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Olukayode Pitan, Managing Director and… June 24, Anders Bouvin, President and Group… March 4, Sign up to the International Banker newsletter. Full Name. Email Address. By subscribing I accept the privacy rules of this site. Home Issues This paper examines trends in infrastructure investment and financing in low-income developing countries LIDCs. Following an acceleration of public investment over the last 15 years, the stock of infrastructure assets increased in LIDCs, even though large gaps remain compared to emerging markets.
Infrastructure in LIDCs is largely provided by the public sector; private participation is mostly channelled through Public-Private Partnerships. Grants and concessional loans are an essential source of infrastructure funding in LIDCs, while the complementary role of bank lending is still limited to a few countries. Bridging infrastructure gaps would require a broad set of actions to improve the efficiency of public spending, mobilise domestic resources and support from development partners, and crowding in private investment.
The paper is part of a research project on macroeconomic policy in low-income countries supported by the U. The growth dividend and the distributional effect of this investment push cannot be taken for granted, as past experiences suggest see Section II , and many challenges lie ahead: infrastructure gaps are still large and bridging those gaps will require tackling several problems, in terms of additional financing and project selection and implementation.
Our main objective is to provide a multi-faceted picture of infrastructure development in LIDCs, covering the evolution of several physical indicators of infrastructure, the role of public and private sectors in delivering infrastructure, and its financing, including traditional and new sources. Then we look at the concurrent evolution of public saving and debt, tracing the main sources of financing for public investment.
Beyond that, the paper takes stock of infrastructure investment via Public-Private Partnerships PPPs , as well as official development financing and syndicated bank lending. Limited data availability prevents us from presenting a comprehensive quantitative picture of the modes of delivery and financing of infrastructure in LIDCs.
To partially overcome this constraint, we introduce a unique dataset on infrastructure investment in LIDCs—based on the results of a survey of IMF country teams—which collects novel information on public investment in infrastructure including its sectoral distribution , obstacles to investment scaling-up, reliance on PPPs, sources and terms of financing for major projects, and other aspects of infrastructure investment for a subset of LIDCs.
We believe that the use of several complementary datasets allows us to shed new light on some key issues related to delivery and financing of infrastructure investment. In addition, selected case studies illustrate experiences with public infrastructure provision Ethiopia , private provision solar micro-grids in Kenya , and PPPs hydropower in Lao PDR.
The next section sets the stage by selectively reviewing the empirical literature on the economic effects of infrastructure, pointing out potential downside risks in terms of growth dividend and distributional effects. Section III provides an overview of the evolution of various measures of quantity and quality of infrastructure in LIDCs since , making clear that infrastructure in LIDCs lags behind that in emerging markets on a number of dimensions.
Section IV explores trends in infrastructure investment and financing over the last 15 years. It starts by looking at public investment and saving, taking advantage of broad availability of these indicators. It then zeroes in on public investment in economic infrastructure using survey data. The rest of the section covers private participation in infrastructure provision, the role of official development finance, and cross-border syndicated bank lending for LIDC infrastructure.
The last section concludes. Since the s there has been a wide body of literature looking at the possible development gains from investing in infrastructure World Bank, The economic importance of infrastructure investment has been analysed both at project and macro levels. At a project level, the focus is on the social cost-benefit of infrastructure projects and their implied internal rate of return see Marcelo et al. The social cost-benefit analysis often tries to account for negative externalities.
At a macro level, the impact of infrastructure investment is analysed using aggregate production function with the assumption that infrastructure is complementary to other inputs in the production function see Aschauer, ; Gramlich The macro literature shows that improvements in infrastructure could raise productivity, stimulate private investment Cavallo and Daude, , and facilitate domestic and international trade Bougheas et al.
However, public investment could be a poor proxy as it is composed of economic and social infrastructure spending as well as government investment on state owned enterprises. In addition, the link between spending and infrastructure build up could be very weak in cases where public investment efficiency is low due to poor project selection, non-transparent procurement processes, and corruption Pritchett, ; Tanzi and Davoodi, Their estimate shows that a 10 per cent increase in infrastructure provision increases output per worker by about 1 per cent in the long run.
