Remoteness

Overcoming the tyranny of distance to achieve sustainable development

Little has been said about the challenges and opportunities associated with remoteness for achieving the 2030 Agenda for Sustainable Development. Remoteness or isolation is an important dimension of vulnerability; one that is not always negative. Isolation or geographic remoteness can create unique, resilient communities with strong traditions and cultures, help preserve rare or fragile ecosystems; and as witnessed over the last 18 months, shield communities from the worst effects of global pandemicCommonly described by the WHO as ‘the worldwide spread of a new disease’, no strict definition is provided. In 2009, they set out the basic requirements for a pandemic: • New virus emerges in humans
• Minimal or no population immunity
• Causes serious illness; high morbidity/mortality
• Spreads easily from person to person
• Global outbreak of disease.
The US Centre for Disease Control uses a similar approach, but with a reduced set of criteria. It is very difficult to gauge whether the spread of a disease should be termed an outbreak, epidemic or pandemic. In other words, when to declare a pandemic isn’t a black and white decision -—
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Building a strong economy may require more innovation in a distant location without natural trade relations with bordering countries and with long distances to markets that offer higher volumes of demand. Remoteness results in higher costs of connecting to global value chains that need to be overcome to ensure competitiveness. Remoteness can also be especially challenging for small economies where domestic demand is insufficient for sustained economic growth, forcing businesses to access far-away destinations to reach larger markets.

Remoteness has many attributes other than just geographical distance. A standard dictionary definition of remoteness is typically comprised of two parts: The first focuses on physical distance (the geographic dimension) and the second on a lack of connection. Due to its multidimensional nature, remoteness can influence all aspects of sustainable development.

The 2030 Agenda -—
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—- set 17 goals for sustainable development addressing economic, social and environmental development challenges with the principle of leaving no one behind. In view of that principle, it is important to consider the specific challenges and opportunities faced by remote economies, such as small island developing states, some LDCsLeast developed country or LLDCsLandlocked developing country that must start their pursuit of sustainable development from a more challenging baseline.

The plight of island nations has been an issue of analyses and concern going back to the 1960’s. The SIDSSmall island developing states (SIDS) were recognized as a distinct group of developing countries at the Earth Summit in Rio de Janeiro in June 1992. More information on UNCTAD official page., that set of countries recognized as being particularly vulnerable to economic and environmental shocks, was first formally recognized at the Earth Summit -—
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—-, held in Rio de Janeiro, Brazil in 1992. But the international community had recognized that developing island countries were a special category from a developmental perspective long before that.

For instance, -—
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—- discusses the characteristics of island societies, noting that remoteness and smallness are their most distinguishable characteristics. He uses the term ‘tyranny of distance’ and lists the related challenges: high transport and communication costs; barriers to market access; fragile environments; dis-economies of scale and scope; limited division of labour; segmented market; remoteness or insularity; high-cost economy; over-blown public sector; and a high dependency on tourism. Kakazu finds that because of their smallness, remoteness and openness, island economies have a distinctive economic structure.

These findings are reflected by the -—
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—- “Development and Globalization: Facts and Figures” which provides statistical analysis of the economic, environmental and social situation of SIDS. The report notes that goods production in agriculture and manufacturing has declined in relative terms in many SIDS, while services like tourism, financial intermediation and the public sector have gained prominence.

Among the many challenges faced by SIDS, remoteness remains one the most formidable and deserves a comprehensive in-focus analysis in relation to the SDGsSustainable Development Goal. Greater distance from markets translates into increased costs, including transportation and insurance, weakening the competitiveness of domestic products in international markets and increasing the import bill. It typically means isolation from the main transportation routes or corridors, potentially making supply of resources more costly and unreliable. Additionally, infrastructure projects, such as those enabling connections to energy and communication networks, are more costly to implement and maintain.

