Chapter 4. Linking sector strategies to national contexts

This chapter provides an overview of donors’ sector allocations of official development finance (ODF) to different country groups. It focuses in particular on the dynamics and trade-offs between various types of flows reaching developing countries. In doing so it takes into account the scarcity of official development assistance (ODA) resources, their declining trend as countries develop and the compensatory role played by other official flows (OOF) when countries embark on a transition path. The analysis of these trade-offs is a first step towards informing the international development community about patterns emerging in financing for development (FfD) flows to sectors. It aims to contribute to the 2015 Addis Ababa Action Agenda, which called for “scaled-up and more effective international support, including both concessional and non-concessional financing”. The first section of this chapter provides an overview of financing and a more detailed sub-sectoral analysis of ODF flows for three different income categories (low income countries, lower middle-income countries and upper middle-income countries).1 The second section provides a similar overview for countries most in need (least developed countries, landlocked developing countries, small island developing states and countries in fragile contexts). The chapter concludes by looking at the main policy messages that can be derived from these analyses.

    

Key messages

Key messages to providers of development co-operation emerging from this chapter include:

  • Allocations of other official flows (OOF) to the education and health sectors in lower middle-income countries (LMICs) appear to be much lower than in the other social sectors. The share of OOF in LMICs amounts to only 6% in health and 12% in education, as opposed to 28% in government and civil society and 34 % in other social sectors. Making more resources available for education and health can boost economic productivity by tackling the root causes of the middle-income trap.

  • Agriculture faces considerable challenges in attracting OOF compared to other productive sectors. This applies across all developing country income categories. Only 6% of official development finance (ODF) to low-income countries (LICs) is in the form of OOF. As countries develop, this proportion remains far below that in the other productive sectors. The share of OOF in agriculture reaches 57% in upper middle-income countries (UMICs), when other productive sectors receive around 90%.

  • Least developed countries (LDCs) receive most grants. Despite higher risk perceptions, evidence exists that LDCs can offer opportunities for providers to support the development of the private sector, including through blended finance packages.

  • In landlocked developing countries (LLDCs), providers do not prioritise infrastructure. The share of infrastructure in ODF is 33% in LLDCs, almost the same as in other developing countries (ODCs) – 34%. In principle, it should be higher, especially in transport and ICTs, to compensate for the challenges of being landlocked.

  • In small island developing states (SIDS), non-concessional finance is lower than in ODCs, for almost all sectors and in any income category. For example, in the water sector, the share of OOF represents only 1% in LMIC-SIDS as against 30% in other LMICs.

  • Adopting a smart, sector approach to transition finance is essential, but demands new research. This publication takes an initial look at the benefits of analysing transition finance gaps from a sector perspective. For example, it can help to identify when providers should target specific sectors as countries climb the income per capita ladder.

  • For countries in fragile contexts (FCs), providers of development co-operation use guarantee instruments much more than in ODCs. Of the amounts mobilised by official development interventions in FCs, 65% are mobilised using guarantee instruments as against only 38% in non-FCs.

4.1. Official development finance by income groupings

From the donor community perspective, the key consideration when a country develops is to ensure a long-lasting impact of its development finance efforts. This implies a progressive mobilisation of domestic and private resources in a sound macroeconomic context (e.g. debt sustainability) towards independence from ODA while avoiding economic and development setbacks. Financing for development is about using the right instruments at the right time for the right projects towards greater development, gradually building capacity for a fast and smooth transition towards less reliance on ODA (See Box 4.1).

This section of the chapter provides an overview of ODF patterns – i.e. ODA and OOF – in different sectors and different country contexts to better understand interlinkages and trade-offs between these two types of flow.2 This overview highlights the transition of countries as they attract more OOF, a type of flow traditionally focused on productive investment that can raise productivity, incentivise job creation and develop human capital. In general, developing countries perceive the transition from ODA to OOF positively: the resources become more investment oriented and provide them with more tools to develop on their own.3 (Cordella and Ulku, 2007[1]) (Moss, Pettersson and Van de Walle, 2006[2]) (Gupta et al., 2004[3]) (Benedek et al., 2014[4]), (Bulow and Rogoff, 2005[5]).

4.1.1. An overview of official finance by income groupings

As for the rest of this report, the following overview is based on five main sector groupings: social, infrastructure, production, banking and business, and multisector over the period 2012-16.4 This section will focus on how ODA and OOF are allocated across sectors and income groups. The aim is to improve the understanding of behaviours and recommend reallocations of resources by providers to accelerate development processes or/and correct paths to facilitate sustainable FfD.

As described in Box 4.1, when countries pursue their development pathways, the relative weights of the different financing resources change. A snapshot for specific income groupings is shown in Figure 4.2 below.

Sector-allocable official finance to the poorest countries mostly consists of ODA, while OOF becomes more prominent when countries develop

Thus, ODA represent 93% of flows to LICs, where OOF represent the remaining 7%. The ODA portion falls to 64% in LMICs, OOF then accounting for 36% in this income grouping. In UMICs, the breakdown between ODA and OOF is almost the opposite of that in LMICs, with ODA being 34% of total ODF and OOFs being 66%.

Box 4.1. What is transition finance?

The study of transition finance consists of understanding the dynamics of external flows (concessional, non-concessional, private flows at market terms, philanthropy and remittances) - as well as domestic resources - to developing countries as they move along the development continuum. The ultimate objective is to combine the right policy and financing mixes to ensure the long-term effects and contribution of development finance to the Sustainable Development Goals (SDGs) (Cattaneo and Piemonte, 2018[6]). The OECD Global Outlook on Financing for Sustainable Development (OECD, 2018[7]) provides a holistic framework for navigating the global development finance architecture, supporting better policies for better finance and promoting inclusive and sustainable development. As shown in Figure 4.1, as countries pursue their development pathways, the relative weights of the different financing flows change: ODA resources decline; OOF, private and domestic resource mobilisation (DRM) resources grow with different patterns; and remittances show a parabolic trend. Observations made in this chapter should be seen in the overall context of this wider set of flows.

Figure 4.1. The mix of external flows changes as countries move along the development continuum
Average 2012-16, 2016 constant prices, USD billion disbursements
picture

Sources: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm (ODA, OOF); Development Assistance Committee (DAC) database (private flows); World Bank database (remittances); United Nations University World Institute for Development Economics Research (UNU-WIDER) database (tax revenues).

 StatLink https://doi.org/10.1787/888933855732

Figure 4.2. Concessionality of ODF decreases as countries develop economically
Share of ODA and OOF in total ODF by income and sector groupings, average 2012-16, 2016 constant prices, USD billion commitments
picture

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933855751

The overall transition from ODA to OOF is homogeneous across sector categories

All sector categories are largely ODA funded in LICs. LMICs still attract a large volume of ODA for the social sectors and infrastructure, but the banking and business and production sectors are becoming less dependent on concessional flows and can instead turn to non-concessional flows. In UMICs, every sector grouping is able to attract more OOF than ODA.5

Comparing the same sector in different income groupings reveals the following:

  • In volume terms, social sectors in LICS receive less ODF than LMICS, but three times more in per capita terms (see the right column in Figure 4.2 and columns 5, 6 and 7 in Table 4.2 further below for data in per capita terms). ODF to LICs represented USD 15.5 billion on average per year in the period 2012-16; nevertheless, this amount is smaller than in LMICs (USD 25.5 billion). However, in per capita terms ODF for social sectors to LICs (USD 24.1 on average per capita) is almost three times that of LMICs (USD 8.5 per capita). UMICs receive the smallest amount of ODF to social sectors among the three income groupings, both globally (USD 14.7 billion on average per year in the period 2012-16) and in per capita terms (USD 6.2).

