in performance. The transition value, although a much lower percentage figure, is also substantial.

Energy sales per employee (MWh) show a similar picture, and it appears that employment must have been sharply reduced to achieve these results.

Coverage shows a 14% post-reform increase. Based on the overall mean of 75 connections per 100 households, the post-reform value would have been around 85—but given that the 42