Focusing on transportation investments in Africa since , Jedwab and Storeygard show that increased market access has a positive effect on city growth, favouring urbanisation. An interesting strand of literature looks at the historical experience of colonial Africa and India to shed light on how infrastructure investment shapes economic activity. The analysis of railroads in Ghana and Kenya shows that infrastructure investment can produce long-term economic gains by reducing trade costs and integrating markets, potentially transforming the economic landscape in poor, remote regions with high trade costs Jedwab and Moradi, ; Jedwab et al.
Similar findings have been shown for colonial India, where railroads decreased trade costs and interregional price gaps and increased interregional and international trade as well as real income level Donaldson, The historical impact of railroads on the American economy is also consistent with a positive impact of infrastructure investment on market integration and economic development Donaldson and Hornbeck, Micro-level evidence shows that the distributional effect of infrastructure investment could vary.
For instance, Khandker et al. They also show that the poorest households are those benefiting the most. Similarly, Jedwab and Storeygard point to the importance of taking the local context into consideration, given the evidence of heterogeneous effects of transportation investments in Africa—which seem to favour small and remote cities.
The evaluation of programs of infrastructure rehabilitation in Georgia and Vietnam also shows positive average effects, with some evidence of a stronger effect on the poor Lokshin and Yemtsov, ; Mu and van de Walle, Duflo and Pande look at large public infrastructure investments—specifically, dams in India—and find a bleaker picture as poverty, in the aggregate, rises.
Moreover, they point out significant distributional implications, as agricultural productivity increases in downstream districts, which benefit from irrigation, but not in those where dams are built, where construction activities causes loss of agricultural land and expose the population to diseases, resulting in higher poverty rates 4.
Similarly, the extensive highway network built in China since the s has complicated spatial effect on economic activity, with winners and losers. Large cities in the centre of a dense regional highway network grow faster and specialise in business services and manufacturing, while the hinterlands grow more slowly, and become relatively more specialised in agriculture Baum-Snow et al.
This points to the importance of anticipating distributional effects of infrastructure projects and planning offsetting measures if such effects are expected to be negative.
Figure 1. Selected Infrastructure Indicators Median, latest available year between For example, in the s, a wave of public-financed infrastructure investment delivered poor results in terms of short and long run economic growth, mostly because of cost overruns, corruption and poor maintenance Arezki et al. After this negative experience, and following market liberalisation policies, the private sector started playing a more prominent role in financing infrastructure investment, partly through PPPs see Hammami et al.
However, in many developing countries this resulted in high construction and maintenance costs Estache and Fay, Thus, public investment effectiveness and efficiency are not always assured and need to be achieved through appropriate institutions and policies.
Firm-level data compiled by the World Bank as part of the Enterprise Surveys World Bank, no date confirm the presence of large gaps in access to electricity, water and transportation infrastructure, and indicate that such gaps are an actual constraint on real economic activity Table 1, top panel. The percentage of firms in LIDCs that identify access to electricity and transportation as a major constraint to their business activity is, respectively, 43 and 24 per cent.
By contrast, the same percentages are 32 and 18 per cent, respectively, in emerging markets EMs. Focusing on access to electricity, it is interesting to observe that 74 per cent of firms in LIDCs experience power outages—compared to 53 per cent in EMs. Furthermore, the average firm in LIDCs experiences 11 power outages per month, which implies a cost of 7. In contrast, in EMs firms have to deal with 4.
This change has been broad-based across country groups, although frontier economies have shown faster accelerations and, on the contrary, changes in fragile states have been less perceptible. A few countries—particularly Vietnam—stand out with impressive performance across a range of indicators. Information and communication technology ICT has expanded dramatically, with the number of Internet servers growing from near zero in to the average of 6 servers per million people in Electricity generation per capita has increased by 57 per cent on average, with over per cent increase in a few countries, such as Bhutan and Vietnam.
On the other hand, improvements in transport infrastructure have been relatively minor, even though transportation is typically the largest item in LIDC capital budgets. Firm-level data from the World Bank Enterprise Survey confirm these trends, as the share of firms identifying electricity and water insufficiencies as major constraints to their business activity sharply decreased over the last decade, while almost no progress is observable on transportation infrastructure Table 1, bottom panel.
