Chapter 4 Infrastructure Investment and the Sustainable Development Goals
Author:
Mr. Yuan Xiao
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Devin D’Angelo
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Nghiã-Piotr Trong Lê
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Language:
English
Keywords:
BOOK; investment; government; governance; country; spending; public investment; infrastructure governance; investment efficiency; investment shock; investment spending; Public investment spending; Public investment and public-private partnerships (PPP); Infrastructure; Budget planning and preparation; Fiscal rules; Global; Asia and Pacific; Africa; Caribbean; Sub-Saharan Africa; management process; low-income developing countries; management reform; investment need; investment needs; Sustainable Development Goals (SDG); Emerging and frontier financial markets
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Abstract

Drawing on the Fund’s analytical and capacity development work, including Public Investment Management Assessments (PIMAs) carried out in more than 60 countries, the new book Well Spent: How Strong Infrastructure Governance Can End Waste in Public Investment will address how countries can attain quality infrastructure outcomes through better infrastructure governance—an issue becoming increasingly important in the context of the Great Lockdown and its economic consequences. It covers critical issues such as infrastructure investment and Sustainable Development Goals, controlling corruption, managing fiscal risks, integrating planning and budgeting, and identifying best practices in project appraisal and selection. It also covers emerging areas in infrastructure governance, such as maintaining and managing public infrastructure assets and building resilience against climate change.

Introduction

The Sustainable Development Goals (SDGs) delineate a comprehensive international agenda for sustainable development by 2030 that has been endorsed by all UN member states and build on the substantial progress achieved under the Millennium Development Goals (UN 2015). The 17 SDGs of the 2030 Agenda for Sustainable Development officially came into force on January 1, 2016. With these new goals universally applied, all countries committed to mobilize efforts aimed at ending poverty, fighting inequality, and reducing climate change over the next 15 years, while ensuring that no one is left behind (Figure 4.1).

Figure 4.1.
Figure 4.1.

United Nations’ Sustainable Development Goals

Source: United Nations Sustainable Development Goals website.

Infrastructure development plays a key role in the SDG agenda. The 17 SDGs aim to tackle a wide range of global issues, including those related to poverty, health, education, water and sanitation, energy, inequality, climate, environmental degradation, prosperity, and peace and justice. They include three goals directly related to infrastructure: water, sanitation, and hygiene (SDG 6), energy (SDG 7), and infrastructure and industrialization (SDG 9). Moreover, infrastructure development will have positive spillovers on most other SDGs because every economic and social sector requires good infrastructure for development. Infrastructure is also an important driver of economic growth, which is essential in enlarging a country’s revenue base to meet spending needs.1

This chapter develops methods to estimate investment spending needs to reach SDGs related to infrastructure and discusses their implications for infrastructure governance in emerging market economies and low-income developing countries. Achieving infrastructure development targets by 2030 requires significant investment and financing. The focus here is on three key sectors— roads, electricity, and water and sanitation—where information is available and quantifiable targets can be defined.

The total cumulative investment needs before 2030 in these three sectors are substantial—at 36.1 percent of emerging market economies’ and low-income developing countries’ GDP, according to estimates in this chapter. These investment needs vary significantly across both income levels and regions and would require significant scaling up of public investment spending in many countries. Governments and the international community will need to explore policy options to address the challenge to finance the increased spending.

An assessment of countries’ current performance on SDGs in infrastructure is a starting point in the discussion in this chapter. Costing methodologies for determining estimated spending needs by income groups and regions for each infrastructure sector are then described in detail. Mobilizing domestic revenues and improving public investment efficiency are also featured as they are crucial considerations in helping countries achieve the SDGs. As noted in Chapter 3, more than one-third of resources are lost in the process of public investment, waste that can be substantially reduced through better infrastructure governance. Public investment management reforms will therefore be a crucial part in reaching SDGs related to infrastructure.

