**Figure 8. Access to Water and Sanitation and Income per Capita**

- **a. Improved water source b. Improved sanitation facilities**

<!-- Start of picture text --> 2008 - 2012 Benchmark (average) 2008 - 2012 Benchmark (average)<br>ZAF GABMUS<br>MWIGINRWABFAZWEMLIGMBUGABENSENLSOCMRCIVGHA MWIRWAZWEGMB SENCMR ZMB AGO ZAF GABMUS<br>NER TGO TZA KEN ZMB SDNNGA ETHMOZ GINBFAMLIUGABEN LSOKENCIV SDNNGA<br>MDGETHMOZ AGO MDGNER TGO TZA GHA<br>-3 -2 -1 0 1 2 -3 -2 -1 0 1 2<br>GDP per capita GDP per capita<br>90% CI Linear Fit 90% CI Linear Fit<br>EAP ECA IND LAC MENA SA SSA EAP ECA IND LAC MENA SA SSA<br>R-sq: 0.6172; Observations 94; Using PWT 9.0 R-sq: 0.7116; Observations 93; Using PWT 9.0<br>Adjusted by demographic and geographic features. Adjusted by demographic and geographic features.<br>.4 2<br>.2 1<br>0<br>0<br>-.2<br>Access to Water<br>Access to Sanitation-1<br>-.4<br>-.6 -2<br><!-- End of picture text --> _Sources:_ 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.

# **C. Growth benefits of closing the infrastructure gap**

In academic or policy circles, few experts would dispute the view that infrastructure development fosters growth. However, there is no consensus on the magnitude of the effect and the factors that shape it. Starting with Aschauer (1989), there is a massive empirical literature that focused on the impact of infrastructure on the level and growth rate of aggregate output or productivity. One strand of this literature examines the long-term growth impact of infrastructure —primarily using a reduced-form growth regression framework that links long-term growth to indicators of infrastructure, public capital or public investment.<sup>12</sup> Growth regressions have used either monetary measures of public capital and/or investment as well as physical indicators of infrastructure stocks. Using physical indicators renders invariably significant growth effects. Some studies have focused on single-sector analysis (typically, indicators of telecommunications penetration or density) while others have used synthetic indicators that capture stocks of physical infrastructure in different sectors —say, telecommunications, electric power, and transport.

This section looks closely at the growth benefits from improved infrastructure development. It consists of three different sub-sections: first, it reviews the current evidence on infrastructure in SSA; second, it presents a methodology to estimate the growth returns from infrastructure, and finally, it calculates the potential benefits of growth effects from narrowing the infrastructure gap.

## **C.1 What the empirical evidence tells us about infrastructure in Sub-Saharan Africa**

Most of the empirical literature on the growth effects of infrastructure in Sub-Saharan Africa has primarily relied on examining the real effects of the _transportation sector_ —despite the data availability problems. The region has been experiencing rapid demographic changes. Major urban areas are densely populated and still have poor road and rail networks while farmers in rural areas have limited opportunities due to their lack

> 12 The growth regression approach often includes standard control variables from the empirical growth literature (see Calderon and Servén 2004, 2010).

_Infrastructure in Sub-Saharan Africa - 19_