Table 1: Infrastructures and Economic Activity. Note: The top panel reports simple averages of all available country-representative surveys, over the period , by country groupings. The bottom panel reports changes between the most recent survey and the first one, starting in Then, the initial and final year changes because of data availability.
Only countries with at least two surveys since are considered. Despite significantly faster growth, electricity generation capacity in LIDCs—even in frontier markets—remains considerably lower than in emerging markets Furthermore, electricity supply is also less reliable see Table 1.
Road density also lags behind 0. Mobile phone penetration made huge strides from near zero in to 72 per people in , but was still significantly lower than per people in EMs. Survey-based measures about the quality of national infrastructure compiled by the World Economic Forum Schwab, show a noticeable improvement in perceived infrastructure quality in LIDCs in the second half of the , but no progress for the median LIDCs since , leaving a large gap with advanced and emerging market economies Figure 2.
Figure 2. Perceptions of Infrastructure Quality Index, It is generally recognised, however, that the public sector provides the bulk of infrastructure in these countries. In addition, as we show in Section 4.
Thus, we start our analysis by examining trends in public investment. Median public investment in LIDCs rose significantly from 5. Following a temporary slowdown in , public investment picked up again and stood at 6. Moreover, a large gap still remains compared to emerging and advanced economies. In the pre-crisis period, the scaling-up of public investment was common to most countries, which benefited from a favourable global environment, rising commodity prices, and debt relief under the HIPC and MDRI initiatives, among other factors.
In particular, commodity exporters expanded public investment more than other countries as they benefited from a large terms-of-trade improvement. These trends diverged in recent years, with public investment falling in commodity exporters as a decline in commodity prices led to fiscal pressures, while diversified exporters recorded a further small increase from the pre-GFC peak Figure 4. Figure 4. In every category, one can find examples of countries that achieved or maintained high public investment levels and examples of those that failed to do so.
A large majority increased the public investment-to-GDP ratio in the period compared to Figure 5. Public investment rose steadily in several commodity exporters, including Bolivia, Mongolia, Mozambique, Niger, and Tajikistan, until a drop in following a negative commodity price shock. However, in some other countries, the ratio of public investment to GDP has declined significantly over time, reflecting, for example, intensified fragility in Eritrea and Yemen, and fiscal pressures in Nigeria and Uzbekistan.
A few countries have not experienced a pronounced scaling-up, but have maintained fairly high levels of public investment throughout the past 15 years. On the other hand, in several countries, public investment has been quite low over the whole period e. Figure 6. Over the last decade and a half, there has been a clear correlation with correlation coefficient of 0.
However, the former was greater than the latter in most countries, especially in most recent years. Median public saving declined sharply during the GFC, and, after a brief rebound, started slipping again, with the latest slide reflecting lower commodity prices. As a result, median public saving has dropped 2. In , public investment exceeded public saving in 42 out of 46 LIDCs and the gap between median public investment and median public saving reached 4. Figure 7.
Fiscal vulnerabilities have increased recently, particularly among commodity exporters. Budget deficits have gone up, interest rates have risen, and local currency depreciation has increased the burden of external debt. As a result, the median general government debt ratio went up from 34 per cent in to 43 per cent in For instance, in Ethiopia issued a USD one billion Eurobond to finance imports related to export-oriented projects such as investment in the power transmission infrastructure, sugar factories, and the development of industrial parks IMF, Thirty-two country teams were able to provide information on public investment in economic infrastructure over the last five years, typically in consultation with the authorities.
This information offers valuable insights, even though the results should be taken with a grain of salt as quality and comparability of data cannot be assured. Looking across country groupings, frontier market economies had somewhat higher levels of investment, facilitated by easier access to financing and stronger economic prospects. Investment levels in fragile states were typically lower than average, likely reflecting limited fiscal space and weak institutional capacity Collier and Cust, Figure 8.
Water and sanitation account for 22 per cent, the energy sector for 19 per cent and ICT for the residual 6 per cent. The relatively low share of energy is somewhat troubling, since access to electricity is frequently identified as a key constraint to development in LIDCs see Payne, , for a review of the literature, and Di Bella and Grigoli, , for an application to Haiti and Nicaragua.
