Chapter 1. Characteristics and vulnerabilities of small island developing states

Small island developing states (SIDS) have unique characteristics that contribute to their vulnerability to shocks and pose persistent challenges to their development. After reviewing definition issues, this chapter assesses the economic and development performance in SIDS compared to larger developing countries and unpacks geophysical and economic features that contribute to their vulnerability.

1.1. Small island developing states: a diverse group with strong commonalities

1.1.1. Definitions of SIDS

A number of lists of SIDS exist, including those established by: (i) the United Nations Office of the High Representative for the Least Developed Countries, Landlocked Developing Countries and Small Island Developing States (UN-OHRLLS) comprising 52 SIDS (38 of which are United Nations (UN) member states); (ii) the Alliance of Small Island States, comprising 39 SIDS; and (iii) the UN Conference on Trade and Development, comprising 29 SIDS. The World Bank Group defines small states as countries that: (a) have a population of 1.5 million or less; or (b) are members of the World Bank Group Small States Forum. Fifty small states fit this definition, including 27 of the 35 ODA-eligible SIDS considered in this report and landlocked states.

Given the focus of this report on financing for development and the role of concessional finance in SIDS in particular, this report considers the 35 SIDS that are eligible for official development assistance (ODA). These include: 9 least developed countries, 5 lower middle-income countries and 21 upper middle-income countries. 1 As illustrated in Figure 1.1, 7 of these SIDS are in the Africa, Indian Ocean, Mediterranean and South China Sea (AIMS) region, 13 are in the Caribbean and 15 are in the Pacific.

The spread of SIDS across different regions and oncome categories suggests that they are a diverse and heterogeneous group of countries that nevertheless share strong commonalities. This report attempts to review both elements of heterogeneity and commonality, in particular in the light of economic growth, development performance, and vulnerability factors.

There are significant variations across SIDS

SIDS exhibit large variations in terms of population size and densities, geographical spread, natural resources endowments and relative development progress. Even among SIDS in the same region or belonging to the same income category, very distinct opportunities for growth and varied needs for support from the international community exist. Within the Pacific region, for instance, gross national income (GNI) per capita ranges from a low of USD 1 830 in the Solomon Islands to a high of USD 13 330 in Nauru (influenced by Nauru’s small population size). Populations can range from under 1 600 inhabitants in Niue to over 7 million in Papua New Guinea. Remoteness from shipping lanes is highly pronounced in Nauru, Palau and Tuvalu,2 and is lowest for Fiji,3 which is a regional hub. In the Pacific, vulnerability to economic and natural shocks, as measured by the Economic Vulnerability Index (EVI),4 is highest for Nauru (67.93) and Palau (69.65), but relatively lower for Papua New Guinea (31.67).

National income levels can also hide significant heterogeneity across SIDS. Some of the smallest SIDS in the Pacific with relatively higher national per capita income face significant challenges in finding a viable path towards sustainable growth. For example, Nauru, recorded sustained growth until 2011 when the main driver of growth – phosphate deposit extraction – became unavailable. Nauru is a microstate possessing no other natural resources, a population of only about 10 000, and a scarcely developed tourism and private sector. Although it has the highest GNI per capita among Pacific SIDS, its unemployment rate is estimated at 90%; and the Nauru government employs about 95% of the workforce.

Several middle-income SIDS – including Grenada, Jamaica, Mauritius, and the Seychelles – seem to enjoy better development prospects as they are better connected to international markets and shipping lanes and present a higher ease of doing business. However, they are often very reliant on top trading partners, which exposes them to “trade fragility”; they tend to have high levels of debt and strong vulnerability as measured by the EVI.

In addition, SIDS include countries that are in some form of free association compact with larger economies (e.g. Australia, New Zealand, United Kingdom or United States). Lacking in capacity and autonomy, more than other SIDS they depend on these larger economies for trade, tourism, and concessional finance, including for the financing of public services.

SIDS also share unique common challenges

As stated in Foreword, the special case of SIDS is internationally recognised, and it has received international attention. By analysing new data and performance against selected vulnerability factors, this report provides new evidence that, in spite of differences, SIDS face common economic and development challenges stemming from their small populations and small landmasses, their spatial dispersion and remoteness from major markets, and their high exposure to external shocks, including severe climate-related events and natural disasters.

While differences among SIDS point to the need for tailored development approaches across the group, they also point to scope for mutual learning and exchange of experiences among SIDS located in different geographical regions as well as among providers of concessional finance operating in different regions. Regional bodies, such as the Pacific Islands Forum Secretariat and the Caribbean Community (CARICOM) have so far been effective in bringing countries together to exchange views, build expertise, and develop policy options. More of this could be encouraged in the AIMS region as well as at the inter-regional level.

The challenge of making ODA work better for SIDS will be to strike the right balance between elements of heterogeneity – tailoring solutions to the specific needs of each country – and commonality – leveraging the political strength of the group and mutually beneficial experiences and good practices.

1.2. Economic and development performance of small island developing states

1.2.1. Economic growth is slow and volatile, owing to strong sensitivity to fluctuations in the global economy and natural disasters

Most SIDS5 compare relatively well to other developing countries in terms of gross domestic product (GDP): three fifths of SIDS qualify as upper middle-income countries (see Figure 1.1). However, economic growth in most SIDS is fairly sluggish. It is also highly vulnerable to shocks in the global economy and to the impacts of climate change and natural disasters, owing to narrow production bases and undiversified economies, and strong reliance on the global economy for financial services, tourism, remittances and concessional finance.