SDGS in Infrastructure: Taking Stock

Tasks for achieving SDGs are distributed unevenly across countries, with larger challenges for developing countries. As Figure 4.2 shows, the median composite SDG index score—a measure that tracks country performance in achieving SDGs—in 2017 is highest for advanced economies at 78 percent and as low as 53 percent for low-income developing countries, with emerging market economies somewhere in between. This suggests there are significant gaps and that more spending will be needed to achieve SDGs in most countries. It is not surprising that higher-income countries tend to have better SDG index scores. In low-income developing countries, not only are the gaps toward reaching SDGs the largest, the group variation in SDG scores is also wider than in other income groups.

Figure 4.2.
Figure 4.2.

SDG Composite Index, 2017

Source: Lafortune and others 2018.Note: The SDG Index aggregates available data on all individual SDGs into a composite index to provide a quick assessment of how countries are performing relative to their peers. SDG = Sustainable Development Goal.

Similar patterns exist for the three infrastructure-related SDGs (Figure 4.3). Targets, including for infrastructure, include a wide range of quantitative and qualitative performance objectives, and precisely defined targets are in general left for the implementing authorities. As a result, for practical purposes and because of data limitations, the performance measurements and spending-need estimates in this chapter focus only on a subset of the infrastructure-related SDG indicators (Table 4.1).

  • Roads. As shown in Figure 4.3, panel 1, access to roads in rural areas remains, to different degrees, low in most countries. Low-income developing countries tend to have poor rural road access and road density. World Bank (2019) argues that, given the weak starting positions, universal access to paved roads may not be within reach by 2030 even if countries spend 1 percent of their annual GDP on roads. Overall, the quality of infrastructure (including transportation) is worse in low-income developing countries than in other income groups, and there is a wide variation across countries.

  • Electricity. There is a long way to universal electricity access in low-income developing countries; by contrast, electricity access is not a significant issue in advanced and emerging market economies (Figure 4.3, panel 2). The variation in electricity access is also noticeably larger in low-income developing countries.

  • Water and sanitation. Access to safely managed water and sanitation is far from universal, especially in rural areas and in low-income developing countries (Figure 4.3, panels 3 and 4). Significant variation exists for emerging markets and low-income developing countries.

Figure 4.3.
Figure 4.3.

Access to Infrastructure, Selected Indicators

Sources: United Nations SDG indicators; and World Bank Rural Access Index.Note: SDG = Sustainable Development Goal.
Table 4.1.

Infrastructure SDG Targets Considered in This Chapter

article image
Source: United Nations SDGs website. Note: SDG = Sustainable Development Goal.

Spending Needs to Reach SDGs in Infrastructure

To reach SDGs, it is important to gauge the spending needs of different countries. However, the task is far from straightforward. First, SDG targets include a wide range of quantitative and qualitative performance criteria, and precisely defined targets are not generally agreed upon. Second, measuring performance and calculating the costs requires a substantial amount of information that is often unavailable, especially for emerging markets and low-income developing countries. Third, the costs of implementation are endogenous and depend on factors that include the chosen technologies, country-specific initial conditions and costs, economic and demographic assumptions, and complementary reforms. Fully measuring all aspects of the SDGs is therefore an impossible task. Instead, the attempt in this chapter is to quantify a selected but nonetheless important subset of infrastructure SDGs, making assumptions in estimating the spending needs while acknowledging that the effort should be an evolving process with room for continuous refinement.

Models and methods developed by the IMF and the World Bank are used to estimate spending needs for road and electricity access and for water. Although an important strand of work on infrastructure gaps is apparent, these studies follow an approach motivated by the need to support economic development; they do not directly measure the costs of reaching SDG targets.2 Bottom-up estimates specifically related to SDG targets on infrastructure are lacking given that the SDG agenda was established just a few years ago and because quantitative targets or indicators for many targets do not exist. This chapter develops a costing methodology for SDGs focusing on access to infrastructure, which is based on the unit cost approach taken in earlier literature about infrastructure gaps. Schmidt-Traub (2015) and Gaspar and others (2019) discuss spending-need estimates for achieving SDGs in a broader set of sectors, including education and health. World Bank (2019) goes beyond costing the access to infrastructure by accounting for climate goals, and explores scenarios based on technological options. Box 4.1 describes the costing methods used in this chapter.