  • While social sectors are not able to attract non-concessional flows in LICs, they are in second place in volume terms in UMICs, attracting 24% of total OOF to UMICs, even exceeding the production sectors (19%) (Table 4.1). UMICS use non-concessional resources in social sectors to engage in large projects for the structural reform of their economies (Box 4.2).

  • Infrastructure is the sector grouping where most of the non-concessional flows are concentrated (Table 4.1) with 61% of OOF going to LICs targeting infrastructure, while this percentage reaches 47% of OOF in LMICs and 38% in UMICs). This reflects the finding that investment in infrastructure can be financially and economically viable. This is especially true in energy and transport, where investments are concentrated (Herrera, 2005[9]) (Henckel, 2010[10]), (Estache, 2012[11]).

Table 4.1. Non-concessional flows are mostly concentrated in infrastructure
Volumes of other official flows by income group and shares by sector groupings, average 2012-16, 2016 constant prices, USD billion commitment

 

LICs

LMICs

UMICs

Total OOF to:

2.0

31.8

34.8

Social sectors

4%

14%

24%

Infrastructure

61%

47%

38%

Production sectors

21%

20%

19%

Banking & business

14%

16%

16%

Multisector

0%

3%

3%

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933855922

Box 4.2. Upper middle-income countries’ use of other official flows

Looking at other official flows (OOF) to upper middle-income countries in social sectors, Brazil receives the most (22% of total), followed by Mexico (14%) and Colombia (11%). These three Latin American countries concentrate their OOF finance in the governance sector. They use it to fund big macroeconomic stability programmes, mainly through Inter-American Development Bank (IADB) resources. For example, Brazil engaged in a fiscal stability consolidation programme for the development of the State of Bahia for USD 0.5 billion in 2012. Mexico received USD 0.7 billion in 2014 to support the development and implementation of alternatives for the strengthening and modernisation of its tax system. Colombia obtained a loan for USD 0.4 billion in 2014 to deepen its fiscal reform. These three examples show that these UMIC countries are able to undertake large structural reform programmes using non-concessional resources with the eventual aim of mobilising domestic resources.

Overall, providers seem to respond to countries’ financing needs as they move up the income ladder

LICs with little or no access to domestic or international financial markets are highly ODA dependent. Indeed, in cases of extreme poverty, external aid to social sectors, for example, may meet the most basic human needs, so donors are essentially fulfilling their role of solidarity. LMICs are already better able to access these markets and thus require fewer concessional resources. The donor community is responding by offering non-concessional loans to finance investment in the more profitable sectors, such as infrastructure. And finally, when countries reach the UMIC status, developing countries are able to benefit from (and are receiving) increasing levels of debt to sustain even more growth. They do this by diversifying their non-concessional finance to other sectors, such as production and structural reform programmes. Thus, at a macro level the international community is doing what seems most appropriate.

However, it is necessary to examine subsector resource allocations to better analyse some of the transition dynamics, such as the “middle-income trap” (see Box 4.3). This affects more than two-thirds of the recipient countries on the Development Assistance Committee (DAC) List of ODA recipients.6 It is important to remember that this analysis only covers ODF flows. Other flows such as private investments, DRM and remittances are not considered in this publication, but will be the subject of additional research within the OECD DAC. Obstacles to the progressive transition from ODF to non-ODF flows could better explain the traps or setbacks in the development path of a given country. Any FfD strategy should not limit itself to ODF, and the understanding of ODA versus OOF interactions should only be seen as a first step in the design of financial policies for development.7 (Ghatak, 2014[12]) (Kaldewei, 2015[13]) (Ratha, 2010[14]) (Sahay, 2015[15]) (Samargandi, 2013[16])

Box 4.3. What is the middle-income trap?

This concept was first suggested by the World Bank in 2005, and quickly gained popularity among economists. It refers to the fact that the majority of the countries that left the low-income country category to reach middle-income status in the 1960s and 1970s have remained there ever since. These economies showed sharp decelerations in growth and in increases in the pace of productivity, remaining “trapped” in the middle-income status and unable to become high-income economies.

Source: Authors based on (Agénor, 2017[17]), (Agénor, 2012[18]), (Aiyar, 2013[19]) (Gill, 2015[20])

4.1.2. Sub-sector and regional observations

Sub-sector allocations reveal more differentiated dynamics than those observed at sector grouping levels

Table 4.2 provides a snapshot (in columns 1, 2 and 3) of the distribution of ODF flows by subsector and income category. For example, column 2 indicates that LMICs attract more ODF resources than LICs and UMICs, for all the sectors. It then provides information on the average ODF volumes by sector (column 4). For example, health received USD 18.2 billion of ODF on average in the period 2012-16. Columns 5, 6 and 7 indicate the amount of ODF per capita for each income grouping. The table gives more dynamic information in columns 8, 9 and 10, showing how and when non-concessional loans take the lead (or not) in the composition of ODF by sector and income grouping. This demonstrates when countries engage in a virtuous cycle of being able to attract more OOF and becoming less ODA dependent.

Table 4.2. Sub-sector allocations reveal more differentiated dynamics than those observed at sector grouping levels
ODF by sector and income grouping, USD per capita, and shares of OOF by income grouping, average 2012-16, 2016 constant prices, USD billion commitment

 

ODF to LICs

ODF to LMICs

ODF to UMICs

Total ODF

(USD

billion, average 2012-16)

USD per capita

LICs

USD per capita

LMICs

USD per capita

UMICs

Share of OOF in LICs

Share of OOF in LMICs

Share of OOF in UMICs

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

Social sectors

24.1

8.5

6.2

Education

20%

49%

31%

12.2

3.8

2.0

1.6

2%

12%

48%

Health

40%

45%

16%

18.2

7.3

2.7

1.2

0%

6%

49%

Gov. & civil soc.

26%

44%

30%

17.9

11.2

2.6

2.3

0%

28%

58%

Other social

16%

48%

36%

7.4

1.8

1.2

1.1

0%

34%

74%

Infrastructure

13.0

12.5

7.7

Water

15%

56%

28%

11.6

2.8

2.2

1.4

6%

29%

70%

Energy

12%

63%

25%

25.2

4.5

5.1

2.5

16%

47%

68%

Transport & storage

13%

56%

31%

26.7

5.5

4.9

3.5

18%

33%

72%

Communications

8%

51%

41%

1.7

0.2

0.3

0.3

42%

64%

72%

Production sectors

7.0

4.4

3.5

Agriculture

29%

52%

19%

12.5

5.7

2.2

1.0

6%

23%

57%

Industry

5%

50%

46%

8.5

0.6

1.4

1.7

31%

79%

91%

Mining & construction

7%

61%

31%

2.6

0.3

0.6

0.4

39%

76%

83%

Trade & tourism

14%

35%

50%

1.9

0.4

0.2

0.4

7%

39%

91%

Banking & business

6%

46%

48%

15.4

1.4

2.5

3.4

32%

70%

75%

Multisector

16%

50%

34%

10.9

2.7

1.8

1.6

1%

20%

37%

Total

172.7

48.2

29.7

22.4

Note: For every line, columns 1, 2 and 3 add up to 100%, reflecting sector by sector how ODF is distributed in every income category; column 4 refers to total ODF by sector; columns 5, 6 and 7 show ODF per capita by income groupings and by sector; columns 8, 9 and 10 do not add up to 100% as they show how much OOF is directed to every sector in every income category (for example 2% of ODF flows in LICs are directed to education – so 98% of ODF to education in LICs are ODA flows).