Nevertheless, some small island economies have achieved high income levels based on exports, not of goods, but of financial, logistical or tourism services, for instance Singapore and the Bahamas. Indeed, an analysis of the new -—
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—- PCIProductive Capacities Index (PCI) is a multidimensional composite index that measures productive capacities of economies by using eight categories: natural and human capital, energy, institutions, private sector, structural change, transport and information, and communication technologies, which together yield the multidimensional productive capacity index -—
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—- shows that SIDS’ productive capacitiesUNCTAD defines productive capacities as consisting of the productive resources, entrepreneurial capabilities and production linkages that together determine a country’s ability to produce goods and services that will help it grow and develop -—
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—- are highly correlated with human development, and that GDPGross domestic product (GDP) is an aggregate measure of production, income and expenditure of an economy. As a production measure, it represents the gross value added, i.e., the output net of intermediate consumption, achieved by all resident units engaged in production, plus any taxes less subsidies on products not included in the value of output. As an income measure, it represents the sum of primary incomes (gross wages and entrepreneurial income) distributed by resident producers, plus taxes less subsidies on production and imports. As an expenditure measure, it depicts the sum of expenditure on final consumption, gross capital formation (i.e., investment, changes in inventories, and acquisitions less disposals of valuables) and exports after deduction of imports -—
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—-. per capita is highest in SIDS which have succeeded in transforming from agriculture to service activities, not necessarily through industrial transformation. Moreover, in the context where financial flows can move from one side of the planet to the other instantaneously and where a growing share of value added comes from the digital economy and intangibles, physical distance is no longer the impediment it once was. This illustrates how digital connectivity can alleviate at least some of the obstacles brought about by geographic isolation.

Cantu-Bazaldua -—
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—- presented a review of the ways in which remoteness has been studied in economics, for instance as a factor increasing transaction and information-exchange costs influencing bilateral trade or investment flows or by looking at the role of geographical distance on economic spillovers, such as technological diffusion. Remoteness is also one of the criteria included in the EVIEconomic Vulnerability Index, used to determine inclusion and graduation from the LDCLeast developed country category. According to -—
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—- the idea for the EVI dates back to 1985, originally to help explain the ‘Singapore Paradox’, where islands enjoying relatively high GDP per capita could be simultaneously economically vulnerable. In the EVI, remoteness is defined as the weighted average distance from closest world markets. It is calculated as the average distance to the nearest neighbours with a cumulative share of 50 per cent of world trade (exports and imports of goods and services). In addition, the indicator is adjusted for landlockedness -—
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Remoteness relates to more than just geographical distance from markets resulting in higher transportation costs. It also involves integration into transport networks, as well as political and cultural linkages. Thanks to the greater importance of the digital economy, access to and performance of digital networks is gaining greater importance. This chapter presents the main dimensions of remoteness and proposes indicators for measuring them in the context of the sustainable development of SIDS.

In the outcome document of the most recent global conference on SIDS, signatory countries called on the United Nations, its specialized agencies and relevant intergovernmental organizations to “elaborate appropriate indices for assessing the progress made in the sustainable development of small island developing States that better reflect their vulnerability and guide them to adopt more informed policies and strategies for building and sustaining long-term resilience”, as well as requesting “the tracking of progress and the development of vulnerability-resilience country profiles” -—
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—-. The indicators proposed herein represent a contribution to this direction.

This chapter studies remoteness as geographical distance adjusted for connectivity. All things being equal, a greater distance imposes additional costs and increases the isolation from markets and people. However, better connectivity could considerably reduce the distance premium. An economy can be distant from others yet well connected (Australia, for instance). While a country cannot control its physical location, it can influence its connectivity through targeted investment in infrastructure and through greater participation in cultural and political networks.

Remoteness has multiple dimensions

From a policy perspective, the broader analysis of remoteness introduces a more complete monitoring of sustainable progress, fully taking into consideration one of the most salient challenges faced by SIDS. More importantly, although location and geographical distance cannot be changed, the expanded definition of remoteness considers factors that can be improved through targeted investment and appropriate policies. This can serve as guidance when analysing the approaches taken by some small island economies to reach a high national income level in spite of their geographic remoteness.

Distance could be measured with respect to main populated areas, markets or sources of financing, for instance. Connectivity could refer to transport routes, socio-cultural linkages or digital networks, among others. Cantu-Bazaldua -—
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—- provides a discussion of dimensions of remoteness (see figure 1) and proposes a set of indicators for measuring them.

