Rethinking the role of critical minerals for development

The global shift toward a low-carbon economy has intensified the demand for critical minerals, placing resource-rich developing countries at the centre of a new geopolitical and economic landscape. In this context, UNCTAD plays a role from the development perspective by promoting fair, inclusive and sustainable trade in critical minerals. UNCTAD also co-led the Secretariat of the United Nations Secretary-General’s Panel on Critical Energy Transition Minerals -—
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—-, which focused on how to guide critical energy transition minerals towards equity and justice.

The UN Panel defines critical energy transition minerals as minerals necessary to construct, produce, distribute and store renewable energy, including copper, cobalt, nickel, lithium, graphite, REEs and aluminum required for electric vehicles and battery storage; and silicon, cadmium, tellurium and selenium (among others) that build solar panels. Wind and hydropower, for instance, require copper and chromium, zinc and aluminium -—
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At COP29, UNCTAD outlined four strategic priorities to address a $225 billion investment gap in mining projects across developing economies: investment in infrastructure, fairer trade rules, transparent governance and knowledge sharing -—
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—-, aligning with the UN Panel’s principles on equitable benefit-sharing.

At the international investment policy level, a number of recent IIAs include specific provisions facilitating and promoting investment in energy and raw materials. These provisions aim to improve the investment environment and remove ground-level obstacles for investors’ activities. Certain recent IIAs for instance provide for the transparency and simplification of procedures for investment in raw materials (see e.g. the European Union-New Zealand FTA -—
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—-). When aligned with countries’ national critical minerals strategies, IIAs can support industrial and investment policy objectives for strategic mineral resources. At the same time, IIAs composed of thousands of agreements may limit space to regulate critical minerals’ extraction and exploitation and raise the risk of costly investor-state disputes. For example, at least five cases in 2024 involved the mining of critical minerals, such as copper -—
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—-, lithium -—
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—-, titanium potentially contained in heavy mineral sands deposits -—
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This SDG Pulse In-Focus provides data-driven analysis of trade and production of critical minerals and proposes UNCTAD’s list of critical minerals. This work builds on the UN Panel’s definition adding to it a review of minerals strategic for developing economies, mapping existing classifications of critical minerals, and offering statistical analysis of what makes minerals critical for both developed and developing economies.

Toward a comprehensive list of critical minerals for trade and development

UNCTAD considers minerals¹ critical not only by their global importance and supply risks but by their relevance for trade and development, reflecting the priorities of developing economies. A mineral is considered critical if it supports structural transformation, energy and digital transitions, or industrial upgrading, while it might also pose supply risks, or offer trade opportunities.

This list of 60 critical minerals mapped to 499 harmonized system (HS) codes can inform the analysis of global trade in minerals and support SDG-aligned national strategies. The data enables analysis of trade dependence, export restrictions, production concentration and value-added potential. While the current list focuses on raw and semi-processed minerals and metals, it could be further expanded in the future to enable the analysis of processed critical minerals and their role in circular economy and global value chains (see the full list in annex 2.). All subsequent analysis draws on this UNCTAD list and its categorization.

Figure 1. UNCTAD’s list of critical minerals by role in energy transition and other areas

As part of this approach, minerals were grouped by their relevance to the energy transition into three categories: those required for the transition (27) (e.g., cobalt, copper, lithium, REEs), relevant to it (10) (e.g., iron ore and steel, palladium, zirconium), and other critical minerals (23) (e.g., gold, gypsum, lead, silver). This distinction helps highlight which materials are under increasing geopolitical and economic scrutiny due to their strategic importance in clean energy technologies. Indeed, this supports targeted analysis of materials essential to technologies like electric vehicles, solar panels and hydrogen systems. Critical status was then assessed using two key indicators, Revealed Comparative Advantage and Trade Concentration Index (for both exports and imports), to classify minerals into high, moderate, or low criticality. See annex 1. for the full list of methodological steps.

Trade in critical minerals reached $2.5 trillion in 2023, with Asia emerging as the world’s largest importing market

In 2023, global trade in raw and semi-processed minerals reached approximately $2.57 trillion in imports and $2.52 trillion in exports. This trade segment represented over 10% of total global exports, highlighting its critical role in the international economy.

Regionally, Asia emerged as the largest market for critical minerals, accounting for $1.5 trillion in imports, more than half of the global total—while exporting only $825 billion, with China accounting for roughly 40 per cent of imports in the Asia region. This substantial trade deficit of around $680 billion underscores Asia's role as the primary global hub for processing and manufacturing activities that relies heavily on critical mineral inputs.

In contrast, Africa, the Americas and Oceania recorded significant trade surpluses, indicating their dominant roles as suppliers of critical minerals. Africa exported nearly $266 billion reflecting a share of 10.6% of world trade, while importing only $68 billion, and Oceania, despite relatively low import volumes, exported over $239 billion. The Americas also showed strong export performance, with a surplus of nearly $194 billion. Europe maintained a more balanced trade profile, with exports slightly exceeding imports. These patterns highlight the global supply chain structure, where mineral-rich regions provide essential inputs for the energy transition, while industrialized and manufacturing-heavy regions, particularly Asia, drive demand. These trade patterns also reflect underlying investment trends in extraction and processing, which shape the geography of mineral value chains.

Figure 2. Asia imports over half the world’s critical minerals, while Africa and Oceania emerge as critical mineral suppliers

Total value exports and imports of raw and semi-processed critical minerals, by region, in billions of dollars, 2005-2023

Source: UNCTAD calculations based on UN Comtrade Database -—
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Minerals required for energy transition drive $773 billion in exports – one third of the total exports of critical minerals

In 2023, global exports of critical minerals required for energy transition amounted to $773 billion (31% of global exports of critical minerals), $674 billion (27%) for minerals relevant to energy transition, and $1,078 billion (43%) for all other critical minerals.

Critical mineral exports grew significantly from 2005 to 2023 across all regions, with Asia and Europe leading in total values. Asia shows the most significant and sustained increase, driven largely by exports of other critical minerals and those relevant to energy transition. The Americas display fluctuating trends among the three segments of critical minerals, with strong overall growth, while Africa records steady growth with a gradual rise in energy-transition-related minerals. Oceania, though starting from a lower base, shows consistent increased and a balanced export mix. Overall, the data reflects increasing global supply for critical minerals, especially for clean energy minerals, such as cobalt, copper, lithium, nickel and REEs.

Figure 3. Exports of energy transition minerals increased until 2022, most in Asia and Europe

Regional exports of raw and semi-processed critical minerals in value, by category of energy-transition-related minerals, in billions of dollars

Source: UNCTAD calculations based on UN Comtrade Database -—
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Data show deep bilateral dependencies in critical minerals’ trade

In 2023, global trade in critical minerals revealed deep bilateral dependencies. Australia emerged as the top exporter by trade value, with over $231 billion in critical mineral exports, primarily to China, Japan and India. Other major exporters included the United States and China. Notable trade corridors included Australia–China ($95 billion), Hong Kong–China ($43 billion) and Canada–United States ($41 billion). Several bilateral flows exceeded $10 billion, including those between the Democratic Republic of Congo and China, the United Arab Emirates and India, and Brazil and China, underscoring Asia’s central role as a demand hub. These patterns highlight the strategic concentration of mineral supply chains.

Battery and electric vehicle manufacturing affect the top traded minerals globally

Copper, aluminium and nickel are the top traded critical minerals essential for energy transition, together with other energy-relevant minerals, such as iron ore and steel, sulphur and potassium.

Africa emerged as the breakout performer in copper, nearly doubling exports (+98.2% to $44 billion) to meet surging demand for electrical infrastructure and electric vehicles. The continent also led nickel growth with a remarkable 122.8% surge, while Asia's nickel exports more than doubled (+107.5% to $15 billion), fuelled by battery manufacturing needs.

Iron ore maintained its position as an important industrial mineral, with Asia's exports growing 52.8% to $192 billion – underscoring ongoing steel demand. Oceania's iron ore shipments grew steadily (+33.7% to $94 billion), although outpaced by its metallurgical coal expansion.

Energy transition needs are significantly reshaping trade flows of critical minerals as reflected by the top 10 globally exported minerals, with regions rich in critical metals gaining strategic economic leverage.

Figure 4. Exports of minerals needed for energy and digital transitions significantly up from 2019

Top 10 globally exported minerals by region, in billions of dollars, 2019 and 2023

Source: UNCTAD calculations based on UN Comtrade Database -—
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Note: The top 10 exported minerals were identified based on total global export values in 2019-2023.
Gold exports from Europe largely reflect refined gold and may include significant volumes of re-exports and re-imports.