Investment Spending Needs

Total cumulative investment needs from 2019 to 2030 in the three infrastructure sectors are estimated at around $12 trillion for 121 emerging market economies and low-income developing countries (36.1 percent of their GDP cumulatively). This implies an annual average investment need of about USD 1 trillion (3 percent of GDP) for these countries.3 As shown in Figure 4.4, on average, emerging market economies have an annual investment need of 2.7 percent of GDP until 2030, while for low-income developing countries it is equivalent to 9.8 percent of GDP. To put these figures in context, the median size of capital spending is about 3.6 percent of GDP for emerging market economies and 5.1 percent for low-income developing countries (Figure 4.5). Although the ongoing capital spending will help achieve the SDGs, the remaining investment spending needs estimated in this chapter are still sizeable, especially for low-income developing countries.

Figure 4.4.
Figure 4.4.

Total Annual Investment Needs

(As a percentage of average GDP)

Source: Authors’ calculations.
Figure 4.5.
Figure 4.5.

Investment Needs and Budget Spending

(As a percentage of average GDP)

Source: Authors’ calculations.

Costing Methodology for Roads; Electricity; and Water, Sanitation, and Hygiene

The estimates for the three infrastructure sectors share a common two-step approach.1 First, an infrastructure gap is defined for a country measuring the distance from the SDG target in the sector. In some sectors, a quantifiable goal (such as universal access) is identified in the SDG. When a clear quantifiable goal is unavailable, the chapter provides a proxy. Second, the cost for closing this gap is calculated based on estimates of sector-specific unit costs found in the literature.

  • Roads. Because there is no specific numerical UN target for road infrastructure, we operationalize Target 9.1 by using GDP per capita and a rural road access index to measure “economic development and human well-being” (Target 9.1). A target road density—as a function of GDP per capita, population density, and rural road access—is estimated using regression analysis (described in Annex 4.1). Once an infrastructure gap is established, the annual investment needed to close the gap by 2030 is computed given the unit cost—obtained from the literature—to build the road network. Maintenance costs are also included.

  • Electricity. Because Target 7.1 (universal access) is quantifiable, existing estimates of unit costs are used to calculate the average annual cost to reach universal access while controlling for population growth and maintaining the same initial electricity consumption per user. The need to increase power consumption as economic activity expands is also accounted for.

  • Water, sanitation, and hygiene. Cost estimates are based on a template developed by the World Bank using the unit cost approach to reach universal access to safely manged water, sanitation, and hygiene services (Hutton and Varughese 2016). The template considers both capital spending and operational costs.

1 See Annex 4.1 for more details on roads and electricity, and Hutton and Varughese (2016) on water, sanitation, and hygiene.

SDG spending needs, including the estimated investment needs, vary significantly across income levels and countries (Figures 4.6 and 4.7) and could pose a challenge for lower-income countries. Figure 4.6 displays both infrastructure SDG needs and total SDG spending needs for education, health, and infrastructure, based on estimates in Gaspar and others (2019) and relative to a country’s income level (the diameter of the balloon indicates GDP size). Some of the largest spending needs (for both infrastructure and total) occur in the smallest economies. This is not surprising given that low-income countries typically have worse infrastructure, but the pattern does highlight the difficulties that poorer countries face

Figure 4.6.
Figure 4.6.

Annual Spending Needs, by Size of GDP

(As a percentage of average GDP)

Source: Authors’ calculations based on Gaspar and others 2019.Note: The diameter of the balloon indicates GDP size. SDG = Sustainable Development Goal.
Figure 4.7.
Figure 4.7.