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933855941

The main findings from Table 4.2 are as follows:

  • All sectors in LICs are mainly ODA financed, as shown by the share of non-concessional flows in total ODF. The proportion of OOF grows gradually as countries develop (columns 8, 9 and 10).8

  • In per capita terms, LICs receive more support than LMICs and UMICs in all social sectors (education, health, governance, and civil society, and other social, individually), the water sector, transport and storage, agriculture and multisector (see column 5). Only some infrastructure sectors (energy and communications), production sectors (industry, mining and construction), and banking and business receive more financing in LMICs and/or UMICs (see columns 6 and 7).

  • While most subsectors show fairly linear transition patterns from concessional to non-concessional financing, this is not the case for education and health. OOF financing could be triggered sooner in the development continuum, as it reaches only 6% of ODF in health and 12% in education in the LMIC category (28% in governance and 34% in other social sectors). Also, these proportions reach 49% in health and 48% in education in UMICs (so between 6 and 12%, and 49 and 48% the margin could be filled more progressively). Making more resources available in education and health is especially important as investing in these sectors can boost productivity improvements for long-term growth, precisely tackling major handicaps in the so-called middle-income trap.

  • Agriculture faces considerable challenges in attracting OOF compared to other productive sectors, across all developing country income categories. Among LICs only 6% of ODF is in the form of OOF, and while countries develop, the level remains well below the other sectors of the grouping. Agriculture is able to deliver high private and social profits, so a higher level of OOF would be desirable. This presumes taking into consideration the macroeconomic situation of each recipient country, its rate of debt in relation to its gross national income (GNI), capacity to respond to new obligations, etc.

  • The water sector in LICs seems to attract less non-concessional finance than other infrastructure sub-sectors. OOF to water in LICs are relatively small (6%) compared to the other sub-sectors of this grouping, but grow quickly, reaching 29% of non-concessional flows in LMICs and 70% in UMICs.

  • What is the ideal mix of external financial flows at each level of development? Can the donor community help engineer a virtuous transition pattern earlier in the development continuum? Is it possible to expect, for example, that in sectors such as health and education OOF (or other non-ODA flows) could shoulder a greater burden than ODA investments, prior to the UMIC stage of development? (See column 10, where non-concessional flows represent almost 50% of the total ODF reaching UMICs).9 If an LMIC has a healthy macroeconomic environment, helping it to accelerate reforms and invest in capacity building at this stage of development would improve its business environment and attract new and more capital to finance development. (Brown, 2001[21]) Could the donor community consider alternative financing for these sectors in LMICs if the macro environment of a country allows it?10 More considerations along these lines will be explored in forthcoming OECD work (OECD, 2018, forthcoming[22]).

Looking at ODF by income categories and regions (see Figure 4.3), the most striking aspects are:

  • Asia attracts the largest share of non-concessional flows in the LMIC and UMIC income categories.

  • America and Asia are able to trigger higher levels of OOF in the UMIC category, especially compared to Africa and Oceania.

Thus, there could be room for UMIC countries in Africa and Oceania to accelerate their transition from ODA to OOF.

Figure 4.3. Regions attract different levels of non-concessional flows across income groups
Share of ODA and OOF by income categories and regions, average 2012-16, 2016 constant prices, USD commitments
picture

Note: there are no LICs in Europe or Oceania.

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933855770

4.2. Official development finance to countries most in need

In recent years, the OECD DAC has been working to develop co-operation approaches and tools tailored to respond to a wide variety of country contexts, with a special focus on countries most in need (LDCs, LICs, LLDCs, SIDS and FCs).

At the 2014 DAC High-Level Meeting (HLM), ministers recognised the need to better target concessional finance and agreed to “allocate more of total ODA to ‘countries most in need’, including least developed countries (LDCs), low-income countries, SIDS, landlocked developing countries and fragile and conflict-affected states” (OECD, 2014[23]). The DAC reaffirmed this commitment at its 2016 HLM, acknowledging the need to better tailor development co-operation instruments and approaches to different country circumstances and needs (OECD, 2016[24]). In its May 2017 meeting, the DAC discussed the issue of transition finance in general and how it relates to countries most in need, in particular.

More recently, the 2017 DAC High Level Communiqué (OECD, 2017[25]) called for “analytical work to help identify where ODA is most needed (such as in least developed countries, low-income countries, small island developing states, landlocked developing countries, and fragile and conflict-affected contexts) and where additional actions may be required” (para. 19). It recognised “the need to ensure that development co-operation approaches and tools can effectively respond to the new complexity of sustainable development by providing appropriate support to countries as they transition through different phases of development” (para. 20). The Communiqué also called for review and reflection “on the evidence base that documents the consequences of different graduation processes on access to development finance from all sources, and (…) policy analysis on the different patterns of co-operation, including financing, channels, and objectives in countries in transition” (para. 20).

The following section will therefore provide analysis based on official finance targeting each of these groups of countries individually, over the period 2012-16.11 The differences and commonalities of the ODA/OOF interlinkages will be examined especially in relation to the sectors’ specific patterns followed by these flows. When relevant, the country groupings are compared with “Other developing countries” (ODCs), which include all countries on the DAC List of ODA Recipients minus the countries included in the country grouping under study (LDCs, LLDCs, SIDS or FCs). Comparing these four country groupings to ODCs highlights the extent to which development finance patterns in the country groupings differ from those in the rest of the developing countries outside this grouping.

4.2.1. Least developed countries (LDCs)

The LDC category contains 47 developing countries,12 representing 13% of the world’s population and 38% of the world’s extreme poor (see Box 4.4). These 47 countries are categorised as having long-term structural handicaps measured by three indicators, recorded simultaneously. A country can be included in the LDC category if:

  • at the moment of its examination: its GNI per capita (Atlas method, World Bank) is lower than USD 1 025

  • it has a human asset index (HAI) lower than 60

  • it has an economic vulnerability index (EVI) above 36.

Countries should also have a population size of less than 75 million for inclusion in this category (United Nations, 2008[26]), (United Nations, 2018[27]).

Today, the LDCs grouping is not composed exclusively of LICs, but also of 17 LMICs and even three UMICs due to the asymmetry in the inclusion and graduation criteria. From its creation in 1971, and despite several improvements to the definition criteria, to date only five countries have graduated from the LDC category: Botswana in 1994, Cabo Verde in 2007, Maldives in 2011, Samoa in 2014 and Equatorial Guinea in 2017. Vanuatu will be eligible for graduation in 2020 and Angola will be eligible in 2021.13

Figure 4.4 shows, for each of the LDC groupings, the composition of ODA and OOF received in 2012-16.