Top mineral producers aren’t always the top exporters

Data reveal striking patterns of concentration in the production of critical minerals: China leads in aluminium and REEs, while the Democratic Republic of Congo dominates cobalt. Australia is the top producer of lithium, and Chile remains the foremost copper producer. However, production statistics are not mapped to HS codes, which are used in trade reporting. This disconnect makes it difficult to directly compare raw production with export volumes. Complementary investment data - particularly from project- and firm-level databases - can help fill this gap by identifying where production and processing facilities are being established by multinational firms -—
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—-. Still, a compelling narrative emerges; for instance, China, while being the top producer of several minerals, is not always the top exporter. This suggests high domestic consumption or value-added processing, where raw materials are transformed into intermediate or final products before being exported. Similarly, South Africa, which accounts for over 80% of global platinum and other PMG production, exports less raw material than expected, as much of it is refined domestically before entering global markets. These dynamics underscore the importance of looking beyond extraction to understand the full picture of mineral flows and economic strategy and of developing a full list that identifies final goods that depend on critical minerals.

Figure 5. Explore the top 5 mineral producers, by mineral

Mineral production for top five producers (2021-2023 average) and the Rest of the World, share

Select a mineral:

Aluminium Antimony Arsenic Barite Bauxite Bentonite Beryllium Bismuth Boron Cadmium Chromium Cobalt Copper Diamonds Diatomite Feldspar Fluorspar Gallium, Germanium, Indium, Niobium, Tantalum, and Vanadium Gold Graphite Gypsum Iron ore and steel Kaolin Lead Lithium Magnesium Manganese Mercury Metallurgical Coal Molybdenum Nickel Other PMG Palladium Perlite Phosphates Platinum Potassium Rare-earth elements Rhenium Selenium Silver Sulphur Tin Titanium Tungsten Uranium Zinc Zirconium

Source: UNCTAD calculations based on World Mining Data -—
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Note: The top 5 producing economies were identified based on total production values in 2023. The production data for minerals is not directly comparable with the UNCTAD list of critical minerals due to differences in classification systems between production statistics and trade data. While trade data is categorized using HS codes, production data is based on mineral outputs that are not always mapped one-to-one with HS-coded traded products. Although efforts were made to align the two datasets, discrepancies remain, as some minerals reported in production statistics may not correspond exactly to those captured in trade flows. Therefore, caution is needed when interpreting which minerals are produced and traded, and when comparing both series.

Trade in critical minerals highly regionally specialized

Figure 6 shows that Africa emerges as a dominant net exporter of critical minerals such as cobalt, manganese and platinum, reflecting its rich geological endowment and growing role in global supply chains. However, it remains reliant on imports for minerals like boron and arsenic (the latter being important for gold processing), largely due to limited domestic production capacity. Oceania, particularly Australia, plays a pivotal role as a global supplier of iron ore, nickel and zinc, yet depends on external sources for potassium and fluorspar. Asia, driven by its vast industrial base, mainly in China, faces substantial trade deficits in cobalt, manganese and chromium, although it maintains a competitive edge in the export of REEs and graphite. Europe presents a mixed profile: while it shows net surpluses in refined gold, palladium and other PMG, these are primarily the result of its advanced refining infrastructure (especially for gold) rather than raw material extraction. At the same time, Europe remains a net importer of manganese, zirconium and graphite. The Americas maintain a relatively balanced trade position, with strong exports of lithium, copper and zinc, but continue to import chromium and manganese to meet industrial demand.

Figure 6. Trade surpluses and deficits across regions underscore global interdependence in critical mineral supply

(Normalized net trade in minerals balance, by continent, 2023)

Source: UNCTAD calculations based on UN Comtrade Database -—
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Note: Net mineral trade balance values is calculated according to the following formula: (X_{ji} - M_{ji})/(X_{ji} + M_{ji}) where i refers to specific Mineral (or its commodity composition), j … economy (or group of economies), X_{ji} … economy’s j exports of specific mineral commodity/mineral category i to World M_{ji} … economy’s j imports of specific mineral commodity/mineral commodity category i from World. Net mineral trade balance values range between -1 and 1. The positive value indicates that an economy has net exports or surplus. The negative values mean a deficit, indicating that the economy imports more than it exports.

Export restrictions shape critical minerals’ trade

Export restrictions can generate supply uncertainties and influence global prices, as well as investment decisions. The data show a clear pattern: minerals required for energy transition—such as copper, zinc, germanium and others, tin and nickel—face a significantly higher and growing number of export restrictions compared to other traded critical minerals. This trend reflects rising geopolitical sensitivities and growing domestic value-chain ambitions in producing countries. In contrast, minerals not directly linked to new energy technologies generally experience fewer trade restrictions. The heatmap below highlights how critical minerals are subjected to export restrictions, which may affect supply security for energy transition worldwide.

Figure 7. Rising restrictions on exports of critical minerals could disrupt energy transition

Total number of export restrictions, by mineral, 2019-2023

Source: UNCTAD calculations based on -—
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Note: Total number of export restrictions corresponds to aggregated policy measures including export taxes, quotas, licensing requirements, export bans, minimum export prices, VAT rebate reductions and other administrative controls -—
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—-. The radiant color indicates the intensity of export restrictions. The number of critical minerals shown in this figure differs from those used in the trade analysis. The database includes only minerals identified as critical raw materials by -—
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—- and for which data is available under HS 6-digit codes (HS07 classification).

When examining critical minerals essential for the energy transition, the highest number of export restrictions between 2019 and 2023 were imposed by countries such as Democratic Republic of Congo, Mongolia, India, Burundi and Zambia. These restrictions primarily target key minerals including copper (notably in Democratic Republic of Congo, Mongolia, Zambia and Argentina), molybdenum (Mongolia), and a group of high-tech or strategic minerals such as gallium, germanium, indium, niobium, tantalum and vanadium (notably in Burundi and Ethiopia). Zinc has also been subject to restrictions, particularly in India, Burundi and Ethiopia.

Figure 8. Countries like Democratic Republic of Congo, Mongolia and India account for most export restrictions on energy-transition minerals

Number of export restrictions by country for critical minerals required for energy transition, average over 2019-2023

Source: UNCTAD calculations based on -—
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Note: This chart displays the average number of export restrictions by country from 2019 to 2023, focusing on countries with the highest levels of restrictions. Each country has its top two most frequently restricted minerals highlighted in distinct colours. All the rest of the minerals are marked in grey. The number of critical minerals shown in this figure differs from those used in the trade analysis. The database includes only minerals identified as critical raw materials by -—
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How critical are these minerals for different countries and regions?

It is possible to analyse how critical minerals are for certain countries or regions using a criteria-based approach. This can be done by analysing : (1) supply risk, captured through an import concentration index, which reflects dependency on a limited number of suppliers; (2) trade opportunity or market dominance, assessed via export concentration, indicating a region’s potential leverage or vulnerability in global markets; and (3) strategic positioning, measured through Revealed Comparative Advantage³ to identify minerals where a region holds a relative trade strength. For example, a mineral with high supply risk in Europe may be a trade opportunity for Africa, or vice versa (see table 1).

Table 1. Highly critical minerals in Europe are often less critical for Africa and vice versa

Low, medium and highly critical minerals for Africa and Europe

Minerals	Criticality status
	Africa	Europe
Aluminium	Low	Moderate
Bentonite	High	Low
Copper	Low	High
Diatomite	Low	Moderate
Fluorspar	Low	High
Garnet	Low	High
Gold	Low	Moderate
Graphite	Moderate	High
Gypsum	Low	High
Kaolin	High	Low
Nickel	Low	Moderate
Perlite	Low	High
Phosphates	Low	High
Silicon	High	Moderate
Sodium	Low	Moderate
Strontium	High	Moderate
Zinc	Low	Moderate

Source: UNCTAD calculations based on UN Comtrade Database -—
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Note: Only minerals with divergent criticality classifications between Africa and Europe are shown. Minerals with identical status in both regions are excluded.