Annual Investment Needs, by Region

(As a percentage of average GDP)

Source: Authors’ calculations.

in financing the necessary spending to reach the SDGs. There is also a wide dispersion of investment needs across regions (for emerging market economies and low-income developing countries): the largest investment need is in sub-Saharan Africa, while Europe and Latin America have the smallest need and Asia, the Middle East, and the Commonwealth of Independent States fall in the middle.

Spending needs in road infrastructure are the largest in both emerging markets and low-income developing countries. As Figure 4.8 shows, emerging markets need average annual investment of 1.7 percent of GDP (1.3 percent of GDP for new construction and 0.4 percent of GDP in maintenance) for roads until 2030, while low-income developing countries need annual investment of 5.2 percent of their GDP (4.1 percent of GDP for new construction and 1.1 percent of GDP in maintenance). These are significant costs, and especially relevant for sub-Saharan Africa, where rural accessibility is of particular concern. In addition, as countries invest to build road networks, maintenance costs will become more important. The model used in this chapter assumes a fixed depreciation rate of road assets, but some studies (for example, World Bank 2019) suggest that maintenance costs can rise to match the amount of new investment in some cases.

Figure 4.8.
Figure 4.8.

Investment, by Sector

Source: Authors’ calculations.Note: Distributions in panels 2, 4, and 6 show maximum, 75 percent, 25 percent, and minimum values.

Spending needs for universal access to electricity are lower for emerging market economies than for low-income developing countries, but demand-driven investment needs cannot be overlooked. It is estimated that emerging market economies will face an average annual investment need of 0.4 percent of their GDP (0.1 percent of GDP to reach universal access and 0.3 percent of GDP to elevate per user electricity consumption to keep up with economic growth) until 2030, while low-income developing countries face an annual investment need of 1.8 percent of their GDP (1.1 percent of GDP to reach universal access and 0.7 percent of GDP to elevate electricity consumption to keep up with economic growth). In emerging market economies, electricity access is not as severe an issue as in low-income developing countries (Figure 4.3). However, more advanced economies tend to have higher power consumption per user. In order to reach aspirations for economic growth, per user electricity consumption may need to increase even when universal access is no longer a concern; for example, in the transition to industrialization while the economic structure shifts toward a more energy-intensive pattern. These investment needs can also be affected by inefficiencies in electricity transmission and country-specific technology in power generation and transmission. World Bank (2019) stresses that operations and maintenance also need to be budgeted for once capital investment is made, to ensure electricity is reliable and affordable.

Investment needs to achieve universal access to safely managed water and sanitation are slightly less than those for electricity access. Average annual spending needs in emerging markets amount to 0.5 percent of their GDP (0.5 percent of GDP for water and 0.01 percent of GDP for sanitation) until 2030, while low-income developing countries face an annual spending need of 2.8 percent of their GDP (2.6 percent of GDP for water and 0.2 percent of GDP for sanitation). As universal coverage requires more than a one-off injection of capital while operation and maintenance in the water sector are especially important, all such costs were included in the estimates.

Our spending-need estimates are comparable to estimates in the literature, but naturally there are caveats in such exercises.4 Reconciling cost estimates across studies is complicated given differences in the interpretation and inclusion of precise targets, country groupings, spending definitions, specific information available, and years for which estimates are reported. In particular, results from cross-country studies need to be verified and improved by using country-specific information, as governments need to incorporate SDGs into their own national development plans, choose practical development targets, and prioritize among objectives competing for the same resources. Moreover, the unit costs used in the calculations could vary depending on country-specific characteristics, technological choices, and the success of complementary reforms. For example, in country cases in which the methodologies described in this chapter have been applied, some of the unit cost assumptions were based on country-level information.