Figure 4.4. Least developed countries are highly funded by concessional finance
Share of ODA and OOF in total ODF (left hand chart) and share of ODA and OOF in total ODF by sector groupings (right hand chart) in LDCs, average 2012-16, 2016 constant prices, USD commitments
picture

Source: (OECD, 2018[8]), “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm

 StatLink https://doi.org/10.1787/888933855789

LDCs are highly funded by concessional finance, with most of the donor effort being concentrated in the social sectors and infrastructure

Total ODF to LDCs amounted to USD 45 billion during the period 2012-16, where concessional finance represented 91% or USD 40.8 billion (see Figure 4.4 and Table 4.3). Social sectors and infrastructure concentrated most of donor efforts (these two sectors represented 77% of total ODF to LDCs, mainly in the form of concessional flows). More granular sector allocation analysis reveals that health, followed by the government and civil society sectors, are by far the two social sectors most supported by providers of development co-operation. (Table 4.3).

Box 4.4. DAC members’ special measures regarding least developed countries

LDCs were first recognised as a group of countries of special interest for the DAC community in 1978. According to their Recommendation on the Terms and Conditions of Aid that year, DAC members agreed that the average grant element in ODA to LDCs should be either 90% of a given donor’s annual commitment to all LDCs, or at least 86% of the donors’ commitments to each individual LDC.

Another action was undertaken in 1981. This was introduced during the first United Nations conference on LDCs, where DAC donors committed to providing between 0.15% and 0.20% of donor GNI in the form of ODA to LDCs. This target is now contained in the Istanbul Programme of Action (2011) and states, for 2011-20:

  • that donor countries providing more than 0.20% of their GNI as ODA to least developed countries should continue to do so and maximise their efforts to further increase ODA to least developed countries;

  • that other donor countries which have met the 0.15% target should undertake to reach 0.20% expeditiously; and

  • that all other donor countries which have committed themselves to the 0.15% target have to reaffirm their commitment and undertake either to achieve the target by 2015 or to make their best efforts to accelerate their endeavours to reach the target.

Also, at their HLM in April 2001, DAC members declared their objective of untying ODA to LDCs to the greatest extent possible. They also stated their intention to promote and ensure adequate ODA flows, especially to LDCs. In January 2002, they specifically recommended the untying of LDCs in the following areas:

  • balance of payments and structural adjustment support

  • debt forgiveness

  • sector and multisector programmes assistance

  • investment project aid

  • import and commodity support

  • commercial services contracts and ODA to non-governmental organisations for procurement-related activities.

Finally, in December 2014, DAC members reached a new agreement to modernise reporting practices regarding ODA loans, thus creating incentives for providing highly subsidised loans to LDCs (OECD, 2015[28]).

Table 4.3. LDCs represent an opportunity for ODF providers to engage in non-ODA financing
DF volumes to LDCs and shares of OOF, average 2012-16, 2016 constant prices, USD billion commitments

 

ODA

OOF

Total ODF

OOF/ODF

Social sectors

 

 

 

 

Education

3.5

0.1

3.6

2%

Gov & civil soc.

6.0

0.1

6.1

2%

Health

8.9

0.0

8.9

0%

Other social infrastructure and services

1.7

0.0

1.7

1%

Infrastructure

 

 

 

 

Water

2.6

0.2

2.8

8%

Energy

4.3

1.3

5.6

24%

Transport & storage

4.6

0.9

5.5

16%

Communications

0.2

0.2

0.4

49%

Production sectors

 

 

 

 

Agriculture

4.6

0.3

4.8

5%

Industry

0.4

0.3

0.8

38%

Mining & construction

0.1

0.1

0.2

38%

Trade & tourism

0.3

0.0

0.3

13%

Banking & business

1.0

0.6

1.6

39%

Multisector

2.6

0.0

2.6

2%

Total

40.8

4.2

45.0

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933855960

Some key questions on the financing of LDCs require specific attention by the development community

While this publication focuses on providing an overview of sector financing, the analysis carried out raised a number of questions related to LDC financing. These require further study. For example, is the low level of OOF explained by the specific needs of LDCs in terms of concessional finance? Or could it be that donors do not wish to carry out OOF operations because they first need to maximise their ODA levels to meet their ODA commitments? Are social and/or economic vulnerabilities (the other two factors, in addition to GNI per capita, that determine the LDC status (Alonso, 2014[29])) such that they justify low levels of OOF in certain sectors?14 Or is it that LDCs’ risk ratings are so high that it makes it simply prohibitive for them to borrow? Finally, could this situation reflect debt sustainability issues that prohibit borrowing from responsible lenders?

LDCs represent an opportunity for ODF providers to engage in non-ODA financing

Even if LDCs are often perceived as more risky, they also represent opportunities for providers to engage in non-ODA financing (UNCTAD, 2011[30]). This is in line with the call made in the Addis Ababa Action Agenda (AAAA) (United Nations, 2015[31]) to mobilise all resources for developing countries. The AAAA also recognises that funding sources additional to ODA are necessary to provide the financing needs for achieving the 2030 Agenda. Therefore non-ODA financing opportunities should also be explored in LDCs. Box 4.5 provides examples of such opportunities in the renewable energy sector.

Box 4.5. Examples of private investments in least developed countries

1. Cambodia solar power project

This project involved the construction and operation, using local resources, of a 10 MW solar power plant in Bavet City, Svay Rieng Province, Cambodia, on a build-own-operate basis. There was an acute energy shortage in Svay Rieng Province, which has special economic zones with growing industrial economic activity and consequently a rising demand for electricity. The province had been relying entirely on imported power from Viet Nam, whose supply was insufficient and unstable. The project represented the first utility-scale solar power plant and the first competitively tendered private-sector renewable energy project in the country. The project sells power to Électricité du Cambodge at a very competitive tariff, below the average supply cost, without any feed-in tariffs or subsidies. The project was ripe for blended finance, and the USD 13.6 million cost was funded by equity and USD 9.2 million of debt (including a long-term direct loan of USD 3.25 million from the Asian Development Bank). Construction started in September 2016, generation started in August 2017, and commercial operations were achieved in October 2017. This project demonstrated the benefits of increasing Cambodia’s power supply through the involvement of the private sector. It also signalled to the market that infrastructure investments led by the private sector can be successfully undertaken in a transparent manner, at a competitive price and with a sound financing package. As such, the project will contribute to meeting the electricity demand, including a balanced electricity supply between dry and wet seasons. It will also enable full electrification of villages by 2020 and electrification of 70% of households via the national grid by 2030.

2. Mobisol in Kenya, Rwanda and the United Republic of Tanzania

Mobisol is a German private company that provides affordable stand-alone solar energy systems for households and small businesses in rural Kenya, Rwanda and United Republic of Tanzania (“Tanzania”). Mobisol’s products are made affordable by a rent-to-own scheme that offers microfinance loans over a period of 48 months in small instalments that are payable via mobile money. Mobisol solar energy systems come with a full service package that includes customer service, free maintenance and remote monitoring technology. The systems can illuminate households; power laptops, radios, TVs, and fridges; and charge mobile phones.