Given the small size of SIDS economies, a single natural disaster can translate into losses of up to 200% of GDP (World Bank, 2005), wiping out entire economic sectors and eroding the development gains accumulated over decades (Box 1.1). Globally, SIDS make up two thirds of the countries that suffer the highest relative losses – between 1% and 9% of their GDP each year – from natural disasters (OECD-World Bank, 2016).

Box 1.1. Impacts of disasters and climate change will significantly increase the cost of sustainable development in small island developing states

SIDS are located in some of the world’s most natural disaster-prone regions. Tropical storms and cyclones perennially afflict SIDS, whose dispersed and remote geographies, and small economies, make them poorly equipped to respond to these extreme events. Furthermore – as in other developing countries – rapid urbanisation, population growth and climate change are increasing the exposure of SIDS to disaster risk (Mimura et al., 2007). Pollution and ecosystem degradation, and the extraction of coastal aggregates for construction, are also compromising natural buffers, leaving the population and assets increasingly exposed. According to Mahul et al. (2014), the impacts of climate change will increase the severity and frequency of extreme weather events by 40-80%, and are posing additional challenges to the economic growth and sustainable development of SIDS. Many SIDS are low-lying or atoll nations, with key infrastructure and populations close to sea level, and hence acutely vulnerable to sea-level rises and storm surge events.

More than 335 major natural disasters have occurred in SIDS since 2000, resulting in an estimated USD 22.7 billion in direct damages. The occurrence of major natural disasters in SIDS has declined slightly since 2000; and yet the associated impacts of these events have increased (OECD-World Bank, 2016).

While absolute losses from natural disasters and climate-related events are dwarfed by those in larger economies, the relative impacts in SIDS are often far greater, causing widespread disruption to key economic sectors and service delivery resulting in significant costs as a share of national output (Figure 1.2). For example, tropical storm Erika caused widespread damage in Dominica in 2015. Landslides and flooding significantly damaged infrastructure, including highways financed with loans that had yet to be repaid. The Dominican government thus had to refinance to rebuild while also paying off debts for now defunct roads. The total cost was estimated at USD 483 million, roughly equivalent to 90% of GDP in 2015 (Government of the Commonwealth of Dominica, 2015).

The large exposure of SIDS to the impacts of climate change and natural disasters, combined with their limited ability to respond, means that SIDS are among the most vulnerable countries in the world. It also means that the cost of sustainable development in SIDS will be significantly higher than in other contexts. Short-term disaster response from humanitarian donors must be linked with long-term financial support for resilience building and, in turn, must be mainstreamed into development planning and financing. Therefore, while speed and low costs are important factors in carrying out reconstruction efforts in the wake of a disaster, taking into consideration the risks from climate change could require different standards and/or changes in planning processes to deliver cost effective, long-term development outcomes. Integrating the concept of resilience is critical to avoid locking out future development and creating new vulnerabilities.

Among developing countries, SIDS were hit the hardest by the 2008-09 global financial crisis (Figure 1.3), with GDP growth rates slumping to 0.9% in 2009, compared to over 3% for other developing countries as a whole.6 The impact of the crisis was most acutely felt in upper middle-income SIDS and Caribbean SIDS, two largely overlapping groups. This partly reflects their greater integration in the global economy – including through financial services, tourism, remittances and exports – compared to other SIDS. After SIDS’ GDP dropped in 2009, economic growth picked up again across all regions and income groups. However, growth rates remain lower than in the pre-crisis period7 for all SIDS, except Pacific SIDS and least developed SIDS, whose recovery has been faster, and whose growth rates exceed their pre-crisis levels.

Relying on income or geographic distinctions, however, can be at times misleading. Stronger economic performance of relatively larger SIDS economies, such as Papua New Guinea and Timor-Leste, leads to a rosier picture of performance in the Pacific after the crisis. The region’s 3.4% growth in 2009 was mainly driven by 6.1% growth in Papua New Guinea and 13.0% growth in Timor-Leste; while six much smaller economies recorded negative growth, and the other nine Pacific SIDS saw lower growth rates. In general, trends in economic growth would also need to be assessed in per capita terms, as robust GDP growth in a few SIDS has not kept up with rapidly expanding populations, as it is the case of Papua New Guinea.

1.2.2. Human development lags behind and SIDS score as the most vulnerable among developing countries

While referring to GDP as a widely recognised and practical means of taking the pulse of a country’s economy, its limitations as a measure of welfare and quality of life are well known.8 When considering a country’s achievements along a broader set of development dimensions (including health and standards of living) through the UN Human Development Index (HDI) (UNDP, n.d.), two fifths of SIDS display a low or medium level of development (Table 1.1). SIDS with low or medium HDI mainly comprise SIDS that are classified as least developed countries, but also some lower middle-income countries across different regions, such as Cabo Verde, Guyana, Federated States of Micronesia (“Micronesia”) and Papua New Guinea.