Fairly broad private provision of ICT services has allowed governments to spend relatively little in that area. Since , LIDCs accounted for 6. After a sharp acceleration in the early s, PPP flows have declined in the most recent years. Vietnam and Bangladesh have the largest number of projects Table 2 , while Lao PDR is an undisputed leader in terms of volume. Across Africa there are several examples of regional infrastructure projects, especially in the energy and transport sectors UNCTAD, A key reason for the rapid deceleration of productivity growth in recent years has been a long period of weak private investment.
As labor markets normalize and begin putting upward pressure on wage growth, there is strong reason to believe that firms will begin searching harder for ways to reduce upward labor cost pressure and will begin investing in labor-saving capital and technology.
Figure D replicates a table from Bivens showing the relationship between lagged values of real compensation growth and private fixed investment. It shows a strong positive relationship between the two. By taking up the last of any remaining demand slack, an increase in infrastructure investment could have an immediate effect in restoring productivity growth to more normal levels. More importantly, there remains a strong economic rationale for investing in infrastructure even after the economy reaches and settles into full employment.
Highways, airports, dams, sewer systems, and utilities are all necessary inputs for private production, but they are largely supplied with public funds. When the public capital stock is allowed to degrade through lack of investment, this could in theory lead to slower private-sector productivity growth. Before delving into evidence assessing this effect, however, it is important to note that improving private-sector productivity is just one reason to support expanded public investment.
If, for example, public investment had no impact at all on private-sector productivity but allowed public goods to be delivered more efficiently, there would be a benefit. If we were to receive clean water and air, safe food and medicine, and transportation services for less money than we spend currently, this would be a perfectly fine way to enjoy the economic returns to expanded public investment, even if they do not boost private-sector productivity.
Further, the possibility that the benefits of public investment are more broadly shared than the benefits of private-sector investment constitutes another compelling reason to support it. This should not be a shock—by its nature public capital is more broadly based in its ownership than private capital in the United States, the wealthiest 1 percent of households own more than 40 percent of private wealth and so its benefits should be more broadly distributed Getachew Finally, it should be remembered that many possible benefits of public investment may not show up as increases in cash incomes.
Clean water and air and shorter commute times provide clear economic benefits, but these benefits do not generally show up in measurable cash incomes. Serious research on the productivity of public investment was begun almost singlehandedly by David Aschauer in a series of papers in the late s and early s see Aschauer , , for two of these. The Aschauer findings were generally based on a time-series estimation of public investment in the theoretical context of an aggregate production function model.
Aschauer estimated these aggregate production functions, augmented with public capital stocks an innovation relative to much empirical growth literature , and found that the elasticity of private-sector output with respect to public capital was between 0.
The implication of this finding was that the rate of return to public capital was roughly three times higher than that of private capital.
However, the approach pioneered by Aschauer soon came under criticism from a variety of angles. Critics of the time-series component—particularly Aaron and Gramlich —argued that the link between public capital and productivity suffered from problems of both causality and simultaneity.
The causality criticism is that faster output growth may simply allow for stepped-up investments in public capital rather than increased public investment driving faster output growth. That is, maybe both series just happened to be rising over time, and the correlation between the two simply reflected these contemporaneous trends without indicating an actual economic relationship between the series.
One suggested econometric fix for the problem of simultaneity is the transformation of the public capital and productivity data into first differences—essentially looking at the year-over-year change in each series. While this transformation does produce two stationary series and is hence a plausible statistical fix, Munnell correctly points out that this fix does not allow one to examine long-run relationships between public capital formation and productivity growth, and that the economic hypothesis of the relationship between the two which is indeed a long-run relationship hence cannot be tested if this particular statistical fix is adopted.
Given that most empirical growth studies are concerned exactly with such long-run relationships, this makes the first-differencing fix fatal to the project of fairly assessing the impact of public capital investments on growth.
The simultaneity problem is most clearly addressed by Heintz , who uses more advanced econometric techniques specifically, a vector error-correction model to search for a cointegrating relationship between the two series. A cointegrating relationship exists between two nonstationary time series if some linear combination of them is stationary.
Heintz confirms that a cointegrating relationship does exist between public capital and private productivity and uses this relationship to estimate a statistically and economically significant long-run relationship between public capital stocks and private productivity. Heintz and Everaert and Heylen also point out that solving the simultaneity problem through error-correction models largely solves the causality problem along the way. Specifically, Heintz allows for the level of public capital to affect both the level and the change in private output.
