industry once public capital is suitably disaggregated.

# 2 The Contribution of this Paper

This paper revisits the question of the productivity impact of public infrastructure, employing a panel from South African manufacturing industry. In particular we investigate the question of whether different forms of infrastructure have a differential impact on productivity growth, whether public capital has both a direct and an indirect impact on productivity growth, and whether controlling for the potential endogeneity of infrastructure has a significant impact on the estimated impact of infrastructure on the direct and indirect productivity measures.

Using South African manufacturing data offers a number of significant advantages in addressing these questions. First, Perkins et al. (2005) has already provided a comprehensive description of particular pattern of economic infrastructural developments in South Africa since 1875. Figure 1, which shows the long-term development of selected infrastructure measures in the form of indices, provides a summary account, and suggests a series of sequential periods of infrastructure roll-out in South Africa. The first wave of infrastructural development was railways over the 1875—1930 period, after which there was little change in the route-kilometer railway line distance — though rolling stock continued to increase. The second take-off in infrastructure investment was in inter-city roads, which reached a plateau around 1940, after which the focus was on the paving of national and provincial roads. In the 1920s and 1930s growth in road traffic far exceeded growth in rail transport, and with the paving of roads after 1940 road traffic continued to grow faster than rail for the rest of the century. While ports constitute South Africa’s oldest form of infrastructure, substantial expansion in port capacity was constrained up to the 1970s, at which point two new ports two new ports were constructed, doubling the volume of cargo handled. The final phase of infrastructural development was in telephones and electricity. While the average growth rate for fixed phone lines dropped in the 1960s, it rose again in response to the introduction of information and cell phone technology.

Second, on the basis of aggregate evidence Fedderke, Perkins and Luiz (2005) has already confirmed not only a positive impact of infrastructure on aggregate economic growth for South Africa employing time series analysis, but has established the importance of controlling for feedback effects from output to infrastructure investment. In addition, Bogeti ́c and Fedderke (2006b) provides a natural framework in terms of which the simultaneity of the infrastructure measures employed in this study emerge in a demand for public capital framework, which finds confirmation for South African manufacturing industry. For our purposes, we therefore start not only with the prior that the infrastructure measures will require instrumentation, but we have strong guidance from the literature in terms of likely suitable instruments that can be employed in estimation.

Third, as demonstrated by Figure 1, the economic infrastructure component of South Africa’s gross fixed capital formation and fixed capital stock of the public sector (both general government and public corporations) published by the South African Reserve Bank, both demonstrate a longterm deterioration: from the mid-1970s in the case of investment, and from the mid-1980s in the case of fixed capital stock. Specifically, the investment per capita fell from R1 268 in 1976 to R356 in 2002 (in 1995 prices), a collapse of 72%! As a percent of GDP, investment fell from 8.1% of GDP to 2.4% of GDP, which lies well below the international benchmark of approximately three to six per cent identified by Kessides (1993). The implication is that a finding of negative impacts from public infrastructure capital on our productivity measures should have low probability, at least for the sample period of this study. For a middle-income country the stock of public capital is relatively low, raising the probability that the emerging manufacturing sector of the country should still be experiencing positive productivity gains from infrastructure investment. This provides a set of natural restrictions in estimation, that aids the search for the appropriate specification to be estimated.

Finally, South Africa is a developing country for which infrastructure data is available for long 4