infrastructure is held constant, which implies increasing returns in all inputs. This externality is captured by the effect that infrastructure has on the level of output. Another way in which infrastructure can have a beneficial impact is by raising the total factor productivity of all inputs (Hulten and Schwab, 1991), which we refer to as the factor productivity externality. Here infrastructure allows these private factors of production to work more efficiently raising their marginal product. For example in the case of workers, they waste less time travelling to work if a country has good transport infrastructure, resulting in an increase in welfare.
While these are the most natural ways of modelling the impact of infrastructure on growth some other approaches have also been used: for example, infrastructure impacts on economies by connecting them. Thus, Kelly (1997) argued along Smithian lines that infrastructure allows for an expansion of markets which in turn increases specialisation, which improves efficiency and therefore growth. In this model growth is subject to threshold effects, requiring sufficient infrastructure to properly integrate markets, which then increases specialisation. Another way in which infrastructure has been incorporated into growth models is to assume that infrastructure reduces the cost of intermediate inputs by fostering specialisation (Bougheas, Demetriades and Mamuneas, 2000). This model yields a non-monotonic relationship between infrastructure and long-run growth, which means that there is an optimal stock of infrastructure beyond which additional investment will be detrimental to growth. Thus, countries with a lower stock of infrastructure will have the highest return to additional infrastructure while those with a stock of infrastructure that is above the growth maximising level will actually grow slower with more infrastructure investment. Another important finding of this model is that infrastructure accumulation is very productive if the tax rate is low and counter productive if the tax rate is too high.
In general it is important to note that while infrastructure has beneficial public good characteristics, it has to be financed through taxes and it is therefore important that the tax revenue is spent on infrastructure that is more productive than any other expenditure that could have been financed by the tax take. This argument has been supported by empirical research, which shows that certain types of infrastructure impact more than others on output. For example, Pereira (2000) finds for the USA that electricity and gas facilities have the highest return, while conservation structures have the lowest return. He also finds a relatively small impact for roads infrastructure, which might surprise some people, but which accords well with the discussion above. The USA already has a highly developed roads network and is therefore unlikely to benefit much from additional roads.
Not every sector benefits equally from infrastructure. Thus agriculture is often found to have the lowest return to public infrastructure (see Pereira and Roca-Sagales, 2001). Thus, ceteris paribus, a country with a higher proportion of agriculture will benefit less from infrastructure than one where agriculture is less important.
MACRO-ECONOMIC BACKGROUND 57
Furthermore, how efficiently a given stock of infrastructure is used also impacts significantly on the effect that infrastructure has as was noted by Hulten, (1996). He shows that, a 1 per cent increase in the efficiency of use has a significantly larger impact than an equivalent increase in the stock of infrastructure.
There is now a large body of literature that has estimated these effects, focusing largely on the estimation of the rate of return to infrastructure. This is inferred from the output elasticity of infrastructure, and the latter is estimated under the assumption that infrastructure enters the production function as a public intermediate input. An alternative approach involves the estimation of a cost function and associated factor demand functions, which yields shadow values for infrastructure.
The only published study for Ireland is that by Kavanagh (1997) who uses the production function approach in conjunction with modern time series methods. She finds an output elasticity of 0.14, which, however, was not statistically significantly different from zero. In other words, her results suggest that a lack of infrastructure would not result in lower levels of output than a situation where there is adequate infrastructure. This finding conflicts with the view of numerous commentators who in recent years have asserted that Ireland faces a serious infrastructure deficit. The existence of such an infrastructure deficit accords well with the evidence on increases in congestion, travel times, as well as environmental damage. If the assertion that Ireland indeed suffers from an infrastructure deficit is correct, then the rate of return from investing in infrastructure should be high, provided that this investment does indeed address this deficit. Denny and Guiomard (1997) on the other hand find unrealistically high output elasticities, which range from 0.93 to 6.3. As part of this Mid-Term Evaluation of the NDP a special study on the returns to infrastructure investment was carried out (Morgenroth, 2003b) which produces more realistic and robust estimates of the macro-economic returns to infrastructure.
RESULTS
Details of the equations estimated are given in Morgenroth (2003b). Overall the results suggest that, while roads infrastructure has a direct positive impact on output and consequently a positive return, water and sewerage infrastructure does not appear to have such an effect. This might be explained by the fact that this type of infrastructure has an indirect effect through improvements in quality of life and thus, the modelling strategy adopted here is not able to pick up these effects.
Given this general result, the results also suggest that the manufacturing sector benefits more than the services sector from road infrastructure investment. At first this might seem puzzling since the services sector includes freight and transport. However, these account for only a small share of the sector, which is dominated by other activities such as retail and wholesale and banking. Thus, this result is not surprising and one would indeed
expect a higher return in the manufacturing sector. This result supports the strategy followed in the study to disaggregate the data into the two sectors and to estimate separate models.