Mobisol’s first investor, a professional in the German solar industry, financed Mobisol’s initial product development and its first employees. After successfully completing the pilot phase, the company was able to attract further investors and development finance institutions such as Germany’s Deutsche Investitions- und Entwicklungsgesellschaft (DEG) and Finnfund. Blended finance from international donors was particularly relevant for project scaling and the early project development phases. In terms of results, over 120 000 households were electrified and over 12.1 MW solar capacity was installed. Over 580 000 indirect beneficiaries profited from electrification infrastructure substituting grid connection. Almost 700 full-time staff were employed and about 1 400 small entrepreneurs worked as contractors, over 95% of them in Rwanda and Tanzania.

Source: OECD Secretariat’s survey carried out in preparation for this publication.

4.2.2. Landlocked developing countries

The Landlocked developing countries (LLDCs) category is a grouping of 32 developing countries15 that face particular challenges related to their lack of direct access to the sea, which leads to geographical isolation from international markets. Imports and exports of goods and services need to transit through other countries. This generates higher trade costs, major logistical and infrastructure challenges (e.g. changes in transport modes, international road and rail connections with neighbours’ networks, etc.). All of these impose serious constraints on their development.16 Infrastructure is the main sector in which LLDCs need assistance in order to overcome their isolation and facilitate their path to development. Currently, high transport costs erode the competitiveness of LLDCs (most LLDCs are commodity exporters). They spend almost twice as much of their export earnings on transport and insurance services than the average for developing countries (and three times more than the average for developed economies).17

In 1965, the United Nations Convention on Transit Trade of Landlocked States addressed LLDCs’ concerns for the first time. In 1970 the General Assembly, within the context of the Second United Nations Development Decade, included a section on special measures in favour of LLDCs. It called for “appropriate attention to the special needs of LLDCs in extending adequate financial and technical assistance to projects designed for the development and improvement of the transport and communications infrastructure needed by these countries”. The situation of transit transport systems was reviewed again in 1995 (at the General Assembly) and in 2003 (at the United Nations global conference in Kazakhstan). A programme of action was adopted as a result, focusing on transport infrastructure and maintenance, transit policies and trade facilitation measures.

LLDCs have unrealised potential to attract non-ODA flows

As shown in Figure 4.5, only 23% of total official aid, USD 7.3 billion per year over 2012-16, was provided in the form of OOF to LLDCs, compared to 44% for ODCs.

Figure 4.5. LLDCs have unrealised potential to attract non-ODA flows
Share of OOF and ODA in LLDCs and ODCs, average 2012-16, 2016 constant prices, USD commitments
picture

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm

 StatLink https://doi.org/10.1787/888933855808

Providers need to redouble efforts towards infrastructure investments in LLDCs

Providers’ support to LLDCs mainly focuses on social sectors – infrastructure is only the second most supported sector. Total ODF to social sectors was USD 13 billion over the period 2012-16 (41% of total ODF to LLDCs). Support to infrastructure amounted to USD 10.3 billion (33 % of total ODF to LLDCs) (Figure 4.6). Also, LLDCs get a similar share of their ODF going to key infrastructure sectors in comparison to ODCs (33% compared to 34% for ODCs). Providers should therefore carefully consider increasing their support on hard and soft infrastructure investment in LLDCs.

Figure 4.6. Providers need to redouble efforts towards infrastructure investments in landlocked developing countries
Share of ODA and OOF in LLDCs by sector groupings, and shares of ODF by sector groupings in LLDCs and ODCs, average 2012-16, 2016 constant prices, USD commitments
picture

Note: the double pie chart on the right shows total ODF to LLDCs in the inner circle and total ODF to all ODCs in the outer circle.

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933855827

The lower levels of total ODF to infrastructure in LLDCs compared to ODCs are due to smaller provisions of non-concessional finance to the energy and water sectors

The lower levels of total ODF to infrastructure in LLDCs compared to ODCs are explained by smaller provisions of non-concessional finance to the energy and water sectors (35% versus 50% and 14% versus 40%, respectively). They are not explained, as could be expected, by transport and storage. In fact, LLDCs receive slightly more OOF as a percentage of total ODF than ODCs in transport and storage: 44% versus 43%, respectively. (Table 4.4 and Table 4.5).

Table 4.4. LLDCs receive a smaller share of OOF for energy and water than ODCs
Volumes of ODA, OOF and ODF and share of OOF by sector in LLDCs, average 2012-16, 2016 constant prices, USD commitments

 

ODA

OOF

Total ODF

Share of OOF

in total ODF to this sector

Social sectors

Education

1.9

0.1

2.1

7%

Health

5.0

0.1

5.0

1%

Gov. & civil soc.

4.2

0.4

4.6

9%

Other social infrastructure and services

1.0

0.2

1.3

19%

Infrastructure

Water

1.6

0.3

1.9

14%

Energy

2.4

1.3

3.7

35%

Transport & storage

2.6

2.0

4.6

44%

Communications

0.1

0.1

0.1

61%

Production sectors

Agriculture

3.1

0.5

3.6

14%

Industry

0.3

0.4

0.7

59%

Mining & construction

0.1

0.7

0.8

92%

Trade & tourism

0.2

0.0

0.3

15%

Banking & business

0.6

1.0

1.6

62%

Multisector

1.3

0.1

1.4

5%

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933855979

Table 4.5. ODCs receive a larger share of OOF for energy and water than LLDCs
Volumes of ODA, OOF and ODF and share of OOF by sector in ODCs, average 2012-16, 2016 constant prices, USD commitments

 

ODA

OOF

Total ODF

Share of OOF

In total ODF to this sector

Social sectors

Education

9.6

2.5

12.1

20%

Gov. & civil soc.

13.0

4.9

17.9

27%

Health

16.6

1.9

18.5

10%

Other social infrastructure and services

3.9

2.9

6.9

43%

Infrastructure

Water

6.3

4.2

10.5

40%

Energy

11.7

11.5

23.2

50%

Transport & storage

12.9

9.7

22.6

43%

Communications

0.7

1.2

1.8

64%

Production sectors

Agriculture

8.2

2.8

11.0

26%

Industry

1.8

7.0

8.7

80%

Mining & construction

0.6

1.3

2.0

69%

Trade & tourism

1.0

1.3

2.3

56%

Banking and business

5.8

12.0

17.8

67%

Multisector

13.8

2.4

16.2

15%

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933855998

4.2.3. Small island developing states (SIDS)

The OECD DAC identifies 35 countries18 as SIDS, located across different geographic areas. SIDS share a number of structural challenges and geophysical constraints that result in disproportionately large economic, social and environmental challenges. These structural features have a major impact on SIDS’ ability to access finance (OECD, 2018[32]) (OECD/The World Bank, 2016[33]). There are numerous commonalities among the countries in this group, such as small geographic and population sizes, remoteness and high exposure to environmental disasters. However, large differences also exist in terms of income level, population density, geographic spread and relative development progress. While most SIDS are UMICs (24 countries), 8 are LMICs and another 3 are LICs.

Concessional finance represents the bulk of ODF to SIDS

During 2012-16, SIDS received on average USD 4.3 billion in official concessional finance each year from bilateral and multilateral donors,19 representing 75% of their total official flows, compared to 64% for ODCs (Figure 4.7).