For instance, copper and phosphates are of low criticality in Africa due to abundant reserves and production capacity, yet they are highly critical in Europe, where supply is constrained. Conversely, kaolin is highly critical in Africa, while Europe maintains a more stable supply. Countries such as Nigeria, Ghana and South Africa hold significant kaolin deposits, often underutilized, but with strong potential for industrial development -—
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Minerals like graphite and nickel show moderate to high criticality across Africa and Europe, underscoring their growing importance in energy transitions. Notably, aluminium is marked as low in Africa due to bauxite abundance, but this overlooks the continent’s limited refining infrastructure, which constrains value addition, suggesting a potentially higher strategic relevance. Finally, it is important to assess the role of critical minerals in a flexible and context-specific way to correctly inform policy and investment strategies also in developing regions.

Global supply of critical minerals increasingly dependent on fewer exporters

Between 2019 and 2023, the export concentration index reveals a sharp rise for minerals such as cobalt, chromium, lithium and graphite, suggesting that global supply has become increasingly dependent on fewer exporters. This trend is particularly noticeable for graphite and lithium, which are essential for energy storage and battery technologies. Conversely, minerals like perlite, cerium and zirconium have seen a decline in concentration, indicating a more diversified and potentially resilient supply landscape.

Figure 9. Battery minerals like lithium and cobalt faced rising supply chain concentration

Export market concentration index, 2019 and 2023

Source: UNCTAD calculations based on UN Comtrade Database -—
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Note: The concentration index of exports ranges from zero to one, with a larger value indicating a higher concentration in the export market. For example, a value of HHI equal to zero indicates that all countries in the world export an equal share of product i, while a value of one means that a single country is responsible for all exports of product i. This index measures, for each product, the degree of export market concentration by country of destination. It tells us if a large share of commodity exports is bought by a small number of countries or, on the contrary, if the exports are well distributed among many countries -—
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Based on production and market concentration (figure 10), the most strategically vulnerable minerals—those in the top-right quadrant—include cobalt, beryllium, graphite and magnesium. Those are characterized by high concentration, and thus a heavy reliance on a small number of countries for both supply and demand. In contrast, minerals like copper, gold, sulphur and tin (the bottom-left quadrant) are widely produced and traded, suggesting a more stable and competitive market environment.

Minerals in the upper-left quadrant are produced by a few countries but exported to a wide range of markets. Producers such as Australia and Brazil for iron ore, China for aluminium, and Brazil and China for gallium, germanium, indium, niobium, tantalum and vanadium have a strategic opportunity to expand processing capacity, deepen industrial linkages, and strengthen their role in global supply chains. As countries accelerate the shift to low-carbon technologies and digital infrastructure, ensuring resilient and diversified mineral supply chains becomes increasingly critical.

Figure 10. Market and production concentration increases risks in global supply of minerals

Production concentration index, export market concentration index, and global export values in billions of dollars, averages for 2019-2023

Source: UNCTAD calculations based on UN Comtrade, UNCTADstat and World Mining Data -—
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Note: The x-axis shows the export market concentration index, and the y-axis shows the production concentration index, both measured using the normalized Herfindahl-Hirschman Index (HHI), ranging from 0 (diversified) to 1 (highly concentrated). Values above 0.25 indicate high concentration -—
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—-. Bubble size represents the global export value of each mineral in billions of dollars, highlighting its economic weight. All values (indices and export values) are calculated as averages for the period 2019–2023. The production data for minerals is not directly comparable with the UNCTAD list of critical minerals due to differences in classification systems between production statistics and trade data. While trade data is categorized using HS codes, production data is based on mineral outputs that are not always mapped one-to-one with HS-coded traded products. Although efforts were made to align the two datasets, discrepancies remain, as some minerals reported in production statistics may not correspond exactly to those captured in trade flows. Therefore, caution is needed when interpreting which minerals are produced and traded, and when comparing both series.

Mapping of classifications and lists for assessing critical minerals

UNCTAD has developed a comprehensive list of raw and semi-processed critical minerals by mapping and analysing the classification approaches used by leading international and regional institutions, as well as reviewing national and regional assessments. The mapping includes the IEA’s demand-driven approach focused on clean energy technologies, the EU’s broad industrial and sustainability-oriented framework, the USGS’s national security lens, and the WTO-ADB’s trade-based classification. It also incorporates insights from the OECD’s governance and trade monitoring tools, the World Bank’s demand trajectory analysis, ESCWA’s development-focused regional perspective, as well as the AU’s agenda for structural transformation and climate resilience. By comparing how different institutions define and classify critical minerals, UNCTAD identifies areas of convergence and divergence. This makes it easier to see which minerals are consistently considered critical and which are particularly important for structural transformation in developing economies. The comparison also lays the groundwork for a more consistent basis for monitoring trade and production, while keeping development priorities at the centre.

Table 2. Mapping of institutional approaches to critical minerals

Organization	Definition / Approach	Key Criteria	List Status	Focus Area	Distinctive Features
AU	Development-focused approach to leverage mineral wealth for local industrialization and climate resilience.	Resource endowment, job creation, value chain localization, sustainability	Emerging list (prioritizes cobalt, lithium, graphite, rare earths)	African mineral-producing economies, just energy transition	Emphasizes local beneficiation, inclusive development and environmental safeguards. Aligns with AU Agenda 2063 and the SDGs, prioritizing minerals critical to Africa’s climate resilience and industrialization.
ESCWA	Regional framework linking mineral use to development opportunities and industrial capacity.	Local value addition, institutional capacity, energy transition role	Regional list (14 minerals)	Arab countries' industrial development and energy transition	Reframes criticality around strategic potential. Prioritizes domestic processing, job creation and equity in mineral value chains.
EU	Based on economic importance and supply risk. Extended by foresight on strategic technologies under the Green Deal.	Industrial demand, supply disruption risks, strategic autonomy	Fixed list (34 raw materials, 2023 CRM update)	Clean energy, green and digital transitions, strategic industries	Applies multi-sectoral lens. Integrates future demand projections and sustainability factors, including environmental and social dimensions
IEA	Demand-driven methodology with no fixed list. Minerals are assessed based on their relevance to energy transition technologies.	Supply risk and economic importance to clean energy systems	Dynamic (26 core minerals analysed regularly)	Clean energy technologies (solar, wind, EVs, etc.)	Classifies minerals along a continuum of criticality. Uses tools like the Critical Minerals Data Explorer to assess 37 minerals under multiple scenarios.
OECD	No formal list or definition. Provides governance tools and transparency indicators.	Export restrictions, policy risk, supply chain governance	Not applicable	Trade regulation, responsible sourcing, global risk exposure	Tracks export restrictions on 65 raw materials. Offers Due Diligence Guidance on conflict minerals. Focuses on long-term structural risks and supply governance.
USGS	Legal definition from the U.S. Energy Act of 2020. Assessment based on strategic importance and vulnerability to disruption.	Supply risk, economic importance, U.S. import reliance	Fixed list (50 critical minerals, reviewed periodically)	Economic security, defense, energy and high-tech sectors	Combines quantitative indicators (e.g., production share, import dependence) with expert judgement. Excludes widely available commodities like copper and aluminium.
World Bank	Demand-driven framework based on projected mineral intensity across clean energy technologies.	Projected demand growth, cross-technology relevance	No list; 4 categories based on expected impact	Mineral needs for solar, wind, storage, etc.	Classifies minerals by sectoral importance: high-impact, medium-impact, cross-cutting. Focuses on forward-looking demand under climate scenarios.
WTO – ADB	Trade-based mapping of mineral-related products using existing national and international lists.	Trade exposure and value chain positioning	No harmonized list; about 250 HS-coded products (raw, intermediate, finished)	Global trade in energy transition materials	Focuses on trade flows and product stages, not criticality per se. Valuable for understanding supply chain stages and export composition.

Sources: UNCTAD mapping based on -—
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Bringing a developing economy perspective to critical minerals

Emerging academic research emphasizes that mineral criticality is context-dependent, shaped by national priorities, capacities and development goals rather than being an inherent or fixed property. Most existing frameworks reflect the perspectives of high-income importing countries, focusing on supply risks and economic importance -—
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For instance, Indonesia restricts exports of unprocessed nickel to boost local processing and manufacturing, while Chile is developing public-private partnerships to manage its lithium industry more effectively. These cases highlight the need for frameworks that consider a country’s ability to move up the value chain, through processing or advanced manufacturing, and its institutional capacity to compete in global markets.

Extending this developmental perspective, -—
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The Africa Green Minerals Strategy underscores the importance of using mineral resources to drive domestic value addition, job creation and regional industrialization, moving beyond Africa’s traditional role as a raw material exporter -—
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UNCTAD assessed national and regional strategies related to minerals and their economic role. This revealed a diversity of terminology, including critical minerals, strategic minerals, green minerals and critical raw minerals, depending on context (see table 3).