Table 1.1. Over two fifths of small island developing states display a low or medium level of human development
HDI Rank	Country	HDI score	Human development group
60	Palau	0.79	High
62	Antigua and Barbuda	0.79	High
63	Seychelles	0.78	High
64	Mauritius	0.78	High
68	Cuba	0.77	High
79	Grenada	0.75	High
91	Fiji	0.74	High
92	Saint Lucia	0.74	High
94	Jamaica	0.73	High
96	Dominica	0.73	High
97	Suriname	0.72	High
99	Dominican Republic	0.72	High
99	Grenadines	0.72	High
101	Tonga	0.72	High
103	Belize	0.71	High
104	Samoa	0.70	High
105	Maldives	0.70	High
122	Cabo Verde	0.65	Medium
127	Micronesia	0.64	Medium
127	Guyana	0.64	Medium
133	Timor-Leste	0.61	Medium
134	Vanuatu	0.60	Medium
137	Kiribati	0.59	Medium
142	Sao Tome and Principe	0.57	Medium
154	Papua New Guinea	0.52	Low
156	Solomon Islands	0.51	Low
160	Comoros	0.50	Low
163	Haiti	0.49	Low
178	Guinea-Bissau	0.42	Low
Source: Adapted from UNDP Human Development Index Data for 2015, http://hdr.undp.org/en/content/human-development-index-hdi.

As a group, SIDS also score the highest among developing countries in terms of the EVI, a measure of the structural vulnerability of developing countries that takes into accounts the impacts of economic and natural shocks9, as well as the determinants of exposure to shocks (including small population size and remoteness from world markets10). Vulnerability measured in terms of EVI is highest for least developed SIDS. When considering a measure of vulnerability, the largest gap between SIDS and other developing countries emerges for upper middle income countries: upper middle-income SIDS exhibit a 73% higher vulnerability than other upper middle-income countries (Figure 1.4).

1.3. Key drivers of vulnerability and structural characteristics

1.3.1. Small, dispersed populations hamper the creation of sizable domestic markets and lead to capacity constraints

Small, dispersed populations are a key driver of vulnerability in SIDS: they limit the scope for developing domestic markets and prevent SIDS from exploiting economies of scale in production. Hence, production costs tend to be higher in SIDS – particularly when populations are scattered across multiple distant islands, and transport costs significantly increase overall production costs. As a result, SIDS tend to focus their economic activities on a small number of sectors (most often tourism, services, agriculture and fishing and natural resource extraction) that capitalise on their natural and human resources. This concentration of activity, in turn, increases the impact of shocks on key sectors.

Small and scattered populations also entail high per capita costs to deliver essential public services, challenging governments’ ability to provide education, health, security and other services. These costs have a significant impact on public finances, leading to larger public sector expenditures compared to other developing countries with a similar income level (see, for example, Horscroft, 2014) and to a larger share of public expenditure that is recurrent expenditure rather than capital investment (See also Chapter 2). Figure 1.5 shows that SIDS’ average for both health and education public expenditure (as a share of GDP) is higher than for comparable income countries, with some countries spending up to four times the comparator average in health (Micronesia), and almost double in education (Timor-Leste).

Finally, human and institutional capital is hard to build and maintain in small states, and small populations often translate into relatively low numbers of qualified staff working in key capacities. Some SIDS face a shortage of skilled labour and rely heavily on expatriate labour, despite a high unemployment rate. In some SIDS, the skilled labour shortage partly stems from limited access to good quality secondary, tertiary and vocational education; in other SIDS, it mainly results from a lack of adequate job opportunities and the ensuing brain drain. For example, Grenada has an annual emigration rate of 2% and ranks among the top five developing nations in terms of the share of college-educated citizens leaving the country. Moreover, while some SIDS are experiencing considerable population growth (20% in Antigua and Barbuda, and 40% in Timor-Leste over 2000-15), some SIDS face large emigration flows, a phenomenon which might increase as a consequence of climate change. Diasporas can be significant, sometimes outnumbering resident populations. Grenada, for example, has a population of about 100 000, with an estimated 230 000 Grenadians living abroad.

According to de La Croix, Docquier and Schiff (2014), on average, emigration rates of SIDS are far above those of other developing countries and high-income countries. This is true for low-skilled workers (15.6 %, i.e. about 13 percentage points above the average level of other developing countries) and for college graduates (50.8 %, i.e. about 37 percentage points above the average level of other developing countries). Countries exhibiting the largest brain drain rates are Guyana (89.2 %), Jamaica (84.7 %), Grenada (84.3 %), Saint Vincent and the Grenadines (81.9 %), Haiti (79.0 %), Tonga (75.6 %) and Samoa (73.4 %). Migration flows can, however, also be a driver for development, which seems to be the case, for example, with labour arrangements with neighbouring countries, revolving migration, or remittances (See Chapter 3).

Overall, most SIDS (18 out of 35) are microstates numbering under 200 000 inhabitants; a further 11 SIDS have populations under 1.5 million (Niue is the smallest, with a population of 1 612); and six have populations between 1.5 and 12 million, with Cuba being the most populous. On aggregate, the total population of SIDS was estimated at 66 million in 2014, roughly 1% of the total global population. The extensive spatial dispersion of their island groupings is particularly pronounced for SIDS in the Pacific. Kiribati, for example, comprises 33 coral atolls scattered over 3.5 million square kilometres (km2) of ocean: an area larger than India. The Solomon Islands is geographically splintered, with 1 000 small islands and a population of 500 000 dispersed across 90 inhabited islands. In the Indian Ocean, the Maldives has a population of 341 200, scattered over 188 inhabited islands spanning an archipelago more than 800 km long and 130 km wide.