Figure 4.7. Concessional finance represents the bulk of ODF to SIDS
Share of ODA and OOF to SIDS and ODCS, average 2012-16, 2016 constant prices, USD commitments
picture

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933855846

High proportion of ODA in the ODF to SIDS in all income categories

The high proportion of ODA in the composition of ODF to SIDS is valid for all income categories. In LIC-SIDS ODA flows represented 97% of ODF versus 93% for other LICs, in LMIC-SIDS ODA represented 91% of total ODF and 63% for other LMICs, and even in UMIC-SIDS ODA was 52% of total ODF flows compared to 32% for other UMICs).

Figure 4.8 shows the allocation of official resources to SIDS by income group broken down by the main sector groupings. When analysing the underlying financing patterns of the different income groupings, it emerges that LIC-SIDS and Other LICs are very similar. However, this is not the case for the other two categories. LMIC-SIDS and UMIC-SIDS receive, in relative terms, less non-concessional flows than Other LMICs and Other UMICs in each of the sector groupings (except for banking and business in the UMIC category). This is even more evident in the production sectors (non-concessional flows in LMIC-SIDS represent 6% of total ODF but 82% in Other LMICs; compared to 34% in UMIC-SIDS and 82% in Other UMICs).

Figure 4.8. ODA represents the bulk of ODF to SIDS in all income and sector groupings
Share of ODA and OOF in ODF to SIDS by income and sector groupings, average 2012-16, 2016 constant prices, USD commitments
picture

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933855865

In order to identify the underfinanced subsectors of the sector groupings just highlighted, Table 4.6 shows the sector component of each of the sector groupings compared with ODCs for LMIC-SIDS and UMIC-SIDS.20

SIDS find it difficult to follow a virtuous transition path towards more OOF, and remain highly ODA dependent for almost all sub-sectors

For almost all sub-sectors, non-concessional finance is lower for SIDS than for ODCs at any income category (see the “Share of OOF” column in Table 4.6).21 This shows the difficulty that SIDS have in following the virtuous transition finance path shown at the beginning of this chapter (see Box 4.1) and achieving sustainable development (with ODA decreasing, OOF increasing, then private flows and DRM flows growing exponentially). It also suggests that the donor community should reflect on ways to make the most of ODF in preparation for transition in these countries.22

There are several possible reasons why OOF do not reach SIDS as they should in LMICs or UMICs:

  • SIDS benefit from a “small island exception” from the World Bank. It permits the provision of International Development Association (IDA) resources to small island economies with a per capita income above the operational cut off for IDA eligibility. As a consequence, non-ODA resources are supplied at a higher income status, sustaining the countries’ abilities to access concessional financing. This could create windfall effects and discourage financing sources other than ODA. For example, in the production sector, it appears that only the International Finance Corporation (IFC) and Korea provided non-concessional loans to LMIC-SIDS in the period 2012-16, and that there were just three new providers in the UMIC category (Inter-American Development Bank [IADB], International Bank of Reconstruction and Development [IBRD] and Belgium). However, SIDS would have been expected to have IBRD funds at LMIC status (in non-small island exception countries) as well, and, in general, a bigger diversity of non-concessional finance providers. It could be useful to analyse the possibility of changing the composition of ODF flows on a country-by-country basis. It could also be useful to evaluate the opportunities for reallocating ODA and OOF across sectors in order to face the transition gaps, mobilise non-ODF flows and trigger the transition patterns of foreign direct investments and DRM financing.

  • In addition, the current average high levels of public debt facing some SIDS could explain difficulties with regards to prospective access to non-concessional or private finance. High levels of public debt result in a higher risk of default, limiting the provision of new debt and making it more expensive to borrow.

  • Further factors could relate to the absorptive capacity and management of new projects (financed by new debt). The low rate of return of some projects could be added to these, especially in the infrastructure sector, because of diseconomies of scale resulting from the provision of public goods to small populations. An economy must be capable of attracting new (non-concessional) resources as a first step to reaching more and new financing to replace ODA finance, taking on the responsibility of its management and acquiring the capacities and skills for its long-term development. In order to do so, it is important to consider new and more risk-mitigating instruments (see Chapter 5). It is also important to convince donors that are traditionally ODA-only providers to consider diversifying their funding modalities.

Table 4.6. SIDS find it difficult to follow a virtuous transition path towards more OOF
Volumes of ODA, OOF and ODF and share of OOF by income and sectors, average 2012-16,
2016 constant prices, USD million commitments

LMIC-SIDS

ODA

OOF

Total ODF

Share of OOF

Other LMICs

ODA

OOF

Total ODF

Share of OOF

Social sectors

Social sectors

Education

201.3

0.0

201.3

0%

Education

5 064.7

716.1

5780.7

12%

Health

218.1

0.0

218.1

0%

Health

7 439.1

471.1

7 910.2

29%

Gov. & civil soc.

333.1

3.3

336.4

1%

Gov. & civil soc.

5 290.4

2 204.3

7 494.7

6%

Other social

51.6

0.0

51.6

0%

Other social

2 313.6

1 209.7

3 523.3

34%

Infrastructure

Infrastructure

Water

91.3

0.7

92.0

1%

Water

4 525.0

1 915.7

6 440.7

30%

Energy

77.9

36.2

114.1

32%

Energy

8 348.8

7 464.3

15 813.1

47%

Transport & storage

320.6

98.0

418.7

23%

Transport & storage

9 683.1

4 816.7

14 499.8

33%

Communications

15.3

7.7

23.0

34%

Communications

303.2

553.7

856.9

65%

Production

Production

Agriculture

114.2

2.1

116.3

2%

Agriculture

4 871.7

1 459.1

6 330.8

23%

Industry

2.6

1.8

4.4

41%

Industry

874.9

3 343.5

4 218.4

79%

Mining & construction

1.1

5.0

6.1

81%

Mining & construction

378.9

1 229.8

1 608.8

76%

Trade & tourism

9.7

0.0

9.7

0%

Trade & tourism

390.9

261.4

652.3

40%

Banking & business

23.6

9.5

33.0

29%

Banking & business

2 085.0

4 959.3

7 044.4

70%

Multisector

164.3

0.0

164.3

0%

Multisector

4 229.4

1 076.4

5 305.8

20%

UMIC-SIDS

ODA

OOF

Total ODF

Share of OOF

Other UMICs

ODA

OOF

Total ODF

Share of OOF

Social sectors

Social sectors

Education

149.5

101.0

250.4

40%

Education

1 810.4

1 674.1

3 484.4

48%

Health

126.0

156.0

282.0

55%

Health

1 347.2

1 268.8

2 616.0

49%

Gov. & civil soc.

162.6

166.2

328.8

51%

Gov. & civil soc.