Figure 1. Dimensions of remoteness

1. Geographical distance from markets. This traditional dimension of remoteness indicates geographical proximity to other territories and separation from economic centres. It will be measured using three variables: distance to nearest neighbour, distance to economic centres, and distance to trading partners.
2. Distance from financing sources. While distance is not an obstacle for financial flows, financial activity tends to cluster around centres, where most business and investment decisions are made. Countries far from these centres risk falling off the radar. The indicators include distance to business centres, distance from sources of FDIForeign Direct Investment (FDI) is an investment involving a long-term relationship and reflecting a lasting interest and control by a resident entity in one economy (foreign direct investor or parent enterprise) in an enterprise resident in an economy other than that of the foreign direct investor (FDI enterprise or affiliate enterprise or foreign affiliate) -—
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   —-., and distance from ODAOfficial Development Assistance (ODA) are resource flows to countries and territories which are: (a) undertaken by the official sector; (b) with promotion of economic development and welfare as the main objective; (c) at concessional financial terms (implying a minimum grant element depending on the recipient country and the type of loan). In addition to financial flows, technical co-operation is also included -—
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3. Distance from cultural and political centres. A frequently neglected aspect of remoteness is the potential isolation from the centres of cultural and political power. These are the countries with a great deal of influence in defining international rules, shaping global discourse and setting cultural trends. This dimension will be assessed as the distance to the main centres of global soft power¹ and the countries with the strongest global presence, as measured through international indicators available in the literature.
4. Transport connectivity. Well-developed transport links could ease the burden of distance, facilitating the inflow and outflow of products and people. Maritime, air and land connectivity are measured in this dimension.
5. Social and political connectivity. It is important to consider also the cultural or social connections of a country with the rest of the world. This dimension is studied through indicators on the number of immigrants in the country and the stock of nationals living abroad, foreign (tertiary) students registered in the national education system and nationals studying (tertiary education) abroad, foreign diplomatic representations in the country, and membership in economic, trade, defence or other alliances.
6. Digital connectivity. For digital economy to mitigate disadvantages of geographic remoteness, ICTInformation and communications technology (ICT) is a diverse set of technological tools and resources used to transmit, store, create, share or exchange information. These resources include computers, the Internet, live broadcasting technologies, recorded broadcasting technologies and telephony -—
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   —-. infrastructure needs to be well developed with widespread access to these tools among businesses and individuals. This dimension will be assessed through three indicators: Internet access of the population; international bandwidth per Internet user, as a proxy of the available Internet infrastructure; and the latency rateLatency rate is a network performance metric, measured as the round-trip time that it takes for a packet of data to travel from a sending node to the nearest receiving server in each country and back. It is collected by Measurement Lab from a high number of tests performed across networks every day. A higher latency indicates a worse connection quality, therefore affecting network performance and opportunities to use ICTs for business or private connections., a measure of network performance.

Source: UNCTAD deliberations based on Cantu-Bazaldua -—
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Cantu-Bazaldua -—
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—- includes complete information on the variables considered, including their definition, data sources, and details on imputation methods. His paper also includes summary statistics for all the variables. The variables considered vary considerably in terms of data ranges and units of measurement and are thus transformed to a 0-100 scale through a min-max transformation to facilitate comparison. The variables will be presented for all SIDS, as well as aggregates for relevant comparison groups.² The visualizations use lighter colours to indicate a higher relative remoteness. Unless otherwise indicated, data refer to 2019.

SIDS are situated far from their main markets

SIDS are situated in remote locations as measured by distance to their nearest (non-SIDS) neighbour (figure 2, column 1). While the global (weighted) average is a distance of only eight kmkilometre to the nearest neighbour, an average citizen from a SIDS has to travel 371km to the closest non-SIDS country. Moreover, the distance ranges from zero for those SIDS sharing a border with another country, to 3 264km required to cover the distance from the Marshall Islands to its nearest non-SIDS neighbour (Indonesia). Tuvalu, Nauru and Samoa also register a high remoteness according to this variable.

It is also important to consider the distance to the largest countries to appreciate the economic opportunities for trade, investment, cross-border interactions and spillovers. SIDS are located far away from the main economic centres (figure 2, column 2), as measured by the average distance to countries weighted by their GDP. Different SIDS regions are situated in relative proximity to some large economic centres (e.g. Caribbean islands) but far from others. On average, SIDS are more remote than other country groups, such as LDCs or LLDCs, and especially when compared to all middle and high-income countries. According to this indicator, the most remote SIDS is Tonga, with an average (weighted) distance of 12 175km, followed by Fiji, Vanuatu and Samoa. However, the top 5 most remote countries according to this variable are not SIDS, but are mostly located in Oceania and South America, including New Zealand, Australia, Chile, Argentina and Uruguay, in that order; Tonga is ranked sixth.

SIDS are not necessarily more remote than other country groups when distance to trading partners (figure 2, column 3), weighted by their bilateral trade (exports plus imports of goods) has been taken into account. In fact, the average distance for all groups is remarkably similar, suggesting that countries tend to specialize in products and services tailored to nearby markets. However, for SIDS, there is a relatively high dispersion, ranging from the Bahamas (3 806km) to the Marshall Islands (8 864km), with Suriname, Cuba and Mauritius also registering high trade-weighted average distances. While the Marshall Islands is the SIDS economy most distant from its trading partners, it is only twelfth in the world rankings. The top 5 most distant countries using this variable are Chile, Brazil, Peru, New Zealand and Argentina, in that order.

