|||||covered). These factors account for 90% of<br>differences in costs.<br>Makes a cost based case for mergers of some of<br>the companies.<br>Documents lack of incentives of operators.|
|---|---|---|---|---|
|Peru|45 operators<br>1998-2000|Alva and<br>Bonifaz (2001)|DEA with 2<sup>nd</sup><br>stage regression<br>analysis of<br>efficiency<br>measure|Ranking of operators for a 3 years period.<br>Find returns to scale.<br>Find important role for environmental variables.|

(*) SPF: Stochastic Production Frontier; SCF Stochastic Cost FrontierDEA: Data Envelopment Analysis; TFP: Total factor productivity index number; For the papers focusing on cost, labor cost, other input costs, production levels, number of clients, population density, water sources (e.g. surface, ground,...), and quality variables tend to be standard. Increasingly also, analysts add environmental variables, including institutional characteristics. Note that these models are sometimes run with quadratic forms to get non-linearities in the technology, including possible returns to scale. For the papers focusing on the production side of the business, employment, fuel and other energy consumption, network size and other expenses are the most common found. The specific functional forms and variable choices are of course driven by data availability.

There are few overall policy lessons from these few studies but those emerging from a comparison of experiences across regions and countries are important. Probably the most important lesson is that the econometric evidence on the relevance of ownership suggests that in general, there is no statistically significant difference between the efficiency performance of public and private operators in this sector. The only paper on Asia (Estache and Rossi (2002) and the paper using the latest data on Africa (Parker and Saal (2004) are both quite robust at that level. An earlier econometric study on the efficiency of the African companies found, with a much smaller sample, some superiority for private operators but the efficiency effect of ownership was much lower than the effect of good governance in the sector. This mixed review of the efficiency payoff of private sector participation may have to be correlated with the observation that water is the sector with the highest rate of renegotiation. According to Guasch (2004), 75% of the water contracts signed in Latin America during the 1990s were renegotiated.

The story is however not that simple. Indeed, the first published country specific paper on this issue in this sector shows the high efficiency payoffs of the privatization policy for 4 Argentinean provinces based on the calculation of a Malmquist index (Estache and Trujillo (2003)). Annual efficiency gains vary from 2.3% for the largest concession to 13.5% for one of the smaller ones. Note that the first average is over an 8 year period and the second over a 3 year period. The difference is at least partially explained by the fact that the biggest bang for the buck of privatization in these industries is immediately after the reform since the operators know that they will eventually have to share with the users the efficiency gains as part of a scheduled tariff revision. This is in fact illustrated by Seroa da Motta and Moreira (2004) in their recent working paper when they document that private operators stimulate a quick catching up but don’t get associated to frontier shifts more than public operators in this sector in Brazil.

The second lesson to emerge is that there is a clear case for increased yardstick competition in the sector, independently of whether the private sector plays a crucial 12