2 082.7

2 924.6

5 077.3

58%

Other social

40.8

116.8

157.6

74%

Other social

645.4

1 858.0

2 503.3

74%

Infrastructure

Infrastructure

Water

144.6

25.4

170.0

15%

Water

817.1

2 352.2

3 169.3

74%

Energy

145.7

121.0

266.7

45%

Energy

1 869

4 155

6 024

69%

Transport & storage

117.1

178.3

295.4

60%

Transport & storage

2 100.9

5 824.9

7 925.8

73%

Communications

25.8

26.3

52.1

51%

Communications

173.3

490.4

663.7

74%

Production

Production

Agriculture

112.6

18.2

130.7

13%

Agriculture

897.5

1 327.9

2 225.4

60%

Industry

18.9

12.5

31.3

40%

Industry

322.9

3 543.3

3 866.2

92%

Mining & construction

2.1

12.3

14.4

86%

Mining & construction

127.1

706.7

833.8

85%

Trade & tourism

18.6

39.0

57.6

68%

Trade & tourism

66.8

822.7

889.5

92%

Banking & business

36.6

197.3

233.9

84%

Banking & business

1 782.3

5 809.9

7 592.2

77%

Multisector

244.0

9.1

253.1

4%

Multisector

2 056.8

1 351.8

3 408.6

40%

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933856017

4.2.4. Countries in fragile contexts (FCs)

The OECD DAC defines fragility23 as the combination of exposure to risk and insufficient capacity of the state, system and/or communities to manage, absorb or mitigate those risks. The fragility framework (OECD, 2016[24]) is built around five dimensions: economic, environmental, political, societal and security. Using these, the 2018 OECD’s States of Fragility Report (OECD, 2018[34]) identifies 58 FCs24 (28 LICs, 26 LMICs and 4 UMICs), of which 15 are extreme FCs.

Because of the way that the FCs are defined and the many variables taken into account (see Box 4.6), the final list of FCs is very diverse. Therefore compiling sector statistics for this group of 58 FCs does not appear sufficiently robust.25 For these reasons, the analysis in this subsection focuses on the overall picture of ODA and OOF rather than providing a detailed sector analysis, as for previous country groupings. As a way to advance the policy discussion on interventions in FCs, this subsection provides an overview on the use of various financial instruments, including risk-management instruments, recognising that FCs are often perceived as riskier areas by both public and private actors.

Box 4.6. The OECD’s states of fragility: taking a multidimensional approach to fragility

The notion of sustainable development is profoundly multidimensional, and nowhere is this truer than in FCs. Therefore, analysing these FCs, designing the right programming, making allocation decisions and measuring results also requires taking a multidimensional approach to well-being rather than a sector approach.

The OECD has long recognised the multidimensionality of people’s well-being and of the resources needed to sustain this over time. With this in mind, the OECD developed a multidimensional well-being framework – the Better Life Index – that can gauge whether people’s lives are improving, and inform policy efforts toward this end at the same time. Starting in 2015, this concept has been applied to the states of fragility framework and to the approaches that OECD members are encouraged to take when working in FCs.

The OECD’s multidimensional approach recognises five different dimensions of fragility, with extensive interlinkages between them:

  • economic fragility: vulnerability to risks stemming from weaknesses in economic foundations and human capital

  • environmental fragility: vulnerability to environmental, climatic and health risks that affect people’s lives and livelihoods

  • political fragility: vulnerability to risks inherent in political processes, events or decisions

  • security fragility: vulnerability of overall security to violence and crime, including both political and social violence

  • societal fragility: vulnerability to risks affecting social cohesion that stem from both vertical and horizontal inequalities.

The approach measures each of these dimensions on a spectrum of intensity that links fragility with a combination of risks and coping capacities, and then synthesises the results (the multidimensional aspect). While previous approaches framed fragility as a matter of weak governance, the new fragility framework builds on the recognition that fragility influences states and societies in different ways. It affects all countries to some degree, not just developing countries. It is part of OECD’s larger effort to move away from the “fragile states list” – a binary view of the world – towards a universal concept of fragility.

Source: (OECD, 2016[24]), "States of Fragility 2016: Understanding Violence", http://dx.doi.org/10.1787/9789264267213-en

Figure 4.9 shows the list of countries defined as FCs when applying the fragility framework.

Figure 4.9. The States of Fragility Framework, 2018
picture

Note: The States of fragility framework was designed before the change of name of Swaziland - now called Kingdom of Eswatini.

Source : (OECD, 2018[35]), "States of Fragility Framework", http://www.oecd.org/dac/conflict-fragility-resilience/statesoffragilityframework2018.htm

ODA remains a critical source of finance for fragile contexts

Figure 4.10 gives a descriptive snapshot of the situation of these 58 fragile contexts in a sector ODF perspective. It shows that ODF (which represented USD 66.8 billion on average per year over the period 2012-16 on a commitment basis) in FCs comprises much more ODA (91%) than in ODCs (61%). This is in line with the 2030 Agenda, where ODA is called on to play a specialised role, targeting critical gaps where it adds the most value according to the context.

Figure 4.10. ODA remains a critical source of finance for fragile contexts
Share of ODA and OOF in ODF to FCs and ODCs, average 2012-16, 2016 constant prices, USD commitments
picture

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm.

 StatLink https://doi.org/10.1787/888933855884

Fragility and vulnerability are associated with risk in development. In order to mitigate these perceived risks, guarantees, insurances and blended finance facilities can be deployed to fragile contexts

For example, the International Finance Corporation–Multilateral Investment Guarantee Agency (IFC–MIGA) private sector window (PSW) (MIGA,(n.d.)[36]) was created under the IDA18 replenishment to expand private investment in the poorest countries and in particular those identified as fragile. Under four windows, PSW provides project-based guarantees without sovereign indemnity to source private investment for large infrastructure projects. The MIGA Guarantee Facility expands coverage of MIGA guarantees via reinsurance. The Local Currency Facility provides long-term local currency investments in countries where capital markets are not developed. The Blended Finance Facility blends support with IFC investments to help small and medium-sized enterprises. New instruments are also being created and especially adapted to FCs – parametric insurance, sovereign risk financing, catastrophe bonds and micro insurance (Poole, 2018[37]).

Official providers are using risk-mitigation instruments, such as guarantees, in FCs much more than in other contexts

As shown in Figure 4.11, 22% of all private finance mobilised by ODF interventions targets FCs. When looking at the composition of instruments used to mobilise this finance in FCs and non-FCs, it appears that providers make great use of guarantees in FCs. Of the amounts mobilised in FCs, 65% are done so using guarantee instruments, as against only 38% in non-FCs. This figure is encouraging as it shows that providers effectively consider the risk perceived by the private sector and use appropriate instruments, such as guarantees, to address it.

Figure 4.11. Official providers use higher proportions of guarantees in fragile contexts
Share of amounts mobilised from the private sector by ODF interventions and share of instruments used to mobilise private finance in FCs and non-FCs, average 2012-16, 2016 constant prices, USD commitments
picture

Note: the double pie chart on the right shows FCs in the inner circle and all ODCs in the outer circle.

Source: (OECD, 2018[8]) “International development statistics (database)”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-data/idsonline.htm and (OECD, 2016[38]), “OECD DAC survey on amounts mobilised from the private sector by official development finance interventions 2012-2015”, http://www.oecd.org/dac/financing-sustainable-development/development-finance-standards/mobilisation.htm with estimates for 2016.

 StatLink https://doi.org/10.1787/888933855903

References

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Notes

← 1. The World Bank income categories are: low income countries (LICs), lower middle-income countries (LMICs), upper middle-income countries (UMICs), and high-income countries (HICs). The World Bank classifies countries into these groups based on their GNI per capita using the Atlas method. The current thresholds are as follows: LICs: < USD 1 005 per capita; LMICs: USD 1 006-3 955; UMICs: USD 3 956-12 235 and HICs: > USD 12 236. The DAC defines countries most in need as: least developed countries (LDCs), landlocked developing countries (LLDCs), small island developing states (SIDS) and fragile and conflict-affected contexts (FCs).