Table 3. Terminology related to critical minerals differs based on context, country and purpose

Labeling	Countries-Regions
Critical minerals	Argentina, Indonesia, South Africa, Australia, Canada, United Kingdom, United States of America
Critical raw materials	European Union
Green minerals	African Union
Industrial minerals Minerals of strategic economic importance	Argentina
Strategic Minerals	Argentina, Brazil, China, Colombia, India, Indonesia

Source: UNCTAD mapping based on Ministerio de Economía, Argentina -—
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Countries define and communicate about critical minerals differently, with some publishing strategies (e.g., EU or the United Kingdom) or acts (e.g., Argentina and Brazil), and others offering preliminary assessments (e.g., Colombia and Indonesia). An analysis of 13 countries and regions reveals eight factors for assessing how critical a mineral is for: the economy, energy transition, industry, infrastructure, international trade, security, supply chains and technology, and these can be disaggregated further into their sub-factors (see annex 3.).

Developing economies’ assessments of critical minerals are more varied, often focusing on inputs for domestic industries and national security. Supply risk is the most cited criterion overall, mentioned by eight of thirteen countries or regions, universally by developed economies, but only by one-third of developing ones. Developing economies also highlight criteria such as food security, defense, industrial development, employment and comparative advantage. They place particular emphasis on the role of minerals in generating government revenue and foreign exchange.

In contrast, developed economies uniquely emphasize maintaining supply chains, international trade and economic stability. They also consider alternative sourcing, recycling and substitution options. Only half of the countries explicitly reference the energy transition, digital economy or technology in their definitions, though most strategies are implicitly linked to these goals.

A more inclusive understanding of critical minerals can reflect diverse economic structures, such as the importance of agriculture and food security, and account for mineral endowments, market concentration and fiscal dependence, especially in resource-rich developing countries.

While there is overlap in mineral lists, developing economies often include gold and iron ore, excluded from most developed country lists due to their large, liquid markets. Their inclusion reflects their fiscal and developmental importance in the global South.

What is critical today might not be tomorrow

UNCTAD’s classification of critical minerals aims to be dynamic. Minerals like lithium and cobalt have become essential due to their role in battery production, with demand expected to rise sharply by 2040 -—
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Geopolitical shifts, trade tensions and supply disruptions also influence mineral criticality. This calls for adaptable strategies in resource management and international cooperation. Minerals represent both risks and opportunities, for industrialization, green growth and trade diversification.

However, several challenges limit countries’ ability to assess and benefit from their mineral resources. A key issue is the lack of specific trade data for informed policy action. HS codes often group minerals into broad categories, and this is compounded by missing or inconsistent trade data. These gaps hinder efforts to monitor trade, assess risks and design effective policies. As critical minerals gain importance, improving detailed trade data by means of capacity building becomes more urgent.

Future work could further explore the priorities of developing economies, incorporating broader criteria aligned with their development needs. This includes integrating environmental and social dimensions, such as recycling potential, responsible sourcing and early circular economy practices. In addition, the list of critical minerals should remain adaptable to reflect emerging technologies, sectoral shifts and evolving development goals. Improving the granularity of trade classifications, particularly through engagement with the World Customs Organization on HS code revisions, is essential to better capture mineral processing stages and product differentiation. This would enable expanding analysis to finished goods and enhancing trade data quality through cooperation with customs and national statistical offices. Country case studies could help to deepen the understanding of value creation. In the future, UNCTAD’s could integrate greenfield and firm-level investment data as a complementary source for information on production alongside trade data.

Finally, the UNCTAD16 intergovernmental meeting offers a platform for member States to discuss evolving priorities and provide input on analytical needs based on national goals and technological trends. UNCTAD’s current list of critical-strategic minerals is a starting point. It is designed to evolve, guided by a multidimensional approach that reflects global relevance and development needs, especially for energy, digital and industrial transitions.

Annexes

Annex 1. UNCTAD’s approach to identifying critical minerals

To develop a comprehensive and inclusive list of critical minerals relevant to global energy transition and industrial needs and tailored to reflect the priorities of both developing and developed economies, UNCTAD undertook a systematic, multi-step exercise. The process was designed to be transparent, data-driven and grounded in expert input. The list was built from the ground up, starting with national and regional priorities, refined through expert consultations, and validated using trade data. A key innovation is the systematic mapping of each mineral to HS codes, enabling robust trade analysis and policy relevance. The methodology involved reviewing national and institutional critical mineral lists, assessing country strategies, and refining selections through expert feedback and trade indicators. The final output, a harmonized list of 60 critical minerals, mapped by 499 HS codes, supports trade policy analysis while accounting for global development priorities. Below is an overview of the key steps in UNCTAD’s methodology.

Step 1: Review of country, regional and institutional critical mineral lists

UNCTAD compiled critical mineral lists from national, regional and international sources, including Argentina, Brazil, Canada, China, India, Japan and the United States; regional bodies like the African Union and European Union; and international organizations including the IEA, OECD, IRENA, WTO-ADB, World Bank and ESCWA.

Step 2: Assessment of country strategies and criteria for critical minerals

UNCTAD carried out an assessment of countries’ strategies and criteria for identifying critical minerals. This provided a validation to the selection of minerals to be included on UNCTAD’s comprehensive list, intended to ensure inclusive consideration of minerals that are critical for both developed and developing economies. The review assessed a sample of strategic documents and how they approached critical minerals, including in African Union, Argentina, Australia, Brazil, Canada, China, Colombia, European Union, India, Indonesia, South Africa, United Kingdom and the United States of America.

Step 3. Selection of a list of critical minerals

UNCTAD developed a reference list of 85 critical raw and semi-processed materials based on mapped classifications and country-level strategic priorities. The selection reflects the needs of both developing and developed economies, with a focus on clean energy, digitalization and industrial growth. Expert judgment, trade exposure and targeted data were used. The list adopts an inclusive approach but includes instances of double counting, such as listing REEs as a group alongside individual elements (e.g., dysprosium, neodymium), and similarly for PMG.

Step 4: HS code identification using HS 2022

Each mineral was matched to appropriate 6-digit HS codes based on traded forms (e.g., ores, refined metals). Care was taken to avoid misclassification, especially for mixed-use products. Some materials were grouped due to classification challenges, resulting in a final list of 60 critical minerals, covering raw and semi-processed minerals. Special attention was paid to distinguishing between pure substances and downstream or mixed-use products.

Step 5. Backward correspondence across HS revisions

To enable historical trade analysis, HS 2022 codes were mapped to earlier versions (HS 2017, 2012, 2007, 2002) using official tables and expert input. This ensured consistency across countries and time periods.

Step 6. Trade data integration and validation

Mapped HS codes were used to extract trade data from UN Comtrade. Volumes and values were validated through cross-checks, producing a consistent dataset for analyzing trade flows and dependencies.

Step 7. Grouping minerals by energy transition relevance

Minerals were categorized into three groups:

• Required for the energy transition (27)
• Relevant to the energy transition (10)
• Other critical minerals (23)

This classification integrates global frameworks (e.g., IEA, World Bank) and regional priorities (e.g., ESCWA), including UNCTAD expertise. The grouping supports targeted analysis of materials essential to green technologies like electric vehicles, solar panels and hydrogen systems.

Step 8. Classifying minerals by criticality status

After compiling the relevant trade data, we calculated indicators based on HS codes. We ultimately focused on two key indicators:

1. Revealed Comparative Advantage
2. Trade Concentration Index (for both exports and imports)

Using these indicators, the scores for each mineral across different regions were generated. Based on these scores, minerals have been categorized into three levels of criticality: High, Moderate and Low. Additional indicators, such as dependency ratios, can be considered to further refine the assessment.

Annex 2. Full UNCTAD list (mapped to HS Codes)

Figure 11. Mapping UNCTAD’s list of critical minerals

Hierarchical breakdown of 6-digit HS 2022 codes for UNCTAD-listed critical minerals

Note: The complete UNCTAD's HS code classification for critical minerals, including revisions from 2002 to 2022, is available for download.