1.3.2. Long distances challenge access and connectivity to international markets

Coupled with small size, remoteness leads to high production and trading costs, limiting investment, competitiveness and the scope for integrating global value chains. Remoteness is an issue for most SIDS, especially those in the Pacific, which are among the most remote states on earth. Nauru, Marshall Islands and Kiribati are at least 3 000 km from the nearest continent, Australia. Mauritius and Antigua and Barbuda, are each over 1 000 km from the nearest continent. The UN Liner Shipping Connectivity Index, which measures connectedness to global shipping networks, indicates that SIDS as a group are less than one third as well connected as other developing countries (UNCTAD, 2010; UNCTAD, 2014). As highlighted in Figure 1.6, Mauritius, the Dominican Republic and Jamaica score comparatively well on the Index, but the other SIDS are very disconnected. Moreover, since the measure began in 2004, the aggregate score for the other developing countries has grown by 75% (from 14.3 to 25.0), whereas the improvement for SIDS has been more modest (40%), rising from 5.1 to 7.1.

Besides their remoteness from larger economies, some SIDS are also distant from each other, limiting the potential for intraregional SIDS trade integration. For example, Fiji is closer to Australia than to Papua New Guinea, and Palau is closer to Asia than to most other SIDS in the Pacific (IMF, 2016).

1.3.3. SIDS economies rely on narrow, undiversified production bases

Given high production costs, limited competitiveness and difficulties in integrating in global value chains, the economy of most SIDS relies on just a few products and sectors. Product concentration11 is widespread and particularly high for several of the least developed SIDS, especially Guinea-Bissau, Timor-Leste, Kiribati, Vanuatu and Tuvalu (Figure 1.7). The economy of least developed SIDS is essentially based on agriculture (which represented 23% of GDP in 2015, compared to 7% in upper middle-income SIDS) and, in some cases, fisheries. Among least developed SIDS, Timor-Leste is an exception, due to its strong reliance on oil and natural gas, which account for about 80% of GDP and 90% of government revenues (IMF, 2016). While a handful of other SIDS rely strongly on natural resources, the economy of most SIDS largely relies on services, particularly tourism and financial services. Economic diversification usually is a path to resilience to external shocks.

1.3.4. Natural resources have been a driver of economic growth in a handful of SIDS

Besides Timor-Leste, other SIDS – such as Papua New Guinea, Guyana, Suriname, Solomon Islands and Guinea-Bissau – possess natural resources, including oil, gas, gold, nickel and bauxite. In 2000-15, natural-resource rents accounted for 10-40% of GDP in these SIDS, and over 140% in Timor-Leste. In the remaining SIDS, they represented less than 5% of GDP.

While natural resource-rich SIDS have benefitted from high commodity prices in recent years, the combined effect of falling commodity prices, China’s economic slowdown and the rising cost of external debt may challenge the pace of their future economic growth. Other SIDS, which are large net importers of fuels and food, are instead likely to benefit from lower commodity prices (see end of Section 1.2). Overall, these SIDS grew slightly faster than other SIDS over 2000-15, recording an average annual growth rate of 4.3%, compared to 3.9% in other SIDS. Similarly to other natural resource-rich developing countries, however, the resource-rich SIDS are prone to suffering economically because of “Dutch disease”: the increase in revenues from natural resources strengthens a country’s currency, rendering its other exports more expensive, with a negative impact on the competitiveness of its manufacturing and agriculture sectors.

Several SIDS, especially in the Pacific, have well-established sovereign funds, which were created to ensure a stable stream of future revenue, to insure against fluctuations in domestic resource mobilisation, promote a wise use of public resources and earmark revenue for pre-approved long-term development expenditure. Kiribati and Timor-Leste successfully established sovereign funds to ensure a stable stream of natural resource revenues and reduce currency appreciation. Although phosphate deposits in Kiribati were depleted in the late 1970s, the Revenue Equalisation Reserve Fund, established in 1956 and financed through phosphate earnings, still represents over 200% of the country’s GDP and significantly contributes to government spending. Timor-Leste’s sovereign fund, established in 2005 to store and invest Timor-Leste’s petroleum revenues, represents over 500% of the country’s GDP (Drew, 2015). The global financial crisis had a strong impact on these SIDS, as it significantly reduced the value of their sovereign funds. Nevertheless, these funds still represent a significant source of wealth.

1.3.5. The economy of several SIDS strongly relies on tourism

Owing to their enchanting natural landscapes, beaches and cultural heritage, several SIDS rely on tourism as a significant source of income and foreign exchange. The tourism sector accounts for less than 5% of GDP in other developing countries, but represents over 20% of GDP for almost two thirds of SIDS, and between 58% and 65% for Palau and the Maldives (IMF, 2016). According to the World Travel and Tourism Council (WTTC, 2016), direct and indirect contributions to the Maldives economy amount to 78% of GDP and 62% of total employment. The tourism sector has been a main driver for graduation from least developed country status for Cabo Verde and Samoa, and represents a main source of revenue, especially for some upper middle-income SIDS (Figure 1.8).

Large financial “leakages” from the tourism sector, however, often diminish its positive impact on the domestic economies and livelihoods of SIDS. Spill over effects on the domestic economy can be limited by large food imports to meet foreign tourists’ tastes, and the considerable imports of consumer goods and construction materials used in the tourism sector. In addition, the repatriation of profits earned by foreign investors and the land rents retained offshore can be considerable. For example, the expansion of the tourism sector in the Cook Islands led to a rapid growth in GDP figures; this, however, does not appear to match the population’s stagnant living standards, likely because of the growing share of revenues flowing out of the economy and the falling share accruing locally (Bertram, 2016).