SIDS are more distant from financing sources than others

The three distance variables from financing sources are correlated as the countries with the largest companies are also the main sources of other types of financing (in this case, private foreign investment and development assistance). Across all three dimensions, SIDS are on average more distant from financing sources than other country groups. High-income countries and LLDCs tend to be closer in proximity to origins of financial flows.

In terms of distance from main business centres (figure 3, column 1), measured by the revenues of the largest 500 firms, Tonga is the most isolated SIDS, followed by Fiji, Mauritius, Vanuatu and Samoa. However, from a more global perspective, the extremes are located in South America (Uruguay, Argentina, Chile, Paraguay, Brazil, Plurinational State of Bolivia), Oceania (New Zealand and Australia) and Southern Africa (Lesotho, South Africa).

The five SIDS with the greatest distance from FDI sources (figure 3, column 2) are Tonga, Fiji, Vanuatu, Samoa and Solomon Islands. In terms of distance to ODA donors (figure 3, column 3), the first four SIDS are also the most remote, with Tuvalu taking fifth place. According to both metrics, New Zealand and Australia are the most remote countries in the world, followed closely by the SIDS mentioned here.

SIDS remain distant from cultural and political centres

SIDS are also located far away from soft power centres (figure 4, column 1), as measured by the Global Soft Power IndexGlobal Soft Power Index is a composite index calculated from extensive public opinion surveys and expert assessments, evaluating the soft power of 60 countries, mostly high- and middle-income economies, along seven pillars: business and trade, governance, international relations, cultural and heritage, media and communication, education and science, and people and values. The data collection of the 2020 index took place in autumn 2019. published by -—
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—-. This group’s average is significantly above those of all other comparison groups. The most remote country according to this indicator is New Zealand, but six SIDS are ranked in the top 10: Tonga, Samoa, Fiji, Vanuatu, Tuvalu and Solomon Islands.

SIDS are also situated at a greater distance from centres of global presence (figure 4, column 2) than most countries, although less so than in the case of soft power centres. Here too, the most remote countries in the world are New Zealand and Australia, and in addition the top 10 includes a mix of SIDS, such as Tonga, Fiji, Vanuatu, Samoa and Tuvalu, and some South American nations, such as Chile, Argentina and Uruguay.

SIDS are well connected by air – less so by sea

For island economies, land connectivity is (mostly³) non-existent so other means of transport gain a greater relevance. For maritime connectivity (figure 5, column 1), Singapore is a clear outlier within SIDS, with a score almost three times higher than the second ranked small island economy, the Dominican Republic. In fact, Singapore is ranked second globally, after the most connected country in maritime networks (China) and just above the third placed country (Republic of Korea). Maritime connectivity is estimated through the liner shipping connectivity index, which indicates a country’s level of integration into global liner shipping networks.

In addition to Singapore and Dominican Republic, mentioned above, only three more SIDS exceed the average connectivity for middle income countries: Jamaica, Mauritius and Bahamas. On average, SIDS are not very well integrated into shipping connections. For countries with a high dependence on the sea, this low maritime connectivity could further aggravate the challenges of geographical remoteness -—
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For air connectivity, as measured by the number of international flights per year relative to population (figure 5, column 2), some SIDS with a high reliance on tourism are among the best connected in the world: Antigua and Barbuda, Saint Kitts and Nevis, Bahamas, Dominica, Nauru, Barbados and Palau. In addition to these SIDS, most of the top ranked countries are either micro-States (Luxembourg) or other island economies (Iceland, Malta, Cyprus). On average, SIDS are comparatively well connected by air transportation, with international flights per capita at a level comparable with high-income countries. However, not all SIDS are as well integrated. Papua New Guinea, Haiti and Guinea-Bissau are among the lowest ranked economies in this variable.

Most European micro-States (landlocked, with extensive land borders relative to their area and excellent roadways) are the best ranked considering land connectivity, constructed from the length of land borders, relative to total area, weighted by road infrastructure.⁴ Unsurprisingly given their lack of land borders, SIDS mostly scored zero, with a few exceptions, but nevertheless low scores (Timor-Leste, Belize, Dominican Republic and SIDS that are not islands or that share an island with another country).