Annex 3. Comparative overview of national and regional approaches to Critical Minerals assessment

Table 4. Eight factors of national and regional critical mineral assessments

Policy Theme	Sub-Category (Factor)	Developed Countries	Developing Countries
A. Economy	Consumption	European Union, United Kingdom	Colombia
	Digital Economy	Canada	South Africa
	Employment		Argentina, Colombia
	Importance	Australia	India, Indonesia
	Resource availability	Canada	Colombia, India, Indonesia
	Value addition	European Union, United Kingdom	Argentina, Indonesia
B. Energy Transition	Inputs	Canada	African Union, Colombia, South Africa
C. Industry	Availability of processing technology		Indonesia
	Development		African Union, Argentina, China
	Inputs	United States of America	African Union, Argentina, Brazil, Indonesia
D. Infrastructure	Development		Colombia
E. International Trade	Comparative advantage		Argentina, Brazil
	Demand of industrialized countries		Argentina
	Government revenue generation		Argentina, Indonesia
	Import substitution		Argentina
	Increase foreign exchange reserves		Argentina, Indonesia
	Market control		Indonesia
	Positioning as strategic partner	Canada
	Reliance on imports	European Union, United Kingdom	Argentina, India
	Surplus in trade balance		Brazil
F. Security	Defense		China, India, Indonesia
	Economic security	Canada, USA	China
	Food Security		Argentina, Colombia, India
	National security	Australia, Canada, USA
G. Supply Chains	Alternative sourcing	United Kingdom
	Availability of Substitutes	European Union
	Concentration of sourcing	European Union, United Kingdom
	Lack of substitutes		Argentina, Indonesia
	Recycling	European Union, United Kingdom
	Supply risk	Australia, Canada, European Union, United Kingdom, USA	Argentina, India, Indonesia
H. Technology	Inputs	Australia	Brazil, Indonesia

Source: UNCTAD mapping based on Ministerio de Economía, Argentina -—
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Note: The strategies of Colombia and Indonesia are preliminary. All labels are included in this table.

Notes

1. Although the term ‘minerals’ is used throughout for simplicity, the analysis covers both minerals and metals. For instance, it refers to minerals that are economically important and face a high risk of supply disruption. Many of these minerals are sources of critical metals, for example, lithium, cobalt, nickel and REEs are all classified as critical minerals, and they yield metals that are essential for clean energy technologies, electronics and defense applications. So, while not all metals are considered critical, many critical minerals do produce or contain metals, and the terms are often used together in this strategic context.
2. The estimate refers to total IFFs from all sources, not just those related to trade in critical minerals. These flows include tax evasion, corruption and other illicit activities that drain public resources and undermine development -—
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References

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Gender inequality persists globally, impacting economic participation, education, health, and political empowerment, affecting women’s lives globally. Despite advancements, significant disparities remain. In 2023, UN Women estimated that at the current rate, it will take 286 years to close gender gaps in legal protection, 140 years for women to be represented equally in positions of power and leadership, and 47 years to attain equal representation in national parliaments -—
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—-. Continuing the rate of progress from 2006 to 2023, it will take 169 years to close the economic participation and opportunity gender gap -—
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The UNCTAD ministerial meeting, in Bridgetown, concluded that policies need to go beyond encompassing a gender perspective and actively promote the inclusion and empowerment of women and youth -—
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The indicators are calculated based on data derived from international databases include employment and earnings by sex in tradable sectors, trade-intensive and trade-dependent industries. These data enable for the first-time to gain insights about international trade from a gender perspective across the world.

Globally, women employees are underrepresented in tradable sectors, representing only 36 per cent of persons employed in tradable sectors in developed and 39 per cent in developing economies. However, their employment in the trade of services has increased at a faster rate than men’s, highlighting the potential for trade in services to enhance women's economic empowerment, particularly in regions like Africa, Asia, and Oceania. Women’s contribution to domestic value added in exports still lags significantly behind men’s, though it is higher in services exports compared to agriculture and industry. Understanding these emerging patterns to inform effective policy actions will require further country-specific analyses to identify drivers and barriers to women’s participation in high value-added sectors unique to each economy.

Leveraging trade as a catalyst for economic empowerment

Trade plays a crucial role in economic growth and poverty reduction. Thus, inequalities in trade participation and in the distribution of benefits significantly impact people’s lives. In the last three decades, the global poverty rate fell from 38 per cent in 1990 to just below 9 per cent in 2022 -—
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Furthermore, recently these trends got disrupted by the pandemic, war and crises. An estimated 23 million more people were living in extreme poverty in 2022 compared to 2019 -—
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UNCTAD's initial analysis reveals an association between trade openness and women’s economic empowerment. According to the GGPI and WEI indices less than 1 per cent of women and girls reside in a country with high women’s empowerment and gender parity (figure 1), mainly in Australia, Belgium, Denmark, Iceland, Norway, and Sweden, while developing economies, such as Iran, Iraq, Lebanon and Pakistan in Asia, and Benin and Nigeria in Africa lag behind. While the impact of trade liberalization on gender inequality depends on multiple factors, research shows several channels by which trade policy can improve gender equality in wages and employment -—
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Figure 1. Developed economies generally exhibit greater openness to trade together with enhanced women’s empowerment and gender equality

Source: UNCTAD calculations based on -—
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Note: GGPI and WEI were published by the UNDP in 2023. Values of GGPI and WEI greater than 0.6 are considered medium parity, and values greater than 0.8 are considered high parity. The UNCTAD’s trade openness index analyzes countries’ economic dependence on exports and imports. The bubble size refers to the trade openness index. Trade values correspond to the sum of exports and imports of goods and services.

While the importance of women’s economic empowerment for closing gender gaps is widely acknowledged, data to enable effective action to close gender gaps remains rare. This lack of data means that gender equality indices continue to limit the focus of economic empowerment on the labour market and political participation -—
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Trade significantly influences employment and business opportunities of women and men, their income, social status, welfare, and equality. Export-oriented industries such as textiles and apparel, often employ a large number of female workers -—
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—-, making up to 33 per cent of the workforce of exporting firms in developing economies, compared with just 24 per cent of non-exporting firms -—
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However, trade can also exacerbate existing gender inequalities, particularly if accompanying trade policies do not include measures to address social and economic inequalities. Women working in global value chains often occupy low-skill and non-managerial jobs, despite being more likely to hold formal jobs -—
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New data linking initiatives to bridge the gap

Despite the urgent need to analyse trade from a gender perspective, only a few countries regularly compile sex-disaggregated indicators linked to international trade, and some countries do so on an ad hoc basis. For example, Finland and New Zealand linked such data to find that women were underrepresented in international trade both as employees and business owners (See National efforts to produce statistics on gender and trade). Some countries have also collected additional data by specialized surveys on trade and gender, such as Chile -—
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—- and some international organizations, like the World Bank, support countries by carrying out such surveys. These can provide more in-depth information on trade barriers or informal cross-border trade to inform policy but may be costly to carry out.

Prompted by the Buenos Aires declaration -—
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—- and collaboration with pioneering countries and organizations, UNCTAD developed the ‘Conceptual Framework for the Measurement of Gender Equality in Trade' -—
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—- released last year and the 2024 release of a global analytical dataset on gender equality in trade, represent significant strides toward addressing the data gaps with countries and partners (See UNCTAD in Action: Gender and Trade). These indicators and the related analysis are intended to inform more gender-inclusive trade policies.

Women continue to be underrepresented in trade across regions

Women’s underrepresentation in tradable sectors is evident across regions, as indicated by UNCTAD’s data (figure 2). 36 per cent of employees in tradable sectors are women in developed economies compared to 39 per cent in developing economies. Notably, African countries exhibit the lowest gender employment gap in tradable sectors, with women comprising 42 per cent of employees compared to 58 per cent for men.

Figure 2. Women employees are underrepresented in tradable sectors across regions, 2022

Percentage

Source: UNCTAD calculations based on -—
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Notes: Classification of tradable and non-tradable sectors is derived based on -—
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—-. Tradable sectors include agriculture (ISIC Rev. 4 - A), industry (B, C, D, E), transport, information and communication (H, J), financial and insurance activities (K), and other services (R,S,T,U). Non-tradable sectors include construction, distributive trade, repairs, accommodation, food services activities (F, G, I), real estate activities (L), business services (M, N), and public administration (O, P, Q). Transportation is also included among tradable sectors, because international transport is considered to be a key enabler of international trade -—
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Women face barriers to trade participation, such as unequal access to resources, limited training opportunities, and cultural constraints. UNCTAD’s studies also highlight the disproportionate burden of care and household work and women’s higher participation in low productivity work are major constraints to women's full economic empowerment -—
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Analysis of OECD countries revealed that 11 per cent of women-led firms export internationally compared to 19 per cent of men-led firms. However, once involved in exports, women-led firms do so to a similar or larger number of countries than firms led by men, suggesting the particular importance of policies aimed at removing entry barriers for women entrepreneurs -—
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—-. For instance, legal and regulatory barriers, such as restrictions on property ownership or business activities and travel, limit women’s entrepreneurship. The Women, Business, and the Law Index indicates that women have less than two-thirds of the legal rights available to men, particularly in entrepreneurship -—
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—-. Gender-blind trade policies may exacerbate these inequalities, also in access to market information and trade networks, hindering women’s ability to participate effectively in trade.