The risks stemming from the over reliance of SIDS economies on tourism became apparent during the 2008 global financial crisis, pointing again to the need to develop more diversified production bases. The tourism sector was, in fact, a key indirect channel of transmission for the 2008-09 global financial crisis, as visitor numbers fell considerably in many SIDS, with significant impacts on economic growth.

Large opportunities lie ahead for SIDS to both develop more sustainable tourism sectors, and integrate local value chains to foster better employment opportunities and inclusive development domestically. This would mean seizing the opportunities provided by the tourism sector to promote the sustainable use of oceans, to foster biodiversity conservation, and invest in green technologies to reduce energy and water consumption. It would also mean establishing policies to reduce the financial leakages currently experienced by several SIDS, mainly owing to the repatriation of profits earned by foreign investors, and the imports of consumer goods and construction materials used in the tourism sector.

The Seychelles provides a positive example in this regard. This atoll nation has introduced high standards in ecological sustainability, embedding them in its efforts to enhance its position in the global tourism market. Currently, 43% of the land – and much of the surrounding ocean – is protected for conservation. The Seychelles has also introduced policies and reforms aiming to enhance this sector’s benefits to the domestic economy. For example, the University of the Seychelles is now providing tailored qualifications to raise the domestic capacity to meet the sector’s demand for skilled labour. A number of initiatives have also been launched to integrate the tourism industry with other domestic sectors. For example, the Small Establishment Enhancement Programme is a local marketing initiative promoting smaller local accommodation under the brand “Secret Seychelles”. Similarly, the use of local materials whenever possible, and advances in renewable energy, can reduce the leakage effect and contribute to more sustainable tourism.

1.3.6. SIDS’ economies are very open to trade and reliance on a handful of trading partners exposes them to “trade fragilities”

SIDS are more open to trade than other developing countries, as signalled by a relatively higher share of trade in GDP (100.5% vs. 78.2% in 2000-15), in part due the small size of their domestic markets. Wide variations, however, are seen across SIDS. The highest level of trade openness is evident in the AIMS region (Figure 1.9), mainly due to the Maldives and the Seychelles, as well as in relatively higher income, tourism-dependent SIDS.

The large GDP share stemming from the value of trade, however, exposes SIDS to market fluctuations more than other developing countries. This fragility is exacerbated by their narrower selection of trade partners. On average, 60% of SIDS exports go to the top three trading partners and 87% to the top ten trading partners, compared to 52% and 77% in other developing countries (Figure 1.10). Key trading partners often coincide with the countries from which SIDS receive the largest flows of tourism, remittances and concessional finance, making development in the economies of those countries particularly impactful for SIDS.

1.3.7. SIDS strongly depend on imported fossil fuels, but are demonstrating an ambition to transition to renewable sources of energy

The vulnerability of SIDS also stems from their strong reliance on strategic imports, again leaving them exposed to terms-of-trade shocks. Food and fuel imports are high due to high demand for these in key economic sectors, such as fisheries and tourism. Imported fossil fuels are used for electricity production and to transport commodities across geographically dispersed internal markets.

The reliance on imported fuel for electricity generation leads to particularly high energy production costs in SIDS, affecting consumers both directly and indirectly through higher commodity production costs. For example, electricity rates for residential customers in Micronesia are nearly four times as high (USD 0.48 per kilowatt hour) as the average residential rate in the United States (USD 0.13 per kilowatt hour) (United States Department of Energy, 2015). Retail electricity prices in the Solomon Islands are even higher: at an average of USD 0.85/kilowatt hour they are the highest in the Pacific and among the highest in the world.

Most SIDS allocate more than 30% of their foreign exchange reserves each year to cover the cost of fossil fuel imports.12 At the same time, high debt burdens in some SIDS hamper investment in innovative sustainable energy technologies, perpetuating their dependence on imported fossil fuels and its negative effect on fiscal space.

SIDS continue to demonstrate ambition in the area of renewable energy: transitioning to low-carbon economies will heavily reduce fossil fuel import costs and free up fiscal space. In the past, this strong ambition strengthened the position of SIDS in the climate change negotiations. The Intended Nationally Determined Contributions (INDCs) of many SIDS contain some of the most ambitious renewable energy targets, with countries (including Samoa and the Cook Islands13) targeting 100% renewable energy for electricity generation by 2025 (UNFCCC, 2015). Guyana plans to increase its share of renewable energy by 100% by 2025, in keeping with its ambition to achieve a green economy and low-carbon development strategy. These targets come with caveats and conditions, provided they receive adequate technical and financial support to remove existing barriers.

Box 1.2. Small states, large ocean states: The potential of the blue economy

Smallness and other geophysical characteristics, such as exposure to extreme weather events and natural disasters, have challenged economic growth and development in SIDS. But while SIDS collectively occupy less than 1% of the global land area, they make up a vast share (14%) of the world’s coastline and possess some of the largest economic exclusion zones (EEZs) in the world: their combined EEZ area covers nearly 23.2 million km². In Tuvalu, for example, the EEZ is approximately 28 000 times the size of the land mass. The largest EEZs are found in Kiribati (3.44 million km²) Micronesia (2.99 million km²), Marshall Islands (1.99 million km²) and Seychelles (1.33 million km²; the average size of a SIDS EEZ is nearly 724 km².