SIDS are relatively well connected socially

Contrary to centrally located countries, working with neighbours over common border issues or tackling regional challenges, SIDS could lack opportunities to join alliances or shared initiatives, movement of persons and ideas. This dimension of remoteness is broader and more difficult to measure than the others. A full account would involve monitoring all spaces that allow exchanges between individuals, societies and governments. Given data limitations, this dimension is estimated using the seven indicators included in figures 6 and 7. These include immigration and emigration, cross-border exchange of students, diplomatic representations and participation in defence and trade agreements. While cultural and political links clearly extend beyond the areas measured by these variables, they are difficult to conceptualize and measure, especially through internationally comparable indicators with worldwide coverage.⁵ Cross-national trust can be important for connectivity and cultural spillovers, and is sometimes used as an indicator of cultural ties -—
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Migrants take with them ideas, traditions, practices and businesses. They build networks and bridges between their communities of origin and destination. For this reason, it is important to consider rates of both immigration and outward migration. Foreign immigrants constitute a sizable share of the population in several high-income SIDS, such as Bahrain, Singapore, and Antigua and Barbuda. However, other SIDS feature some of the lowest immigration rates in the world: in Cuba, Haiti, Papua New Guinea, Solomon Islands, Timor-Leste and Jamaica, immigrants constitute less than one per cent of the population. Overall, the average immigration ratio in SIDS is higher than in low and middle-income countries, although still at about one third of the levels observed in high-income countries.

A similar story is told by emigration (figure 6, column 2). One SIDS, Saint Kitts and Nevis, has the largest emigration rate in the world, with 2.4 nationals living abroad for each person living in the country. Other countries with high outward migration are Dominica, Suriname, Tonga, Grenada, Guyana and Samoa. Other SIDS, such as Maldives or Solomon Islands, exhibit a very low ratio in this variable. Nonetheless, with an overall emigration rate of 33.6 per cent, SIDS are significantly above the world average in this aspect.⁶

An interesting group of migrants, for which detailed statistics are available, are students that move to another country to pursue a tertiary education. The inbound mobility rate, measured as the percentage of students from abroad enrolled in a tertiary education program at a local university (figure 6, column 3), is very high in Grenada and Saint Kitts and Nevis, where 85 and 73 per cent of tertiary students are foreigners. Although these are clear extremes, the SIDS average remains well above the average for low and middle-income countries. In terms of outbound mobility rate (figure 6, column 4), SIDS are on par with high-income countries, although far from the high student mobility rates observed in some cases.

Many SIDS are less well connected politically

The number of foreign nations with at least one diplomatic representation (embassy, consulate or permanent mission) in a SIDS (figure 7, column 1) ranges from 50 in Singapore to two in Antigua and Barbuda, Dominica, Nauru, Saint Kitts and Nevis, Saint Vincent and the Grenadines, and Tuvalu. Based on the Global Diplomacy IndexGlobal Diplomacy Index includes a full listing of all diplomatic representations abroad from 61 countries, for a total of 7320 missions -—
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—-, it is evident that as a group, SIDS have one of the lowest numbers of diplomatic representations, below low-income countries and other groups such as LDCs and LLDCs. The results vary from zero in Yemen (no diplomatic missions at all) to 61 in Switzerland and the United States of America, meaning that all 61 origin countries featured in the dataset are represented in the country.

Inter-country linkages can also be analysed through agreements, pacts and other alliances. Defence agreements, some of the oldest international pacts in existence, are one manifestation of this. By using the somewhat outdated database from -—
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—-, which only includes data up to 2012, the most connected nations are the United States of America and Canada, having some type of defence agreement in force with 56 and 51 nations, respectively. Conversely, 45 countries have no such alliance in force. According to this variable, the average SIDS has defence agreements with 15 countries (figure 7, column 2), above the world average but still limited compared to other cases, particularly high-income countries.

A similar situation is observed when trade agreements are examined. According to the -—
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—- database, Egypt has the highest number of active bilateral or plurilateral trade pacts in force. They have active trade agreements with 105 countries, closely followed by members of the European Union, whoWorld Health Organization have a common international trade policy involving trade agreements with 98 countries. On the other hand, a handful of nations have no active agreements covering trade, including two SIDS (Palau and Sao Tome and Principle). The average SIDS has a trade agreement with 34 partners, less than the average for middle and high-income countries (40 and 67, respectively).

