INFRASTRUCTURE AND GROWTH IN AFRICA of the gross domestic product, GDP), trade openness (real value of exports and imports as percentage of GDP), and governance (International Country Risk Guide, ICRG, index of institutional quality).

(c) Stabilization policies proxied by the lack of price stability (average inflation rate) and the size of government burden (as captured by the general government’s real consumption as a percentage of GDP).

(d) External factors approximated by terms-of-trade shocks and time dummies that capture other global shocks.

In addition to this set of determinants, we include our variable of interest: _infrastructure development_ . This dimension is captured by our aggregate indices of infrastructure stock and quality, as previously described.

Our empirical evaluation uses an unbalanced panel data set of five-year period observations over 1960–2005, with 580 observations in total. Before discussing our regression results, we should note that the correlation between economic growth and our aggregate index of infrastructure stock is equal to 0.22. The correlation between growth in output per capita and individual stocks is also positive (0.17 for main telephone lines, 0.13 for electric-power-generating capacity, and 0.27 for the total length of the road network). In addition, growth in output per worker is also positively correlated with the aggregate index of infrastructure quality—the degree of association is 0.32. The individual components of the quality index also have a positive association with growth in output per worker: 0.22 for telecommunications quality, 0.18 for energy provision, and 0.23 for road quality.

# Regression analysis

We ran growth regressions augmented by aggregate indices of infrastructure stock and infrastructure service quality, and the results are reported in table 2. We used the GMM-IV system estimator proposed by Arellano and Bover (1995), and Blundell and Bond (1998). This tackles problems of unobserved time and country effects and, likely, endogeneity. Note that we used _external_ instruments for infrastructure to avoid getting inconsistent estimates for our parameters of interest. Before we discuss the results obtained in table 2 we should point out that the specification tests (Sargan test and second-order correlation test) validate our moment conditions so that we can use our regressions for statistical inference.

Our coefficient estimates in table 2 suggest that: (a) there is evidence on conditional convergence for the real output per worker; (b) economic growth is enhanced by a faster accumulation of human capital, deeper financial systems, higher institutional quality, and favorable terms-of-trade shocks; and (c) growth is adversely affected by higher inflation and heavier government burden. We should also note that trade openness does not show a robust relationship to growth.

Regarding _infrastructure development_ , we find that the aggregate index of infrastructure and the quality of infrastructure services have a positive and robust relationship to growth per capita. The relationship between growth and infrastructure stock is positive and robust to changes in the aggregate index used (see the results in columns [ **IK** 1] through [ **IK** 2a]). The estimated coefficient of the aggregate infrastructure stock is positive and significant, regardless of the aggregate index of infrastructure stock used. Thus, our results suggest a positive contribution of infrastructure development to productivity 10