Efforts to improve public investment efficiency could change the sizes of countries’ spending needs. Improvements in infrastructure coverage and quality

in recent years have been only loosely correlated with public investment, suggesting considerable efficiency loss in public investment in most countries.5 As seen in Chapter 3, the size of the efficiency gap—the difference between the average country’s public investment efficiency and that of best performers— widens as income falls, with a gap of 34 percent in emerging market economies and a gap of 53 percent in low-income developing countries. Reforms could help countries deliver more infrastructure “bang” for their public investment “buck.” To illustrate the impact of efficiency gains, suppose emerging markets could improve efficiency such that the resulting average rose to match the current 75th percentile level for the group. Then these economies could reduce their total annual investment needs from 2.7 percent of GDP to 2.3 percent of GDP; if all emerging markets were to reach the maximum efficiency level, then their total annual investment needs would fall to 1.8 percent of GDP (Figure 4.9).6 Similarly, low-income developing countries could reduce their total annual investment needs from 9.8 percent of GDP to 8.6 percent of GDP if their average efficiency rose to match the current 75th percentile for the group. Were all low-income developing countries to reach maximum efficiency, they could further reduce their total annual investment needs to 5.9 percent of GDP.

Figure 4.9.
Figure 4.9.

Impact of Improving Public Investment Efficiency

(Cost as percentage of average GDP)

Source: Authors’ calculations.

Implications for Revenue Mobilization and Public Investment Management

Since the investment needs to achieve infrastructure SDGs are sizeable, successful implementation of the SDG agenda requires strong national ownership to mainstream the SDG strategy into national development plans, investment prioritization, and budget processes. This in turn requires carefully planning the financing options, galvanizing private sector involvement, and managing the associated risks, as well as improving public investment governance and efficiency.

Meeting infrastructure investment needs requires scaling up public investment spending in many countries. Although in some cases the private sector could share the burden of the projected investment, a significant share of spending will necessarily come from the government budget. Therefore, financing the increased spending is a challenge that country authorities and the international community will need to address. Gasper and others (2019) explore some policy options.

  • Additional revenue mobilization is the most important source of financing. It is estimated that if countries with tax-to-GDP ratios below the 75th percentile for their income group were to raise them to the 75th percentile, the increase would amount to 5 percentage points of GDP, on average. Adopting a medium-term revenue strategy is key. It would involve the following steps: building a broad-based consensus for medium-term revenue goals; designing a comprehensive tax reform policy, covering its administration and legal framework; committing to sustained political support over many years; and securing adequate resources to support coordinated implementation.

  • Structural reforms that boost the level and durability of growth can be used to increase the resources available for investment. These reforms encompass a broad set of areas, including labor and product markets, the financial sector, governance, public finance management, and the business environment.

  • Closer cooperation of the international community will help in achieving infrastructure SDGs in low-income developing countries. As mentioned earlier, the investment needs in low-income developing countries and some emerging market economies far exceed what they have been able to spend on public investment on average, and it would be difficult for many countries to rely solely on their own resources. Delivering on existing official development assistance targets would make a substantial contribution to closing the financing gaps.

The private sector can play an important role in infrastructure investment, but private financing is no panacea. Public-private partnerships can deliver infrastructure services more efficiently than can traditional public procurement under certain conditions. A well-designed contract can take advantage of bundling activities from building to operating the infrastructure, as the private partner has an incentive to construct high-quality assets and allocate an appropriate amount of maintenance spending over the lifetime of the asset. In a similar vein, private partners usually have an incentive to finish projects early with public-private partnerships.

However, public-private partnerships are not always more efficient than traditional procurement and entail significant fiscal risks. Privately financed projects will generally face higher financing costs than public sector projects. In addition, given the high contracting costs associated with public-private partnerships, they are only appropriate for large projects, and the quality of service must be measurable. Moreover, although public-private partnerships can help governments to circumvent short-term budget constraints, they do not genuinely create long-term fiscal space and could entail significant fiscal risks, including contingency costs. Therefore, their use will require strengthening public investment management processes and fiscal and legal institutions (navigating the fiscal risks that feature in Chapter 11).

Improvements in public investment efficiency will help to reach the infrastructure-related SDGs. There is significant potential for efficiency gains in public investment for emerging markets and low-income developing countries, since the investment gaps are large. As illustrated in the “Spending Needs to Reach SDGs In Infrastructure” section, if all countries were at their maximum efficiency levels, annual investment costs would be cut by 0.9 percent of GDP for emerging markets and 3.9 percent of GDP for low-income developing countries.