Services trade offers increasing potential for women’s economic empowerment

Women are concentrated in the services sector in all regions. Figure 3 shows a rising share of services as an employer of both women and men from 1991 to 2022 in all regions. The shift to services is also mirrored in international trade as growth of trade in services is surpassing that of goods since 2011 -—
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—-. Developing economies in Africa, Asia and Oceania have potential for growth in services with opportunities for expanding women’s contribution to the economy.

Figure 3. Women's employment in services increased at a faster rate than men's since 1991

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Source: UNCTAD calculations based on -—
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In manufacturing, high shares of female employment typically align with whether an industry is capital-intensive (technology-dependent) or labour-intensive. Low technology-intensive industries which typically employ more women (termed feminization of labour), such as food and beverages and textiles, often face higher tariffs on imported inputs than other industries. Such tariffs can elevate trade costs and hinder the competitiveness of sectors that offer employment opportunities for women -—
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—-. For instance, data show that the United Republic of Tanzania exhibited a high share of female employees, 54 per cent in 2020, in its low technology-intensive industries, such as food, beverages and textiles. In contrast, the share of women in medium-high and high technology-intensive sectors, was substantially lower at 10 per cent in 2020. Another example is Cambodia, where female share in low-technology industries, such as wearing apparel and leather products, was high at 67 per cent in 2021, compared to medium-high and high technology-intensive industries where female share of labour was 48 per cent in the same year (figure 4).

Figure 4. Share of female employees is higher in low technology-intensive manufacturing industries compared to more capital-intensive industries

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Note: The year for the reported employment varies from 2009 to the latest available. Technology classification is based on R&D expenditure incurred in the production of manufactured goods -—
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Women produce 20-40 per cent of total export value depending on region

Women’s contributions to domestic value added in gross exports lag behind men’s across all regions. This indicates that women’s contribution to the production of goods and services exported worldwide still trails that of men (figure 5). For example, in 2020 women’s largest contribution to domestic value added in gross exports was estimated at 40 per cent in developed economies, while in Africa women only produced one fourth of the total generated exported value. In developing Americas and developing Asia and Oceania, men’s contributions were nearly double that of female generated domestic value added in gross exports.

Figure 5. Women’s contributions to domestic value added in gross exports lag behind men’s across all regions, 2020

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Source: UNCTAD calculation based on -—
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Note: Aggregated figures are based on data on employment and trade in value added for 76 economies. This analysis assumes that there are no differences in gender distribution between exporting and non-exporting firms. The proportions of male and female contributions to domestic value added are calculated assuming homogeneity in labour intensity, skills, etc., thereby stating that women represent a comparable share of value added to their proportion in employment.

Analysis by sectors reveals an intriguing pattern: women’s domestic value added is higher in services exports compared to agriculture and industry in most regions (figure 6). This suggests that trade in services offers greater opportunities for women to contribute to exports in developed economies, developing Africa and the Americas. For instance, in developed economies women’s domestic value added in services nearly equals men’s, whereas their contribution to agriculture and industry exports is approximately one third of that of men’s.

Figure 6. In most regions, women’s domestic value added is higher in services gross exports compared to agriculture and industry, 2020

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Source: UNCTAD calculation based on -—
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Note: Aggregated figures are based on data on employment and trade in value added for 76 economies. This analysis assumes that there are no differences in gender distribution between exporting and non-exporting firms. The proportions of male and female contributions to domestic value added are calculated assuming homogeneity in labour intensity, skills, etc., thereby stating that women represent a comparable share of value added to their proportion in employment.

To further explore women’s contribution to higher value-added exports, the analysis examines exports of goods and services that add more than 50 per cent to the domestic value added in exports. Figure 7 shows that women's share of employment is higher in economies where services exports contribute more than 50 per cent to the domestic value added, compared to economies where goods exports contribute more than 50 per cent. This supports WTO’s argument that services trade may benefit women in the labour market, as services sectors exhibit greater gender balance than manufacturing or mining -—
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Figure 7. Economies with high exported value added from services show greater female employment rates compared to goods-producing industries

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Note: The year for the reported employment varies from 2008 to 2020 based on the latest available with most data reported for 2019 or later. Country data for high-exported value added – i.e. sectors contributing more than 50% to the domestic value added in gross exports. Sectors are aggregated into two groups: goods (primary goods and manufacturers) and services.

While UNCTAD’s first set of trade and gender indicators show that women are still underrepresented in tradable sectors and contribute less to creating domestic value added content in exports across regions, a sectoral analysis reveals opportunities to catalyse trade for women’s economic empowerment. Trade in services presents an opportunity for women to contribute to the growth of exports in most regions. Nevertheless, a further in-depth analysis can help to identify specific drivers and bottlenecks of women’s contribution to high-value sectors unique to each economy. This approach requires country-level linking of micro-data to enable more accurate insights to inform policy action, such as the following examples of UNCTAD’s collaboration with Finland and Georgia.

Women’s contribution to domestic value-added exports in Finland

A small open economy like Finland benefits from globalization and foreign trade significantly. The share of exports in GDP is high up to 30 per cent, but the benefits of trade are unevenly distributed between businesses, employees and consumers -—
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—-. Statistics show a high concentration of exports in the largest enterprises, and higher salaries paid by trading firms compared to others. Importantly, the study showed that women work less often in trading companies, and only one fifth of businesses engaged in exports are female owned.

Gender gap widens as firm size increases.

Statistics Finland releases annually experimental statistics on trade in value added. These can be compiled by linking existing data sources without additional data collection. An analysis of domestic value added embodied in exports, whether through direct or indirect export dependencies, reveals insights into the role of firms and export-supported jobs (figure 8). While larger enterprises in Finland provide many jobs supported by exports, the proportion of jobs that are export-supported is smaller in the largest enterprises, since they often engage with smaller intermediaries to produce intermediate goods for them.³

The global value chain analysis reveals that in Finland women’s share of jobs supported by exports is 32 per cent compared with 38 per cent for men. Interestingly, while export-supported jobs in micro-firms are almost equally distributed between women (20 per cent) and men (21 per cent), the gender gap widens as firm size increases. In large firms, 30 per cent of women’s jobs are supported by exports compared to 43 per cent of men’s jobs.

Figure 8. Finland’s women’s contribution to domestic value added is lower than men’s contribution with widening gap in larger firms, 2021

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Women’s employment, wages and entrepreneurship in trade in Georgia

Gender aspects of trade statistics become very relevant to addressing issues related to welfare and equality. There’s high interest from state institutions, international partners and non-governmental organizations,Gogita Todradze, executive director of Georgia’s National Statistics Office

Georgia was the inaugural pilot country supported by UNECE and UNCTAD in developing sex-disaggregated trade indicators through microdata linking (See UNCTAD in Action: Gender and Trade).⁴ This involved linking annual goods trade data with key sex-disaggregated variables from business statistics and the structure of earnings survey. The linked company-employee data represented over 85 per cent of both exports and imports value in Georgia.

High-skill female workers face less gender inequalities.

The study revealed gender gaps in employment and wages. Women-to-men employment ratios in trading companies ranged from 57 to 64 per cent over the five-year period, while the gender pay gap fluctuated between 30 and 35 per cent. Further analysis by skill levels indicated that high-skill workers had the lowest gender pay gap (18 per cent for importers, 31 per cent for two-way traders), while the gaps for managers and low-skill workers were between 38 and 45 per cent. Gender indicators disaggregated by skill levels highlighted that, generally, high skilled female workers experienced less disparity in trade, both in their employment and pay (figures 9 and 10). Higher education levels could protect women from some gender inequalities.

Figure 9. Gender employment gap in trading companies is lowest among high-skilled workers in Georgia, 2017

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Note: Two-way traders are defined as firms involved in both exports and imports of goods.

