for 74 countries for 1998–2002 and 65 countries for 2008–12. Still, there is a positive and significant relationship between income per capita and rail density. For 2008–12, South Africa continues to have the highest rail density in the continent, and its rail network remains over the international norm. The adjusted rail density is larger than those of countries with larger gross domestic product per capita (for example, Chile and Malaysia, among others). By contrast, Côte d’Ivoire, Cameroon, and Burkina Faso have underperformed relative to their level of income per capita, and also show the lowest density of the railroads in the region.<sup>11</sup>

# **Infrastructure Quality**

_Telecommunications_ . Figure 4 depicts a positive relationship between international Internet bandwidth (in bits per second per Internet user) and real income per capita after controlling for demographic and geographic indicators. One finding that emerges from this analysis is that the partial correlation between Internet density and income per capita has increased over time (when comparing 1998–2002 vis-à-vis 2008–12), and most countries in Sub-Saharan Africa are above the international norm in the latter period.

In 2008–12, South Africa registered an astounding increase in Internet density, thus becoming the best performer in the region and a significant over-provider of these services according to the country’s level of development. Other MICs in the region (for example, Gabon, Nigeria, Angola, and Sudan) are below the international norm. Finally, when looking at LICs in the region, Ghana, Cameroon, and Lesotho have levels of Internet infrastructure quality that are way below what the international norm predicts for their level of economic development.

**Figure 4. Internet Traffic and Income per Capita**

<!-- Start of picture text --> 2008 - 2012 Benchmark (average)<br>ZAF<br>TGO SEN CIV GABMUS<br>ETH BFAMLI KEN NGA AGO<br>NER MOZMWIGINRWAZWEGMBUGABENTZA ZMB SDN<br>MDG LSO<br>CMR<br>GHA<br>-3 -2 -1 0 1 2<br>GDP per capita<br>90% CI Linear Fit<br>EAP ECA IND LAC MENA SA SSA<br>R-sq: 0.7136; Observations 94; Using PWT 9.0<br>Adjusted by demographic and geographic features.<br>4<br>2<br>0<br>-2<br>Bits per second per internet user<br>-4<br><!-- End of picture text --> _Sources: International Telecommunications Union’s World Telecommunication/ICT indicators; World Bank, World Development Indicators. GDP per capita is from Feenstra, Inklaar, and Timmer 2015. Note: CI = confidence interval; EAP = East Asia and the Pacific; ECA = Europe and Central Asia; GDP = gross domestic product; IND = Industrial Countries; LAC = Latin America and the Caribbean; MENA = Middle East and North Africa; SA = South Asia; SSA = Sub-Saharan Africa._ _Electric Power_ . The partial correlation analysis shows that countries with higher income per capita tend to have a lower percentage of power losses (that is, higher quality of electricity supply). For 2008–12, Mauritius, Cameroon, Ethiopia, and Mozambique are among the best performers in the region (with the lowest level of

> 11 Adding road and rail networks and assessing their performance as a whole would lead to similar results to those for the total road network. This analysis is not reported, but it is available from the team upon request.

_Infrastructure in Sub-Saharan Africa - 15_