An important result emerges on the return that can be measured by the marginal product of investment, i.e. the return of a one-unit increase in the stock of infrastructure. This is readily calculated from the results. These indicate that at no point do the returns to road infrastructure exceed those of private capital. However, the results indicate that, while the returns over a long period were no higher than the long-run interest rate, during the 1990s they rose very substantially to an average of 30 per cent. While these returns appear high they point to the severe infrastructure deficit, which is putting a constraint on the economy as a whole. Indeed it is well known that when investments remove bottlenecks the return is very substantial as such investments not only have a direct return, but they increase the return of the existing infrastructure. Thus, the completion of some projects such as the Dublin port tunnel or the remaining section of the M50 are likely to have very substantial returns as they affect the efficiency of the existing sections of the M50.
The results from Morgenroth (2003b) are incorporated in the analysis in the next section. The productivity gain for each sector is imposed on the HERMES model and the resulting broad economic benefits are estimated.
T
he micro-economic studies described in the previous sections provide an important quantification of the positive externalities arising from infrastructural and human capital investments under the NDP/CSF. In this section we use the results from these studies as inputs into an assessment of the full macro-economic impact of the NDP/CSF.3.5
Macro-
economic
Impact
Figure 3.5: Source of Funding 2000-2002
EU funding 9.0%
Public Co-financed 5.0%
Public Non Co-financed 86.0%
MACRO-ECONOMIC BACKGROUND 59
Here we consider the impact of all public expenditures under the NDP over the period 2000-2002. This includes all public monies, both national and EU. The vast bulk of this money, 86 per cent, is national non co-financed expenditure. Funding from the EU (including the CSF plus the Cohesion Fund, TENS (Trans- European Networks) and the EEA Financial Mechanism) amounts to 9 per cent of the total, the remaining 5 per cent comes from national public co-financing of these Measures.
Our analysis concentrates on total national public expenditure, referred to as the NDP. In addition, we examine separately the impact of a subset of the NDP, the Community Support Framework (CSF). The CSF includes EU and national public co- financed expenditure. Finally, we also examine the impact of EU funding alone, excluding the Irish government contribution, referred to as EU. Table 3.9 shows the levels of expenditure under these three definitions.23 The 2000-2002 NDP spending is a very
substantial investment programme, accounting for just under 6 per cent of GNP in 2000, rising to 7.6 per cent by 2002. As shown in Figure 3.5 above, CSF expenditure accounts for a relatively small portion of this total. Nevertheless it represented an injection of 1.2 per cent of GNP in 2002, over 60 per cent of which was funded by the EU.
Table 3.9: Public Expenditure under the NDP
NDP CSF EU 2000 2001 2002 2000 2001 2002 2000 2001 2002
Total, € million 5,161 6,932 7,702 562 968 1,219 354 604 739 % Of GNP 5.9% 7.2% 7.6% 0.6% 1.0% 1.2% 0.4% 0.6% 0.7%
We use the ESRI HERMES medium-term macro-economic
model (Bergin et al., 2003) to analyse the impact of the 2000-2002 public expenditures under the NDP, CSF and EU. This provides a sufficiently comprehensive and detailed framework to quantify the substantial demand side impact of the NDP on the economy. Furthermore, it can also be used to assess the longer-term supply- side effects of the NDP, i.e., the impact on the long-term productive capacity of the economy. Initially such supply-side effects are much more modest than individual year demand-side effects. However, because they outlive the lifespan of the investments themselves they are ultimately more important to the long-run growth potential of the economy.
We begin this section by reviewing briefly the channels through which the NDP influences the economy. This section also elaborates on the methodology used to aggregate individual investment programmes into different economic categories for input into the HERMES model, and discusses how we incorporate the results of the studies on human capital and infrastructure in
23 The figures for the EU for 2000 do not include expenditure carried over from
Sections 3.3 and 3.4 above to estimate supply-side effects. The final part of this section presents our results.
METHODOLOGY
In assessing the impact of an investment programme on the economy, it is important to clearly define the counter-factual or alternative scenario. This is not unproblematic, since the assumption of “no NDP” is clearly unrealistic – it is inconceivable that the state would have undertaken no investment over such a sustained period. However, it does have the advantage of simplicity and captures the likely “maximum” impact of the NDP. As a starting point we use the “with NDP” scenario, this represents the state-of-play at present. We use the latest forecasts from the Medium Term Review 2003-2010 as the “with NDP” scenario for the years 2003 out to 2015. We then run a series of “what if” simulations designed to extract the investment policy shocks. For example, for the NDP simulation we set the NDP 2000-2002 expenditures at zero and re- simulate the model. For the EU simulation we set the EU 2000- 2002 EU funded expenditures at zero and re-simulate the model. The effects of the NDP or EU are then defined as the difference between the “with” and “without” scenarios.
The demand side effects arise from the spending of the NDP: employment of builders, teachers etc. on undertaking the investment. The key to the success of the NDP/CSF, however, lies in the extent to which the level of output and employment is permanently raised as a result of the investment. The extent of this “supply side” effect can be compared to the initial injection to measure the “rate of return” on the public investment.