Technological choices among individual sectors will also play an important role in achieving desirable trade-offs among various objectives and result in different costs. For example, World Bank (2019) shows that costs can vary widely with the choice of technology and different pathways used to achieve universal access to safely managed water. In the power sector, there are different strategic choices to deliver different levels of power consumption. In transportation, complementary socioeconomic policies will influence how different modes are delivered and how the sector is organized. These technological decisions will result in different costs and also different levels and quality of infrastructure services.

Conclusions

Infrastructure development is a key aspect of the SDG agenda and entails significant investment needs. On average, emerging market economies face an annual investment need of 2.7 percent of GDP for infrastructure (roads, electricity, and water and sanitation) until 2030, while it is 9.8 percent of GDP for low-income developing countries. There is a large variation among countries, and the challenge is especially daunting for low-income developing countries. Gaps in spending on roads dominate the investment needs. These estimates, as in other cross-country studies, should be refined wherever country-specific information is available. Scope exists to improve the methodology in further studies by considering additional factors and information.

In view of the large investment needs, countries need to develop plans to galvanize financing and improve public investment governance and efficiency. Efforts should focus on careful planning of financing options, galvanizing private sector involvement, and managing the associated risks, as well as tapping into foreign aid. Improving public investment governance and efficiency will help to reduce financing needs by increasing the dividends from public investment for a given level of spending.

Annex 4.1. Methodological Note on Estimating Cost of Reaching SDGS on Road and Electricity Infrastructure

This annex explains the methodology developed at the IMF for estimating the cost of building the road and electricity infrastructure consistent with reaching SDG Target 9.1 and Target 7.1. For the World Bank methodology on costing water, sanitation, and hygiene, see Hutton and Varughese (2016).

Access to Road Infrastructure

A two-step approach is used to estimate the cost for reaching the SDG target related to road access. First, a road infrastructure gap is estimated; and second, the annual investment needed to close the gap by 2030 is computed, given the unit cost to build the road network.

Investment needs to achieve SGD Target 9.1 are envisioned by estimating a target road density based on income, population density, and rural access levels. SDG Target 9.1 states, “Develop quality, reliable, sustainable and resilient infrastructure, including regional and transborder infrastructure, to support economic development and human well-being, with a focus on affordable and equitable access for all.” As there is no specific numerical UN target for road infrastructure, the target road density for a country is derived by considering its projected GDP per capita and population density in 2030 and the goal of ensuring adequate access for those in remote locations, which is measured using a Rural Access Index (RAI).7

A country’s specific target for road density is estimated using elasticities obtained from a regression analysis. Taking a similar approach to the literature for measuring infrastructure gaps (such as for Fay and Yepes 2003), estimates are derived from the following relationship using a cross-section of country-level data:

RDi = C + β1 Yi + β2 PDi + β3 RAIi + β4 Xi + εi,

where RD is the log of road density, Y is the log of GDP per capita, PD is the log of population density, RAI is the rural access index, X is a vector of control variables, including the share of agriculture in GDP, share of manufacturing in GDP, and the degree of urbanization. The estimation results, using a cross-section of low-income developing countries and emerging markets, and all countries separately, are shown in Annex Table 4.1.1. Data sources used in the cost estimation are described in Annex Table 4.1.2. The road infrastructure gap is defined as how far a country is from its target road density.