Possessing such vast ocean resources, many SIDS are increasingly looking to the oceans as the next frontier for economic development, and are determined to embark on a pathway toward sustainable “blue” growth. The value of the global ocean economy is estimated at USD 1.5 trillion per year (OECD, 2016). OECD projections suggest that the ocean economy could reach over USD 3 trillion between 2010 and 2030, more than doubling its contribution to global value added. The ocean economy is expected to account for around 40 million full-time equivalent jobs; the most rapid job growth should occur in offshore wind energy, marine aquaculture, fish processing and port activities.

Ocean-based industries (such as tourism and fisheries) are already key sources of income in SIDSs. Innovative investments to make sustainable use of existing sectors and create new sectors (integrating land-based, coastal and ocean-based activities) could boost sustainable, inclusive growth and tackle some of the critical challenges facing these economies, such as high unemployment, food insecurity and poverty. New economic sectors include improved aquaculture, ocean renewable energy and ocean biotechnology (Table 1.2.). The potential of ocean renewables is vast. Ever-improving technologies may open up new possibilities, although limitations in the infrastructure required to connect and distribute power, as well as limited finance, may hold back progress. While the potential of biotechnological resources is largely unknown, marine organisms could provide valuable resources to the chemical and pharmaceutical sectors (Day et al., 2016).

Table 1.2. Established and emerging sectors of the ocean economy
Established	Emerging
Capture fisheries and seafood processing	Marine aquaculture
Shipping and ports	Deep-water and ultra-deep water oil and gas
Shipbuilding and repair	offshore wind energy
Offshore oil and gas (shallow water)	Ocean renewable energy
Marine manufacturing and construction	Marine and seabed mining
Maritime and coastal tourism	Maritime safety and surveillance
Marine business services	Marine biotechnology
Marine research and development and education	High-tech marine products and services
Dredging

Innovative approaches and a more sustainable use of resources also have great potential for boosting the economic and social benefits of existing sectors. For example, global demand for fish products is greatly benefiting the fishing sector in SIDS: exports of fish and fish products contribute between 30-80% of GDP in Pacific SIDS and there is scope to expand this (Ababouch, 2015). However, the sustainable management of fisheries will require designing a favourable policy and regulatory environment, and investing adequate resources. Fishery revenues could also increase through measures to curb illicit, unregulated and unreported fishing, as well as through fairer trade. For example, fishing agreements that provide access to an EEZ usually allow for a low appropriation of fishery export revenues by national operators and do not translate into knowledge transfer by foreign fishing companies to national stakeholders (World Bank Group and United Nations Department of Economic and Social Affairs, 2017).

References

Ababouch, L. (2015), Fisheries and Aquaculture in the Context of Blue Economy, background paper from “Feeding Africa, High Level Conference on Agricultural Transformation” UN Economic Commission for Africa, Dakar, Senegal, 21-23 October 2015, www.afdb.org/fileadmin/uploads/afdb/Documents/Events/DakAgri2015/Fisheries_and_Aquaculture_in_the_Context_of_Blue_Economy.pdf.

Bertram, G. (2016), Implications of the Cook Islands’ Graduation from Development Assistance Committee (DAC) Eligibility, Ministry of Finance and Economic Management, Government of the Cook Islands, www.mfem.gov.ck/images/documents/DCD_Docs/Development-Resources/Implications_of_the_CKI_Graduation_from_DAC_Eligibility.pdf.

Day, J., A. Hughes, L. Greenhill and M.S. Stanley (2016), “Blue Biotechnology” Commonwealth Blue Economy Report Series, No. 5, Commonwealth Secretariat, London, http://thecommonwealth.org/sites/default/files/inline/Blue%2BBiotechnology_UPDF.pdf.

De la Croix, D., F. Docquier, M. Schiff (2014), “Brain Drain and Economic Performance in Small Island Developing States”, in Artal-Tur, A. & G. Peri & F. Requena-Silvente (eds), The Socio-Economic Impact of Migration flows - Effects on Trade, Remittances, Output, and the Labour Market, Springer International Publishing, www.springerprofessional.de/en/brain-drain- and-economic-performance-in-small-island-developing-/2078340.

Drew, A (2015), The Role of Sovereign Funds in Pacific Island Nations, New Zealand Institute for Pacific Research, University of Auckland, Auckland, https://nzipr.blogs.auckland.ac.nz/files/2017/07/theroleofsovereignfundsinpacificislandsnations-1etr6ol.pdf.

Ferdi (n.d.), Economic Vulnerability Index (database), Fondation pour les études et recherches sur le développement international, Clermont Ferrand, France, http://byind.ferdi.fr/en/indicator/evi/results/0bad6ab7965ccca0e81a70ddbe010754ff774aa4.

Government of the Commonwealth of Dominica (2015), Rapid Damage and Impact Assessment Tropical Storm Erika – August 27, 2015, A report by the Government of the Commonwealth of Dominica, Roseau, Dominica, http://documents.worldbank.org/curated/en/142861467995411564/pdf/104251-WP-PUBLIC-Rapid-Damage-and-Needs-Assessment-Final-Report-Oct5.pdf.

Horscroft, V. (2014), “Public Sectors in the Islands: Are They ‘Too Big’ and Do They ‘Crowd Out’ the Private Sector?” Policy Research Working Paper Series, No. 7102, World Bank, Washington, D.C., http://documents.worldbank.org/curated/en/986481468098052675/pdf/WPS7102.pdf.

IMF (2016), Resilience and Growth in the Small States of the Pacific, (eds.), H. Khor, R. Kronenberg, and P. Tumbarello, published Spring 2016, International Monetary Fund Publications, Washington, D.C., www.elibrary.imf.org/staticfiles/misc/excerpts/small_states_pacific_excerpt.pdf.