Figure 10. Gender pay gap is the highest among low-skilled workers in trading enterprises in Georgia, 2017

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Note: Two-way traders are defined as firms involved in both exports and imports of goods.

The data linking exercise also facilitated the analysis of female and male entrepreneurs in trade. It revealed that men own trading companies five times more often than women (figure 11). Drawing on these data insights, Georgia plans to include gender-in-trade statistics in its regular statistical production to inform design of policies that encourage women entrepreneurship, as well as increase job opportunities and wages for women in international trade.

Figure 11. In Georgia, men own five times more trading companies than women, 2017

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Note: Two-way traders are defined as firms involved in both exports and imports of goods.

More inclusive economies reach higher productive capacities

Enhancing a country’s productive capacities — comprising of human and natural capital, energy, transport and ICT capacities, well-functioning institutions and private sector, and structural change — fuels inclusive economic growth and resilience. Investments in productive capacities yield immediate economic benefits but also lay the groundwork for sustained growth by creating jobs, enhancing skills, and promoting equitable development. Generally, the propensity to build productive capacities is higher in countries with well-crafted and informed economic, trade, industrial, as well as science and technology policies -—
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The strong relationship between inclusive growth and productive capacities is illustrated in figure 12. It also shows that economies with higher PCI scores primarily consist of developed economies that rank high on the IGI equality dimension, which measures labour and political participation, income distribution, education, and gender distribution of social reproduction. Among developing economies, Asia and Oceania demonstrate higher average equality scores, whereas African economies exhibit significant diversity in equality, suggesting that women’s productive capacities have not been optimally developed and utilized -—
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Figure 12. Developed economies reveal higher PCI and IGI equality scores in 2021

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Note: The figure compares overall PCI scores (x-axis) and IGI equality scores (y-axis). The size of the bubbles refers to the overall IGI scores. IGI is composed of four dimensions – economy, living conditions, equality and environment.

Domestic value added in gross exports is closely linked to productive capacities because it reflects the extent to which a country's domestic resources, capabilities and production processes contribute to the final goods and services that are exported. In 2020, total value added, as measured by domestic value added in gross exports, is estimated at almost $15 trillion globally, with 3 per cent generated in agriculture, 56 per cent in industry and 42 per cent in services -—
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Figure 13. Developed economies reveal higher PCI scores and higher contribution of women to domestic value added in gross exports in services

Source: UNCTAD calculation based on -—
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Note: The year for the reported employment varies from 2015 to 2020 based on the latest available. Country data for high-exported value added – i.e. sectors contributing more than 50% to the domestic value added in gross exports. Sectors are aggregated into two groups: goods (primary goods and manufacturers) and services.

While a clear division between developed and developing economies exists in their productive capacities, some outliers, particularly in the service sector, warrant examination. To understand why some economies follow a different path, PCA was used to assess the main factors affecting gender inequality in trade. This analysis, based on 19 indicators (see table 1) for 62 economies available from the OECD TiVA database -—
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The analysis identifies four principal components, namely education and social conditions (PC1), trade and labour participation (PC2) and political empowerment and participation in decision-making (PC3 and PC4) which explain 71 per cent of the total variance of gender equality. The first component mostly represents preconditions for trade participation for women and men: motivations, aspirations, resources, and constraints. The second points to their degree of involvement in trade. The third one stands for political empowerment and participation in various levels of decision-making.

Figure 14. Developed economies reveal higher gender equality in education and social conditions and in trade participation in contrast to developing economies

Source: Data for the analysis is collected from multiple sources, UNCTAD Gender-in-trade indicators -—
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Note: The figure shows gender equality in education and social conditions (PC1) on the x-axis and gender equality in trade and labour participation (PC2) on the y-axis.

Developed economies stand out as a relatively homogenous group with higher gender equality in education and social conditions and in trade participation with a stark contrast to developing economies (figure 14). They also boast better social conditions and higher women’s empowerment and wages.

Various patterns of gender equality in trade emerge across different countries. In a cluster including Cambodia, Lao PDR, Peru and Viet Nam, women participate significantly in trade, particularly in industries and sectors heavily reliant on trade. Conversely, a group of economies represented on the right side of figure 14 (Bangladesh, Egypt, Jordan, India, Pakistan and Tunisia) faces unfavourable conditions for women’s economic participation, resulting in limited benefits from trade. Nordic and Benelux countries share similarities in high levels of women’s empowerment, institutional representation, education, and wages, grouping them together. Similarly, Eastern European economies demonstrate commonalities in high female labour force and trade participation. These diverse patterns highlight the complex interplay between gender equality, trade participation, and economic and social conditions across different regions.

Table 1. Summary of gender-relevant indicators used for the PCA analysis

Component	Gender equality dimension	Indicator
PC 1	Education and social conditions	Restricted access to productive and financial assets index (SIGI)
		Adolescent birth rate (births per 1,000 women ages 15–19)
		Discrimination in the family index (SIGI)
		Ever-partnered women and girls subjected to physical and/or sexual violence by a current or former intimate partner in the previous 12 months (% ages 15–49)
		Labour force participation rate among prime-working-age individuals who are living in a household comprising a couple and at least one child under age 6, female (% ages 25–54)
		Population with completed secondary education or higher, female (% ages 25 and older)
		Restricted physical integrity index (SIGI)
		Women of reproductive age whose need for family planning is satisfied with modern methods (% ages 15–49)
		Youth not in education, employment or training, female (% ages 15–24)
PC 2	Trade and labour participation	Average monthly earnings of female employees in high exported value added industries (2017 PPP $)
		Average monthly earnings of female employees in tradable sectors (2017 PPP $)
		Share of female employees in high exported value added in industries (%)
		Share of female employees in high export-intensive industries (%)
		Share of female employees in top 5 export-intensive industries (country level) (%)
		Share of female employees in tradable sectors (%)
PC 3 & 4	Political empowerment and participation in decision-making	Restricted civil liberties index (SIGI)
		Share of managerial positions held by women (%)
		Share of seats held by women, local governments (%)
		Share of seats held by women, parliament (%)

Source: Data for the analysis is collected from multiple sources, UNCTAD Gender-in-trade indicators -—
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Note: Indicators are grouped into gender equality dimensions based on the PCA results.

Trade policy as a driving force to bridge gender inequality gaps

Gender equality amplifies human progress, economic growth, and social development. Governments play a crucial role by allocating funds for essential services, investing in education, social support and legal reforms shaping policies and taking actions to enhance economic empowerment, and combatting gender-based barriers and violence.

UNCTAD, jointly with UN Women -—
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—-.⁵ The total spending need is substantial, at $6.4 trillion per year, representing 21 per cent of the collective GDPs of these economies. Per person, the total cost is calculated at $1 383 annually. Notably, SIDS and LDCs face the highest requirements relative to the size of their economies, with 44 and 42 per cent of their GDPs, respectively. However, it is essential to recognize that achieving gender equality yields high synergies with all SDGs. Similar to investments in education, progress towards gender equality can catalyse advancements across various SDGs, such as eradicating poverty, alleviating hunger, and driving socio-economic progress by women’s equal participation in society.

Trade policy is increasingly recognized as a means to address gender disparities and promote inclusive trade. Today, approximately one-fourth of RTAs incorporate gender-related provisions -—
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Incorporating stand-alone gender chapters in trade agreements has enhanced the visibility of gender issues in trade policymaking, especially through requirements to assess progress with agreed indicators. UNCTAD has developed ways to link statistical data to assess the gender impacts of trade agreements, with support by the European Commission -—
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—-. Compared to simple gender provisions, full-fledged gender chapters provide a higher level of detail for cooperation activities and capacity-building; and the institutionalization of monitoring activities. To date, only a handful of countries have signed FTAs with stand-alone gender chapters (table 2).

Data and analysis are key to understanding the complex dynamics essential for achieving more gender equal trade. These dynamics are shaped by various factors, including domestic labour markets, cultural norms, legal frameworks, international markets and economic fluctuations. Such interactions are highly country-specific, what works in one country may not yield results in another.