Annex Table 4.1.1

Main Estimated Coefficients

article image
Source: Authors’ calculations. Note: Standard errors are in parentheses. **Significant at the 5% level. ***Significant at the 1% level.
Annex Table 4.1.2

Data Sources

article image

The regression results confirm the positive correlation between road density and GDP per capita, population density, and rural road access. Increasing the RAI by 1 percentage point requires increasing the road density by about 1.7 percent, when using the estimates for low-income developing countries and emerging markets, and 2.4 percent using the full sample estimate. This implies that a country with a current access level of 50 percent should have a road density 84–120 percent higher than its current value to increase access to 100 percent. The study finds that the elasticity of road density to GDP per capita is around 0.13 in low-income developing countries and emerging markets. This is similar to the coefficient of 0.14 estimated in Fay and Yepes (2003). Population density also is found to be statistically significant with an elasticity of 0.485 across low-income developing countries and emerging markets, and of 0.422 in the all-country sample. This is about the same as the findings in Fay and Yepes (2003).

Then, the country’s specific target is computed and both the investment cost and the associated maintenance cost are calculated. This uses GDP per capita and population density projected for 2030 from World Economic Outlook and UN projections. The RAI is set at a target level,8 and estimated elasticities are applied to calculate the country’s specific target for road density and the corresponding target road length in 2030 (R*). Using the unit cost to build 1 kilometer of road (C), the annual average investment cost to reach R* is as follows:

INV=(R*−R0)⋅C⋅1T,

where R0 is the initial road length and T is the number of years before 2030. For maintenance costs, the assumption is that each year a fraction δ of the newly constructed road network will need to be replaced. Then, the annual average cost to maintain the new roads would be the following:

M=1T⋅δ⋅Σt=1T−1INV⋅t=δ⋅INV⋅(T−1)2.

The unit cost to build 1 kilometer of a two-lane paved road is assumed to be $487.17, unless a country-specific unit cost is available (World Bank 2013). The default depreciation rate δ is assumed to be 5 percent.9 To improve the accuracy of the cost estimates, the historical data, unit cost, depreciation rate assumptions, and country-specific targets should be verified and customized based on country information where that is available. The results also need to be interpreted carefully as the road network is only one factor affecting economic and human development, while the location of the roads and road quality are also important for transportation access.

Access to Electricity

The unit cost approach is used to estimate the average annual cost to reach access for 100 percent of households. SDG Target 7.1 states, “By 2030, ensure universal access to affordable, reliable and modern energy services.” The average annual cost is estimated as follows:

INV1=〈(1−a)⋅P+[P⋅(1+g)]⋅T⋅P〉⋅1T⋅w⋅C,

where a is the initial fraction of the population with access to electricity, P is the population level, g is the population growth rate, T is the number of years to reach universal coverage, w is the initial level of electricity consumption per user in kilowatt-hours (assumed to be constant), and C is the unit cost to generate and distribute electricity (assumed to be $2,258 per kilowatt) (World Bank 2013b).

In addition, estimates are made for the average annual cost to reach a higher level of consumption per user (w *) in line with economic development. In this case,

INV2=(w*−w)[P⋅(1+g)]⋅T⋅C⋅1T,

where w* is assumed to increase with per capita GDP.10

References

  • Fay, Marianne, and Tito Yepes. 2003. “Investing in Infrastructure: What Is Needed from 2000 to 2010?” World Bank Policy Research Working Paper 3102, World Bank, Washington, DC.

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  • Gaspar, Vitor, David Amaglobeli, Mercedes Garcia-Escribano, Delphine Prady, and Mauricio Soto. 2019. “Fiscal Policy and Development: Human, Social, and Physical Investments for the SDGs.” Staff Discussion Note 19/03, International Monetary Fund, Washington, DC.

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  • Global Infrastructure Hub. 2017. Global Infrastructure Outlook: Infrastructure Investment Needs—50 Countries, 7 Sectors to 2040. Sydney: GI Hub.

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  • Hutton, Guy, and Mili Varughese. 2016. “The Costs of Meeting the 2030 Sustainable Development Goal Targets on Drinking Water, Sanitation, and Hygiene.” Water and Sanitation Program Technical Paper, World Bank, Washington, DC.