Digital connectivity of SIDS varies while some of them reach the world top

The first indicator of digital connectivity, the share of population that has access to the Internet (figure 8, column 1), shows that SIDS are well connected, although with a great deal of variability. Indeed, this variable ranges from 99.7 per cent in Bahrain, the highest digital connectivity in the world, to only 3.9 per cent in Guinea-Bissau, the country with the fifth lowest Internet access. On average, SIDS have similar outcomes than middle-income countries and better scores than LDCs and LLDCs.

International bandwidth per Internet user (figure 8, column 2) shows a skewed distribution for SIDS, with a few countries (Singapore, Bahamas, Saint Vincent and the Grenadines, and Saint Kitts and Nevis) among the best performers in the world, while many other SIDS' score is very close to zero. This mirrors the world distribution of this variable, which serves as a proxy for the Internet infrastructure in place. On average, SIDS have a relatively good attainment in this variable, outperforming the average for low- and middle-income economies, although still behind the high-income group.

The average SIDS performs as well as the average middle-income country and LLDCLandlocked developing country in the latency rate (figure 8, column 3), based on all tests conducted in each country in 2019. SIDS perform significantly better than low-income countries or LDCs. This average hides a large variance, with one SIDS at the bottom of the world rank (Tuvalu, with a median latency of 1 821 milliseconds), whereas other SIDS have some of the best Internet connections worldwide, like the Bahamas or Singapore.

An overall remoteness index – top 15 featuring mostly SIDS

The previous analysis presented 21 variables that can provide a comprehensive assessment of remoteness across six dimensions. This shows that traditional measures of geographical distance to markets are not sufficient to give a complete panorama of the challenges of distance. Moreover, a large number of connectivity factors could mitigate or accentuate remoteness, and they should be taken into account. This section presents the steps for calculating a remoteness index and the results for SIDS and relevant benchmarks. The methodology is discussed in more detail by Cantu-Bazaldua -—
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For some of the variables presented in the above analysis, a higher score indicates greater remoteness, whereas for others the opposite was the case. To overcome this problem, all variables were transformed so that a higher value corresponds to greater remoteness. The index for each dimension was calculated through a simple average of the variables included, and the results were adjusted to a 0-100 scale through a min-max transformation. This way the most remote country takes a value of 100 and the most proximate country a value of zero. The overall remoteness index was calculated as a simple average of the aggregate indicators for all six dimensions.

According to the overall remoteness indicator (figure 9), the most remote SIDS is Tuvalu, closely followed by Tonga and Vanuatu. Samoa and the Solomon Islands complete the top 5. The top 10 is composed of nine Pacific SIDS, which are remote on all or most dimensions. New Zealand is the only country that makes top 10 and is not SIDS.

For some SIDS, the overall index is improved by positive scores in one or a few dimensions of remoteness. For example, while Timor-Leste and Papua New Guinea score high in most dimensions, their overall index score is reduced by their geographical location, as they are relatively close to their main markets and trading partners. A similar situation is observed in Nauru, although in this case it is the relatively high transport connectivity, mostly based on air transport, which lowers the overall remoteness score. Mauritius’ score is significantly improved by its well-developed digital connectivity.

Figure 9 also shows some SIDS that are more proximate across most dimensions, but whose score is penalized by a poor result in one dimension. For Suriname, Cuba, Guyana, and Trinidad and Tobago, the area lagging behind is transport connectivity. For the Maldives and Palau, it is their social and political isolation.

The least remote SIDS are at the bottom of the figure starting with the Bahamas which compensates for a relatively low social and political connectivity with shorter average distances to markets and an excellent digital infrastructure. Following closely are Singapore, Bahrain and some of the high-income SIDS in the Caribbean, such as Saint Kitts and Nevis, Antigua and Barbuda, and Barbados.

Comparing SIDS’ scores to the world distribution, they are indeed among the most remote economies in the world, particularly Pacific SIDS. All top-15 most remote countries are Pacific SIDS except New Zealand (8th), Australia (13th) and Madagascar (15th).⁷ The most remote SIDS outside the Pacific is Comoros, ranked 18th in the world. For scores for all countries see Cantu-Bazaldua -—
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Figure 10 presents the aggregate results for SIDS with several benchmarks. A first highlight of this graph is the strict ordering of each of the six dimensions of remoteness according to income level. This indicates a clear link between remoteness and economic performance, as well as a clustering effect. SIDS’ a score in the remoteness index is comparable to low-income economies.

Another striking result is that SIDS are not worse off than LDCs or LLDCs in terms of remoteness. While they are located at a greater distance from markets, financing sources and cultural centres, they partially compensate for this disadvantage through better connectivity, especially in terms of ICT and digital technologies. This draws attention to the importance of connectivity and considering all aspects of remoteness beyond just geographical distance when studying the development of SIDS.