Kuznets (1941), National income and its composition 1919–1938, National Bureau of Economic Research, New York.

Mahul, O., B. Signer, L. Boudreau, H. Yi, S. Atamuratova, D. Clarke, E. White, (2014), Financial Protection against Natural Disasters: From products to comprehensive strategies - an operational framework for disaster risk financing and insurance, World Bank Group, Washington, D.C., http://documents.worldbank.org/curated/en/523011468129274796/Financial-protection-against-natural-disasters-from-products-to-comprehensive-strategies-an-operational-framework-for-disaster-risk-financing-and-insurance

Mimura, N., L. Nurse, R.F. McLean, J. Agard, L. Briguglio, P. Lefale, R. Payet and G. Sem, (2007), “Small islands. Climate Change 2007: Impacts, Adaptation and Vulnerability”. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, pp 687-716, M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds., Cambridge University Press, Cambridge, www.ipcc.ch/pdf/assessment-report/ar4/wg2/ar4-wg2-chapter16.pdf.

OECD (2016), The Ocean Economy in 2030, OECD Publishing, Paris, https://doi.org/10.1787/9789264251724-en.

OECD DAC (2014), DAC List of ODA Recipients, OECD, Paris, www.oecd.org/dac/financing-sustainable-development/development-finance-standards/daclist.htm.

OECD-World Bank (2016), Climate and Disaster Resilience Financing in Small Island Developing States, OECD Publishing, Paris, https://doi.org/10.1787/9789264266919-en.

The Economist (2016), “The Trouble with GDP”, The Economist, April 2016, London, www.economist.com/news/briefing/21697845-gross-domestic-product-gdp-increasingly-poor-measure-prosperity-it-not-even.

UNCTAD (2014), Small Island Developing States: Challenges in transport and trade logistics, United Nations Convention on Trade and Development, Geneva, http://unctad.org/meetings/en/SessionalDocuments/cimem7d8_en.pdf.

UNCTAD (2010), Review of Maritime Transport, United Nations Convention on Trade and Development, Geneva, http://unctad.org/en/docs/rmt2010_en.pdf.

UNCTAD (n.d.), Shipping Liner Connectivity Index (database), United Nations Convention on Trade and Development, Geneva, http://unctadstat.unctad.org/wds/TableViewer/tableView.aspx?ReportId=92.

UNDP (n.d.), Human Development Index (database), United Nations Development Programme, New York, http://hdr.undp.org/en/content/human-development-index-hdi.

UNFCCC (2015), Samoa’s Intended Nationally Determined Contribution, September 2015, United Nations Framework Convention on Climate Change, New York, http://www4.unfccc.int/ndcregistry/PublishedDocuments/Samoa%20First/Samoa%20INDC_Submission%20to%20UNFCCC.pdf.

United States Department of Energy (2015), Energy Transition Initiative: Island Energy Snapshot - Federated States of Micronesia, NREL (National Renewable Energy Laboratory), National Renewable Energy Initiative, U.S. Department of Energy, Washington, D.C., www.nrel.gov/docs/fy15osti/64294.pdf.

World Bank (2005), Grenada: A Nation Rebuilding An assessment of reconstruction and economic recovery one year after Hurricane Ivan, World Bank Group, Washington D.C., http://documents.worldbank.org/curated/en/538951468030331426/pdf/355660GD0rebuilding0hurricane0ivan.pdf.

World Bank (n.d.) World Development Indicators (database), World Bank Group, Washington D.C., https://data.worldbank.org/data-catalog/world-development-indicators.

World Bank and United Nations Department of Economic and Social Affairs (2017), The Potential of the Blue Economy: Increasing long-term benefits of the sustainable use of marine resources for small island developing states and coastal least developed countries, World Bank, Washington D.C., http://www.climateactionprogramme.org/images/uploads/documents/World_Bank.pdf.

WTO (2016), UNWTO Statistics (database), United Nations World Tourism Organisation, Madrid, http://statistics.unwto.org/.

WTTC (2016), Economic Impact Reports, World Travel and Tourism Council, London, www.wttc.org/research/economic-research/economic-impact-analysis/.

Annex 1.A. Data sources and coverage

This report focuses on the 35 SIDS currently eligible for ODA (as per the OECD DAC List of ODA-Eligible Countries (OECD, 2014). When referring to “other developing countries”, the report considers all remaining ODA-eligible countries that are not the 35 SIDS.

In this chapter, a number of statistical sources are used, the coverage of which varies across SIDS. In general, data quality and availability remains a challenge in SIDS, largely owing to limited national capacity. For several SIDS the lack of data is linked to the fact that they are not members of the Bretton Woods institutions. This is the case for three SIDS: Cook Islands, Montserrat and Niue. Nauru joined the International Monetary Fund and World Bank in 2016. Annex Table 1.A.1 details the data sources and coverage of the statistical data used in this chapter.