He finds a statistically significant relationship between the level of public capital and the change in private productivity.
If, however, the direction of causality actually ran from greater private productivity to larger public capital stocks, then there should be no such relationship between the level of public capital and the change of productivity. Data and methods are described in detail in the technical appendix. The dependent variable is the ratio of private-sector output to capital stock, while the coefficient of interest is the lagged ratio of public to private capital.
For the period from — i. However, the s saw a more rapid pace of infrastructure investment than what came thereafter, largely due to the construction of the interstate highway system. Again, the coefficient is essentially unchanged. The coefficient values imply that a 10 percent increase in the public capital stock boosts private-sector output by 1. For the results from Table 2, this implied rate of return is very large, hovering between 30 and 40 percent.
Notes: The dependent variable is the change in private-sector productivity, measured as the ratio of private-sector output to private-sector capital stock. Data and methods are discussed in the technical appendix.
T -statistics are in brackets. Three asterisks denote significance at the 1 percent level, two asterisks denote significance at the 5 percent level, and one asterisk denotes significance at the 10 percent level.
While high, these rates of return are not clear outliers. Figure E shows the distribution of their findings, focusing strictly on 33 studies they survey that generate estimates of the rate of return to public investment in the United States. The average rate of return is If one excludes the top three and bottom three estimates, the average return drops slightly, to Figure E shows the central estimate and minimum and maximum estimated returns for the 33 studies surveyed by Bom and Ligthart It is worth noting that even the average minimum rate of return 6.
Thus, it seems that CBO estimates of the benefits of public investment—particularly infrastructure investment—are too low given the other evidence in this literature. Finally, another striking feature of these estimates are how consistently they tend to rise over time, as more up-to-date data and research methods are used.
The studies are aligned on the horizontal axis chronologically, and the pattern of more recent studies yielding higher estimated rates of return is clearly visible in the chart. There is strong evidence that a period of increased infrastructure investment effort could provide large benefits to the American economy. It could provide a fiscal expansion in an economy where aggregate demand growth has been stubbornly slow for years, even in the face of prolonged expansionary monetary policy.
It could also aid the capital deepening that is necessary for boosting productivity growth, especially during a period that has seen anemic private-sector investment. This paper was made possible by a grant from the Peter G. Peterson Foundation. The statements made and views expressed are solely the responsibility of the author.
Josh Bivens joined the Economic Policy Institute in and is currently the director of research. His primary areas of research include macroeconomics, social insurance, and globalization. He has authored or co-authored three books including The State of Working America, 12th Edition while working at EPI, edited another, and has written numerous research papers, including for academic journals.
He often appears in media outlets to offer economic commentary and has testified several times before the U. He earned his Ph. The large estimates of rates of return on public investment found by Aschauer were subsequently criticized on the grounds that they suffered from problems of simultaneity. Essentially, the argument was that the statistical relationship between public investment and output found by Aschauer was spurious, driven only by the presence of nonstationarity in one or the other of the series.
A data series is nonstationary if its mean or other statistical properties change over various parts of the sample in this case, if the mean or other statistical properties vary over time.
If a nonstationary series is used in regression analysis, it can yield regression results that are spurious. Heintz , however, notes that if both series public capital and output have a unit root in levels are nonstationary in the same way but are stationary in growth rates, then an error correction model can be used to undertake regression analysis and the simultaneity problem can be dealt with.
He regresses the change in the ratio of output to private capital on lagged values of the dependent variable, the private capital stock, the labor force, and the infrastructure capital stock, as well as changes in private and infrastructure capital stocks and the labor force.
Table A1 confirms that each of the data series has a unit root in levels but is stationary in first differences. For each series, the hypothesis of a unit root cannot be rejected in levels, but it can be rejected at the 5 or 1 percent level of significance for the first differences. Given this confirmation, we can employ the Heintz error correction model. Notes: T -statistics are reported, with p -values in parentheses.
Three asterisks denote significance at the 1 percent level, and two asterisks denote significance at the 5 percent level. Data on private and infrastructure capital stocks was obtained from the Bureau of Economic Analysis BEA series on fixed assets.
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