As shown in the country-level results (figure 9), the SIDS’ average hides some important differences between countries. SIDS in the Pacific are distinctly more remote, with a higher score in most dimensions, particularly transport and socio-political connectivity. SIDS in the Atlantic and Indian Ocean are the least remote, thanks in part to their improved digital and transport connectivity.

The figures presented in this chapter also include an aggregate for analytical SIDS -—
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Does remoteness hamper sustainable development?

To study the relationship of remoteness to the economic, social and environmental pillars of sustainable development, we compare the remoteness index with some composite indicators broadly representing these themes. The 231 SDGSustainable Development Goal indicators designed to measure the 17 goals and their respective 169 targets are rather narrow in scope when looked at individually, and comprehensive data coverage is not available. Therefore, six indicators are selected to evaluate their interaction with the remoteness index and dimensions of sustainable development. These include GDP per capita, PCI, Gini indexGini index measures the extent to which the distribution of a variable over a population deviates from a perfectly equal distribution. A Gini index of zero represents perfect equality and 100, perfect inequality., GIIGender Inequality Index (GII) measures gender inequalities in three aspects of human development: reproductive health, measured by maternal mortality ratio and adolescent birth rates; empowerment, measured by proportion of parliamentary seats occupied by females and proportion of adult females and males aged 25 years and older with at least some secondary education; and economic status, expressed as labor market participation and measured by labor force participation rate of female and male populations aged 15 years and older -—
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Data for SIDS show that GDP per capita is negatively correlated with remoteness (ρ = -0.61) (see figure 11). The more remote the country, the lower their GDP per capita. Singapore had the highest GDP per capita in 2020, and the lowest overall remoteness score, together with the Bahamas and Saint Kitts and Nevis. The negative correlation between GDP per capita and remoteness is even higher (ρ = -0.66) among the rest of the SIDS excluding Singapore. When looking at poor connectivity only (dimensions 4-6 of the overall index on transport, socio-political and digital connectivity), the negative correlation with GDP per capita is notably higher (ρ = -0.79).

We also look at the new UNCTAD PCI as another proxy indicator of the economic pillar (figure 12). It provides a more comprehensive measure than GDP per capita as it assesses productive capacities from the perspective of eight categories: natural capital, human capital, energy, institutions, private sector, structural changeStructural transformation or change can be broadly defined as the reallocation of economic activity across three broad sectors, agriculture, manufacturing and services, which accompanies the process of economic growth -—
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Overall remoteness is negatively correlated with income inequality (ρ = -0.45) in SIDS, as measured by the Gini index (figure 13). Geographic remoteness i.e., distance (dimensions 1-3 on distance from markets, financial and cultural-political centres) is more strongly negatively correlated with income inequality (ρ = -0.51) than poor connectivity (ρ = -0.21). People living in the most geographically remote SIDS experience lower income inequality. Remote locations may offer less opportunities for achieving high income levels, especially small rural communities. It should be noted, however, that the Gini index is not available for the eight least remote SIDS, including Bahamas, Saint Kitts and Nevis, Singapore, Bahrain, Antigua and Barbuda, Barbados, Dominica and Grenada.

For SIDS that have GII data, gender inequality has a relatively high positive correlation (ρ = 0.68) with poor connectivity (dimensions 4-6), but not with geographic remoteness (ρ = 0.13). The overall remoteness index is positively correlated with gender inequality (ρ = 0.46) (figure 14). In general, SIDS with higher transport, social, political and digital connectivity provide a more gender equal environment, but geographic distance does not mean increased gender inequality. GII data are available for 19 SIDS only. Data gaps are somewhat more common for the most remote SIDS.

The overall remoteness index correlates negatively with the HDI (ρ = -0.57) (figure 15). The negative correlation of human development and poor connectivity (dimensions 4-6 of remoteness) is significantly higher, -0.76, with little correlation with geographic remoteness only (dimensions 1-3), -0.22. Small island economies with good transport, social, political and digital connectivity have achieved higher human development.

Due to their geography, SIDS face a unique and varied mix of environmental concerns, ranging from increased exposure to storms and floods, to the loss of their actual land. SIDS account for three of the top five most environmentally vulnerable countries according to the EVI in 2020. Kiribati, Marshall Islands and Tuvalu are the most vulnerable countries globally according to the EVI. These small island economies are also among the most remote countries in the world. Overall remoteness is positively correlated with economic and environmental vulnerability (ρ = 0.58).