Annex Table 1.A.1. Data sources and coverage
Variable	Source	Coverage (%)	Missing SIDS	Notes
GDP per capita	World Bank, World Development Indicators	100
Trade Openness (the sum of exports and imports of goods and services measured as a share of gross domestic product)	World Bank, World Development Indicators	84	Micronesia, Marshall Islands, Sao Tome and Principe, Tuvalu, Nauru
GNI per capita	World Bank, World Development Indicators	88	Cuba, Maldives, Nauru, Sao Tome and Principe
GNI current	World Bank, World Development Indicators	97	Nauru
GDP growth (%)	World Bank national accounts data, and OECD National Accounts data files.	97	Nauru
External debt stock % of GNI	World Bank, World Development Indicators	63	Antigua and Barbuda, Cuba, Kiribati, Marshall Islands, Micronesia, Nauru, Palau, Seychelles, Suriname, Tuvalu, Timor-Leste
Total debt service % of GNI	World Bank, World Development Indicators	69	Antigua and Barbuda, Cuba, Kiribati, Marshall Islands, Nauru, Palau, Seychelles, Suriname, Timor-Leste , Tuvalu
Natural resource rent	World Bank, World Development Indicators	63	Antigua and Barbuda, Cabo Verde, Comoros, Grenada, Guinea-Bissau, Marshall Islands, Micronesia, Nauru, Palau, Tuvalu, Sao Tome and Principe, Seychelles
Exports % GDP	World Bank, World Development Indicators	81	Marshall Islands, Micronesia, Nauru, Papua New Guinea, Sao Tome and Principe, Tuvalu
Fuel imports	World Bank, World Development Indicators	47	Antigua and Barbuda, Cuba, Dominica, Grenada, Guinea-Bissau, Haiti, Kiribati, Marshall Islands, Micronesia, Nauru, Palau, Papua New Guinea, Solomon Islands, Saint Lucia, Timor-Leste, Tuvalu, Vanuatu
Public expenditure in health and education as a share of GDP, (2014)	World Bank, World Development Indicators	100		Data for Cabo Verde, Fiji and Guinea-Bissau refer to 2013.
Brain drain	La Croix, Docquier and Schiff, 2014
Liner shipping index	UNCTAD	91	(Series starts in 2004). Nauru, Timor-Leste, Tuvalu
Ease of doing business	World Bank, World Development Indicators	91	Cuba, Nauru, Tuvalu
Debt composition	World Bank Debt Statistics	66	Antigua and Barbuda, Cuba, Kiribati, Marshall Islands, Micronesia, Nauru, Palau, Seychelles, Suriname, Timor-Leste, Tuvalu
HDI (2015)	UNDP	83	Marshall Islands, Nauru, Tuvalu, Cook Islands, Montserrat and Niue
EVI (2013)	FERDI	100
Product Concentration (2014)	UNCTAD	100
Inbound tourism/GDP	UNWTO	75	Cuba, Kiribati, Marshall Islands, Micronesia, Palau, Nauru, Sao Tome and Principe, Tuvalu
Top 3 Trading Partners (2015)	UNCTAD	100
Food imports	World Bank, World Development Indicators WDI	88	Haiti, Marshall Islands, Micronesia, Nauru
Gross Debt/GDP (2014)	World Economic Outlook	100

Notes

← 1. In 2017, Samoa moved from lower middle income status to upper middle-income country, according to the updated World Bank income thresholds. As this report mostly covers in its analysis statistical data up to the year 2015 (when Samoa was still a lower middle income country), Samoa is consistently treated as a lower middle income country throughout this report.

← 2. Nauru, Palau and Tuvalu have a liner shipping index of 1.32.

← 3. Fiji has a liner shipping index of 8.56.

← 4. The EVI is the simple arithmetic average of 2 sub-indexes: the exposure sub-index, which is a weighted average of five component indexes: population size (25%), remoteness from world markets (25%), exports concentration (12.5%), share of agriculture, forestry and fishery in GDP (12.5%) and the share of population living in low elevated coastal zone (25%), and the shocks sub-index, which is a weighted average of 3 component indexes: the victims of natural disasters (25%), the instability in the agricultural production (25%), and the instability in exports of goods and services. The EVI is calculated by Ferdi (Fondation pour les Études et recherches sur le Développement International), a French foundation for international development studies (www.ferdi.fr/en).

← 5. As highlighted in Chapter 1 of this report, the SIDS considered here are the 35 ODA-eligible SIDS.

← 6. In this report, the term “other developing countries” refers to all other ODA-eligible countries that are not identified as SIDS.

← 7. The pre-crisis period under consideration is 2000-08, while the post-crisis period is 2010-15.

← 8. The criticisms towards GDP concerns even its ability to capture economic development. Simon Kuznets, who developed GDP back in the late 1930s, warned it was not a suitable measure of a country’s economic development. He highlighted that GDP is not a welfare measure, it is not a measure of how well we are all doing. It counts the things that we’re buying and selling, but it’s quite possible for GDP to go in the opposite direction of welfare. See National income and its composition 1919-1938 (Kuznets,1941), The Trouble with GDP (The Economist, 2016).

← 9. Victims of natural disasters; instability of agricultural production; and instability of exports of goods and services.

← 10. The full list of indicators regarding the determinants of exposure to shocks is: small population size; remoteness from world markets; export concentration; share of agriculture, forestry and fisheries in GDP; and share of population living in low-elevation costal zones.

← 11. This is based on the Concentration Index published by UNCTAD annually. The index is a Herfindahl-Hirschmann Index (Product HHI) measuring the degree of product concentration. A HHI value closer to 1 indicates that a country's exports or imports are highly concentrated in a few products. On the contrary, values closer to 0 reflect exports or imports are more homogeneously distributed among a series of products.

← 12. http://unctad.org/meetings/en/SessionalDocuments/cimem7d8_en.pdf.

← 13. The timeframe indicated by the Cook Islands is 2020.