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  • Iimi, Atsushi, Ahmed Farhad, Edward Charles Anderson, Adam Stone Diehl, Laban Maiyo, Tatiana Peralta-Quirós, and Kulwinder Singh Rao. 2016. “New Rural Access Index: Main Determinants and Correlation to Poverty.” World Bank Policy Research Working Paper 7876, World Bank, Washington, DC.

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  • International Monetary Fund (IMF). 2015. “Making Public Investment More Efficient.” IMF Policy Paper, Washington, DC.

  • Lafortune, Guillaume, Grayson Fuller, Jorge Moreno, Guido Schmidt-Traub, and Christian Kroll. 2018. “SDG Index and Dashboards—Detailed Methodological Paper.” Bertelsmann Stiftung and Sustainable Development Solutions Network, New York.

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  • Schmidt-Traub, Guido. 2015. “Investment Needs to Achieve the Sustainable Development Goals—Understanding the Billions and Trillions.” SDSN Working Paper Version 2, Sustainable Development Solutions Network, New York.

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  • United Nations (UN). 2015. “The Addis Ababa Action Agenda of the Third International Conference on Financing for Development.” New York.

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  • World Bank. 2013. “Global Development Horizons: Capital for the Future—Saving and Investment in an Interdependent World.” Technical Annexes, World Bank, Washington, DC.

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  • World Bank. 2019. Beyond the Gap: How Countries Can Afford the Infrastructure They Need while Protecting the Planet. Washington, DC.

1

An in-depth analysis of the relationship between infrastructure and economic growth features in Chapter 2.

2

See Fay and Yepes (2003) and Global Infrastructure Hub (2017) for examples of this literature.

3

In the SDG literature, both starting-point GDP and 2030 GDP have been used to express spending needs as percentage of GDP. However, since infrastructure investment will occur continuously to 2030 and beyond, GDP averaging between 2019 and 2030 is used as the denominator throughout this chapter to avoid overrepresenting or underrepresenting the spending needs.

4

As shown in Gaspar and others (2019), other studies tend to find the annual infrastructure spending need for low-income developing countries and emerging markets to be in the neighborhood of $2 trillion (for a wider sectoral coverage than the three sectors examined in this chapter).

5

See IMF (2015) and Chapter 3 of this book.

6

Assuming a unitary elasticity of the change in the average unit cost to build the infrastructure, with respect to a change in the efficiency gap.

7

The RAI (measured as the percentage of rural households living within 2 kilometers of an all-season road) is developed by the World Bank, and the latest data correspond to 2006. The World Bank is updating the index using a new methodology developed in 2015 (Iimi and others 2016).

8

In this chapter, a target RAI ensuring good access is assumed to be 75 percent for those currently below 75 percent and 90 percent of those already above 75 percent.

9

The literature estimates that the depreciation rate for public capital stock ranges between 2.5 percent and 4.7 percent (see IMF 2015).

10

The elasticity is assumed to be 0.94, reflecting the estimated correlation.

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Cover Well Spent
Well Spent
How Strong Infrastructure Governance Can End Waste in Public Investment
Editor:
Mr. Gerd Schwartz
,
Ms. Manal Fouad
,
Mr. Torben S Hansen
, and
Ms. Genevieve Verdier
ISBN:
9781513511818
Publication Date:
03 Sep 2020
Publisher:
International Monetary Fund
DOI:
https://doi.org/10.5089/9781513511818.071
Pages:
344
Figure 4.1.

United Nations’ Sustainable Development Goals
Figure 4.2.

SDG Composite Index, 2017
Figure 4.3.

Access to Infrastructure, Selected Indicators
Figure 4.4.

Total Annual Investment Needs

(As a percentage of average GDP)
Figure 4.5.

Investment Needs and Budget Spending

(As a percentage of average GDP)
Figure 4.6.

Annual Spending Needs, by Size of GDP

(As a percentage of average GDP)
Figure 4.7.

Annual Investment Needs, by Region

(As a percentage of average GDP)
Figure 4.8.

Investment, by Sector
Figure 4.9.

Impact of Improving Public Investment Efficiency

(Cost as percentage of average GDP)