Geographic remoteness adds an extra barrier but can be mitigated

The analyses presented here show that remoteness has a negative impact on the economic, social and environmental aspects of sustainable development and places additional demands on countries. Figure 17 summarizes the correlations of overall remoteness, geographic remoteness and limited connectivity across the themes covered by the indicators analysed in figures 11 to 16. The analyses show that geographic distance correlates most positively with environmental vulnerability and most negatively with income inequality. They also show that the correlations with geographic distance are weaker than for limited connectivity, and distant location can, thus, be mitigated by improving transport, social, political and digital connectivity. Limited connectivity has the strongest negative correlation with GDP per capita, human development and productive capacity, and a strong positive correlation with gender inequality and vulnerability in SIDS.

There are examples of highly geographically remote countries outside of SIDS that have also managed to mitigate the impacts of geographic isolation. Across all geographical indicators (the first three dimensions), New Zealand is the most remote country in the world, sometimes by a large margin. However, it partially makes up for this disadvantage through a well-developed connectivity infrastructure, especially ICT. A similar situation can be observed in Australia. Uruguay, for instance, compensates for its location with excellent digital and transport connections, whereas Chile has well developed social and political networks, including one of the world’s highest number of defence and trade pacts. The remoteness ranks for these four selected countries are shown in table 1, where top ranks (i.e., high relative remoteness) in the first three dimensions are offset by good performance in the connectivity dimensions, therefore improving the overall remoteness score.

These four cases strengthen the message that geographic remoteness is not an insurmountable obstacle. While geographical distance does entail higher transportation costs and hinders participation in global decision-making, this can be offset by targeted investments in transport and ICT connectivity, as well as an active participation in cultural and political networks. SIDS have already done important progress in this front and, on average, according to the index, they are not more remote in digital connectivity than other groups of countries, such as LDCs or LLDCs.

Remoteness is a gap that needs to be bridged to progress towards SDGs (see figure 18). It brings challenges, many of which can be mitigated by investing in transport and digital connectivity and cultural and political networks. But those investments naturally require sufficient resources and finances. It seems that highly remote countries do not start their journey towards the 2030 Agenda on equal footing, and this should be taken into consideration in global development assistance and finance.

Figure 18. Remoteness as a factor in sustainable development

Source: UNCTAD deliberations.

The broader study of remoteness presented herein also highlights the heterogeneity within SIDS. While most SIDS located in the Pacific are objectively remote in all dimensions, SIDS in the Caribbean or in the Atlantic and Indian Oceans are no more remote than the average middle-income country. This illustrates the importance of having detailed, disaggregated statistics for SIDS that reflect the most pressing challenges they face and highlights the usefulness of regrouping SIDS for analytical purposes, reflecting discussions in -—
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A remoteness index, along the lines presented here, could be used as a measure to evaluate the challenges faced by SIDS due to their isolated location. The index reflects the importance of geography, but also of attenuating factors stemming from targeted policies for improving connectivity. Moreover, it reflects key aspects of remoteness, including the limited options for transport connectivity with no land borders for most SIDS, but also lack of access to maritime transport for most LLDCs. As suggested by Cantu-Bazaldua -—
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Notes

1. An idea originally developed in -—
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   —-, “soft power” refers to the ability to influence the behavior of others to get the desired outcomes through attraction and co-option rather than coercion (or “hard power"). According to the author, it relies on three pillars: political values, culture and foreign policy.
2. Note that country aggregates are calculated as a weighted average of the corresponding variables, using population as weight.
3. Some islands, however, have a better land connectivity, e.g., in the case of shared islands, mainland islands and connected islands -—
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4. This indicator is only a proxy for land connections and does not consider important factors affecting cross-border transportation, including geographical features (mountainous or fluvial borders), border-crossing infrastructure, customs and border-crossing administrative efficiency, or other obstacles.
5. For instance, an interesting indicator would be the share of the world population that share the same language. A shared language facilitates exchange and transmission of ideas, and gives access to larger knowledge pool and more media sources, therefore reducing isolation. Although there are specialized databases for this variable (for instance, CEPII or Ethnologue), they present important data gaps, particularly for some SIDS.
6. Some cases could be affected by practices where countries grant citizenship by investment. This could have an ambiguous relationship with social connectivity, but the available data do not allow a more detailed disaggregation.
7. On the other hand, the 30 least remote countries in the world are all located in Europe. The five less remote countries are Luxembourg, Belgium, the Netherlands, Cyprus and the United Kingdom.

References

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