← 2. The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.

← 3. Loans with greater concessionality may be prone to being over-borrowed and therefore less efficiently used than loans with less concessionality. This decreases the need for efficient investment (Odedokun, 2003[39]); (Moss, Pettersson and Van de Walle, 2006[2])Moss. Moreover, given the fact that loans need to be repaid, a higher level of loans in official assistance associated with higher interest rates would require higher mobilisation of fiscal revenues. It would also require investment in high-impact projects. In fact, a higher proportion of loans in official assistance was associated with larger domestic revenues (Gupta et al., 2004[3]); (Benedek et al., 2014[4]) (Cordella and Ulku, 2007[1]) found that “the level of loan concessionality that maximises growth: (i) is negatively correlated with the quality of a recipient country’s policy and institutions, (ii) decreases with the level of initial income, (iii) and increases with the existing debt obligations.” Other voices have called for increasing the number of grants distributed (Bulow and Rogoff, 2005[5]), so as to take into account the risk exposure of development banks rather than favouring the emergence of developing countries.

← 4. See the Annex at the end of this report for more information, and in particular a list of the subsectors that make up these five sector categories.

← 5. Except for the “multisector” grouping, which is not a sector grouping per se.

← 6. Until the 1990s the neoclassical growth model (Solow) was largely accepted, as it provided a good explanation of what happened in the growth processes. The model basically suggests that differences in observed growth across countries stem from factor accumulation, especially capital investment. This model is still useful for LICs. However, with accelerating technological upgrading, it is no longer useful for middle-income countries.

← 7. For example, any FfD strategy should include a plan to remove or reduce those obstacles through capacity building and investment in transformational change enablers.

← 8. Combining all income categories (LICs, LMICs and UMICs) and excluding regional/unspecified flows, OOF represents 24% of total official flows in social sectors, 45% in infrastructure, 54% in production sectors and 72% in banking and business.

← 9. As countries experience growth and transition through the development continuum (i.e. moving from low to higher levels of GNI per capita), it is possible to observe some distinctive patterns for each of the financial flows composing the global set of external flows they receive. Among other external flows, concessional flows (ODA) decrease and non-concessional flows (OOF) increase (Cattaneo, O. and Piemonte, C., 2018[7]).

← 10. It is important to highlight these two sectors as they are key to removing inequalities in society and to combating poverty. Improvements in these two sectors can help countries to escape from the well-known middle-income trap.

← 11. With the exception of LICs, analysed in the preceding section.

← 12. LDCs: Afghanistan, Angola, Bangladesh, Benin, Bhutan, Burkina Faso, Burundi, Cambodia, Central African Republic, Chad, Comoros, Democratic Republic of the Congo (hereafter “DRC”), Djibouti, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Haiti, Kiribati, Lao People’s Democratic Republic (hereafter “Lao PDR”), Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mozambique, Myanmar, Nepal, Niger, Rwanda, São Tomé and Principe, Senegal, Sierra Leone, Solomon Islands, Somalia, South Sudan, Sudan, Timor-Leste, Togo, Tuvalu, Uganda, United Republic of Tanzania, Vanuatu, Yemen and Zambia.

← 13. To avoid setbacks, the LDC graduation criteria states that a country eligible for graduation must cease to meet two of the three graduation thresholds, and that this eligibility must be observed over two consecutive triennial reviews. To ensure a smooth transition, the General Assembly recommended the extension and gradual phasing out of LDC-specific support for some time after graduation.

← 14. Nevertheless, when looking at OOF loans, Bangladesh was able to benefit from considerable volumes from the Asian Development Bank in recent years: 20 loans delivered in the period 2012-16 for a total of USD 2.8 billion, mainly spent on energy and transport and storage.

← 15. Afghanistan, Armenia, Azerbaijan, Bhutan, Plurinational State of Bolivia, Botswana, Burkina Faso, Burundi, Central African Republic, Chad, Kingdom of Eswatini, Ethiopia, the Former Yugoslav Republic of Macedonia, Kazakhstan, Kyrgyzstan, Lao PDR, Lesotho, Malawi, Mali, Republic of Moldova, Mongolia, Nepal, Niger, Paraguay, Rwanda, South Sudan, Tajikistan, Turkmenistan, Uganda, Uzbekistan, Zambia, Zimbabwe.

← 16. Other areas that are major constraints to LLDCs’ development include high dependency on commodities, lack of value addition to exports or limited industrialisation.

← 17. These figures are based on the United Nations Conference on Trade and Development (UNCTAD) estimates derived from the International Monetary Fund (IMF) balance of payment statistics (UNCTAD, 2018[41]).

← 18. As for other country groupings, there are several definitions of SIDS. The United Nations identify 52 countries or territories under this grouping. They first defined a SIDS grouping in 1992, then came others such as the European Union with ACP (Africa, Caribbean and Pacific), and the World Trade Organisation with the economic vulnerability index (Small Vulnerable Economies). The World Bank has been applying a small island exception in determining IDA eligibility since 1985.

← 19. Including the regional groupings Oceania and West Indies.

← 20. The analysis by subsector has not been included for LIC-SIDS versus other LICs, as the results are almost the same.

← 21. Trade and tourism in both the LMIC-SIDS and UMIC-SIDS categories are OOF-neglected (0% in LMIC-SIDS versus 40% for Other LMICs and 68% for UMIC-SIDS versus 92% for Other UMICs). This means that major current investments in this sector are financed by foreign direct investment. It also means that there are no resources flowing directly to local investors for them to invest in this sector. Knowing the huge potential of tourism in SIDS, a study could be conducted into whether mixed investments could better fill the gap of capacity building for the local population and whether some incentives could be put in place to prepare SIDS to develop in the long run could also be analysed. It could be useful to explore some options involving quality investment.

← 22. As discussed in previous OECD work on SIDS, while the broad nature of development needs in several SIDS can make prioritisation difficult, some areas and sectors that would seem vital to promoting sustainable development in SIDS receive relatively little support. For instance, high costs and limited access to energy constrain development in SIDS, yet the energy sector received less than 9% of total ODF to SIDS in 2012-16.

← 23. There are several other definitions of fragility, such as those from the World Bank, the UK government’s Department for International Development (DFID) and the Overseas Development Institute (ODI). The different lists of fragile countries differ by the theoretical background concepts and the use of different indicators, proxies and/or value judgments.

← 24. From a total of 146 ODA-eligible countries.

← 25. This is why the OECD takes a multidimensional approach to analysing ODA flows to FCs, rather than using traditional sectors. For example, the States of Fragility Report identifies ODA flows that seek to reduce economic fragility. It also analyses whether contexts that are economically fragile are receiving ODA targeted at the root causes of that form of fragility. The results are interesting: some of the extremely fragile contexts with respect to the long-term drivers of growth receive fairly high levels of ODA per capita (Liberia, Solomon Islands and South Sudan), but others do not (Burundi, Central African Republic, Chad and DRC). In some specific sectors, ODA per capita is even negatively correlated to fragility in the long-term drivers of growth. This is the case, for instance, for industry and mining and construction, which tends to prioritise non-FCs with relatively sound economic fundamentals (such as Mauritius, Serbia and Tunisia).

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