MAKING SENSE OF AFRICA’S INFRASTRUCTURE ENDOWMENT: A BENCHMARKING APPROACH Here we perform a country-level benchmarking exercise for infrastructure stocks in SubSaharan Africa, comparing them with a global peer group of developing countries. The paper extends and deepens the work of Bogetic (2006) for the countries of the Southern African Development Community (SADC), in particular by using regression techniques to control for a wide range of differences in the operating environment faced by particular countries. In this way, the benchmark against which each country is compared is individually adjusted to control for a comprehensive set of economic, demographic, geographic, and historic conditioning factors.

The analysis is based on a panel dataset of all developing countries for the years 1960 to 2004. Developing countries are defined to be those in the low-income, lower-middle-income, and upper-middle-income categories as defined by the World Bank. Data availability varies over the period according to the specific infrastructure variable under consideration. Thus, road data are available from 1960, ICT data from 1970, and electricity generation capacity data from 1980. In the case of water and sanitation, only two time periods are available (1990 and 2002), while for access to electricity no consistent time series could be found. The data are drawn from a variety of global sources, including the World Bank’s _World Development Indicators_ , the International Telecommunications Union, and the World Economic Forum’s _Global Competitiveness Report_ , among others.

Our study contributes to the international benchmarking literature in three ways. In terms of scope, it is the first study to benchmark the entire region of Sub-Saharan Africa, with an emphasis on comparing regions of the developing world as well as the diverse subregions of Africa. It is also the first study to base its predicted infrastructure levels on a panel dataset and to control for potential endogeneity of regressors.

The benchmarking exercise compares each country’s actual infrastructure endowments to an expected, or predicted, value based on its socioeconomic structure. The predicted values are derived from an econometric model that explains variation in infrastructure levels among developing countries based on a set of economic, demographic, and structural variables. This exercise produces a measure of infrastructure endowment that controls for differences in all of the socioeconomic variables included in the model. Thus, for example, it would be incorrect to explain a lower-than-predicted infrastructure endowment for a particular country in terms of the country’s low income, because the model includes income as an independent variable. Hence the result already controls for differences in income. Note that here the concept of an expected, or predicted, infrastructure level does not refer to any concept of demand, since actual levels of infrastructure may also be driven by supply factors. Moreover, the expected value should not be treated as an ideal; it simply expresses the average endowment of countries with comparable characteristics.

Each country’s infrastructure endowment is measured by the deviation between its actual endowment and the endowment predicted by the model (equation 1). A positive deviation indicates that the country outperforms the benchmark provided by the econometric model (i.e., the average for the relevant peer group) and vice versa. The larger the absolute size of the deviation, the greater the extent of the corresponding over- or underachievement.

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