assessments are needed to facilitate debates between governments and operators on the specific levels of risks associated with any project and on their distribution. This debate has already started in Argentina, Brazil, Kenya, Mali, Mexico or Uganda where electricity, ports or water operators and regulators or governments are arguing about quantitative estimates of the rate of return required by operators to match the demands of their equity and bond holders.

This paper’s main goal is to provide a quantitative baseline of the risks perceived between 1998 and 2002 by private providers for a range of infrastructure services in a range of developing countries based on a sample of 120 companies. We do so by calculating the hurdle rates for each one of these operations (that is, the risk-adjusted cost of capital faced by the operators). The data available do not allow the assessment of the financial viability of these operations but allow a comparison of the returns on equity with the cost of equity for the same sample. This comparison is used to highlight the origin of the concerns of private investors.

The paper is organized as follows. In section 2, we present the methodology and the data. Section 3 presents the estimates of the cost of capital. Section 4 compares the cost of equity to the return on equity to get a sense of the returns that are consistent with the risks perceived by investors in infrastructure. Section 5 presents the results on the cost of capital, and section 6 on the comparison between the cost of equity and the return on equity. Section 7 privides some insights on the volatility of returns and costs. Section 8 reviews the evolution of the indicators over time. Section 9 concludes.

# **2. The Sample of Companies**

We focused on companies active in four infrastructure sectors: energy, water, ports and railways. We only used publicly available information on the Web. Indeed, various commercial databases and a Web search provided us with the balance sheets, financial statements and related information for 120 companies. The information was checked whenever possible either on the site of the companies or on the sites of their regulators in the countries in which they are operating. We also relied on reports generated by credit rating agencies or investment banks to cross reference the information. The sample covers 31 developing countries in five regions: Sub-Saharan Africa & MENA (11), South Asia (12), East Asia (30), Europe & Central Asia (12), Latin America and the Caribbean (55). Latin America and East Asia provide, as expected, the largest number of companies since these are the two regions which generate over 75% of public-private partnerships over the 1990s. The distribution of the sample per income groups or geographical regions, per sector is summarized in Table 1.

The table points clearly to the limited statistical significance of the sectoral observations for the water, port and rail sample in Africa, South Asia and Eastern Europe. Classifications by country income group (low-income, lower-middle-income, upper-middle-income) were less problematic because they take all countries with the same average risk level and compare them with appropriate hurdle rates, which have the same average risk level as well. The sample size for the low income group is however also limited for all sectors, except energy.

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