Table 2. FTAs with gender chapters

Agreements with gender chapters	Type	Year
Chile-Uruguay FTA	Bilateral	2016
Chile-Argentina FTA	Bilateral	2017
Chile-Brazil FTA	Bilateral	2018
Chile-Ecuador FTA	Bilateral	2020
United Kingdom-Japan FTA	Bilateral	2020
Canada-Chile amended FTA	Bilateral	2019
Canada-Israel amended FTA	Bilateral	2019
United Kingdom-Australia FTA	Bilateral	2021
United Kingdom -New Zealand FTA	Bilateral	2021

Source: UNCTAD Trade, Gender and Development Programme

Trade agreements have the potential to significantly advance gender equality, particularly when they recognize and harness the transformative power of gender equality for our societies. Economies with higher productive capacities tend to achieve greater gender equality and more inclusive growth. Gender equality is essential for long-term structural transformation by improving human capital allocation, but sustainable economic development also relies on aggregate demand and macroeconomic policies. While the global dataset offers new insights into gender and trade, linking country-level micro-data is needed to inform effective policy action. Greater involvement of women and civil society representatives in negotiation and monitoring of trade agreements is critical to enhance positive outcomes of trade policies. UNCTAD supports governments in sensitizing trade officials to gender implications, enhancing data and analytical capacities, and carrying out ex ante impact assessments.

★ UNCTAD in Action ★

Gender and Trade

2 200 people trained on UNCTAD’s e-learning courses on trade and gender in 2015-2023.

Since 2015, UNCTAD’s e-learning courses on trade and gender have addressed the knowledge gap about how gender and trade interlink, and how trade policies can contribute to reducing gender inequalities, targeting especially developing and least developed countries. To date, nearly 2 200 people (62 per cent women) in 154 countries have benefitted from 25 iterations of the online course (figure 15). Participants speak about their experience in this video.

Figure 15. Over 60 per cent of people trained in UNCTAD’s e-courses on trade and gender were from Africa in 2015-2023

Source: UNCTAD Trade, Gender and Development Programme

Six countries compiled new indicators and more than 500 experts were trained.

UNCTAD spearheaded efforts on gender equality in trade statistics following the Buenos Aires Declaration -—
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—- which urged sharing methods and procedures for collecting and analysing gender-focused statistics related to trade. The resulting Conceptual Framework for the Measurement of Gender Equality in Trade -—
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This informed the development of Compilation Guidelines -—
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Table 3. UNCTAD trained more than 500 people in 11 events on gender and trade statistics

Type of workshop	Number of workshops	Total number of participants
Regional workshop	4	302
National workshops	6	188
Interregional training workshop	1	32
Total	11	522

Source: UNDA project “Data and statistics for more gender-responsive trade policies in Africa, the Caucasus and Central Asia”

Increased capacity of over 500 small-scale traders in six countries.

Informal cross-border trade is largely driven by women as one of the few options available to them due to their time constraints, limited access to resources, and lower education levels. Despite their critical role, they often face challenges, such as regulatory barriers, high duties, poor border facilities, weak border governance, corruption and harassment, resulting in minimal benefits from trading.

Small-scale traders also encounter challenges beyond checkpoints, including information gaps on rules, regulations and market demand. Additionally, supply side obstacles such as difficulties in business registration and limited capital resources further impede their success.

To address these barriers, UNCTAD initiated a capacity-building programme for women in small-scale informal cross-border trade. The programme aims to raise awareness of trade rules and customs procedures, enhance entrepreneurial skills (see UNCTAD in Action on Empretec) and facilitate dialogue with border authorities. In 2019-2023, 18 workshops were delivered focusing on trade rules, customs procedures and entrepreneurship at 9 border crossings in Botswana, Kenya, Malawi, Mozambique, Tanzania and Zambia, benefiting 547 cross-border traders, most of which were women (map 1).

Map 1. Over 500 small-scale traders trained on trade procedures and entrepreneurship skills, 2019-2023

Source: UNCTAD Trade, Gender and Development Programme

International treaties and agreements related to gender equality

Numerous international agreements aim to promote gender equality, urging countries to safeguard women’s rights.

Figure 16. Timeline of international treaties and agreements related to gender equality

Source: UNCTAD

The Convention on the Elimination of All Forms of Discrimination Against Women (CEDAW) is a landmark treaty adopted in 1979, obligating signatory states to combat discrimination against women in various fields, including politics, law, employment, education, and healthcare -—
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In the realm of trade, the Addis Ababa Action Agenda -—
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Notes

1. For instance, UNCTAD analysis of three major global gender equality indices (The Global Gender Gap Index (GGI), The Gender Inequality Index (GII), The Social Institutions and Gender Index (SIGI) revealed that none of them reported indicators related to trade.
2. WEI is comprised of 10 indicators related life and good health (two indicators); education, skill-building and knowledge (two indicators); labour and financial inclusion (two indicators), participation in decision making (three indicators); and freedom from violence (one indicator). GGPI is a composite index that assesses the relative achievements between women and men in four dimensions: life and good health (one indicator); education, skill-building and knowledge (two indicators); labour and financial inclusion (two indicators); and participation in decision making (three indicators). Source: -—
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3. This analysis is made in relation to the size of the producing firms, not exporting firms. When producing goods for exports, large firms typically use intermediate goods, which are either produced by other (smaller) firms domestically or imported.
4. Georgia’s National Statistical Office was the first to take part in the UNDA project titled "Data and statistics for more gender-responsive trade policies in Africa, the Caucasus, and Central Asia".
5. UNCTAD in partnership with UNDESA and UNDP calculated the costs along six key “transition pathways” that can amplify efforts and speed up progress towards the 2030 Agenda for Sustainable Development. In addition to these six pathways, UNCTAD is working with UN Women to estimate the cost of achieving gender equality for certain gender-related SDG indicators.
6. The study covered the following border crossings: Noe-Elubo border (Côte d'Ivoire–Ghana); Afl­ao–Kodjoviakope (Ghana–Togo); Segbe–Kpoglo (Ghana–Togo); Hillacondji–Sanve econdji (Togo–Benin); Seme–Krake (Benin–Nigeria).
7. In Rwanda, informal cross-border trade is defined as transactions in goods between residents and non-residents of the country that are not documented through official customs clearance system and ultimately not included in the official statistics. They constitute exports and imports of goods and exclude smuggled goods; transit goods; goods properly (100 per cent) declared and verified by the customs officials on declaration documents.

References

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The Bridgetown Covenant underlines the importance of “boosting resources, private and public, and domestic and international” and their “effective employment” in delivering on the 2030 Agenda -—
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—-, the UN Secretary-General urged world leaders to come together at the SDG Summit in September 2023 to deliver a Rescue Plan for People and Planet centred around three major breakthroughs: equipping governance and institutions for sustainable and inclusive transformation; prioritizing policies and investments that have multiplier effects across the goals; and securing a surge in SDG financing and an enabling global environment for developing economies. This SDG Pulse In Focus offers analytical, data-driven input to these efforts based on experimental costing of SDG indicators using official statistics.

The 2030 Agenda can be seen as a universal agenda for investment in sustainable development. But progress towards the SDGs is off track and slipping increasingly out of reach. Effective action is hampered by the lack of overall understanding of the financing needs required to achieve the SDGs. It is difficult to align the national budgets, investment and financing flows, or debt relief with the needs for achieving the SDGs when there is no data to guide decisions.

In recent years, approximately 50 countries have estimated the costs of achieving selected SDGs reflecting national priorities based on guidance developed by the Inter-agency Task Force on Financing for Development -—
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—-. These efforts have shown that better data and understanding of the costs can strengthen financing for national sustainable development priorities and feed effectively into national planning. These estimates are, however, tailored for specific national purposes and the global picture of the need for SDG financing remains weak and incomplete.

The 2023 SDG Pulse In Focus discusses experimental cost estimates calculated for 60 countries, including 21 developing economies¹, initially covering 20 SDG indicators including their breakdowns, and spanning across the transition pathways. The study covers more than 45 per cent of the global population. This analysis, however, focuses on developing economies covering over 35 per cent of their total population. The SDG transition pathways on energy, education, jobs and social protection, digitalization, food systems and climate, as communicated by the UN Deputy Secretary-General -—
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—-, are the focus of the analysis. UNCTAD has developed an SDG costing methodology that considers synergies and trade-offs, i.e., the impact of spending on one SDG across the other goals (see Annex I). This method can be used to identify strategies and best practices to maximize the effect of spending on the achievement of the SDGs. When effectively implemented, systematic financing through the pathways can serve as catalysts for change to focus on sustainable solutions and put human rights and equality at the centre.

The work is inspired by the UN Secretary-General’s SDG Stimulus which calls for a massive increase in financing for development, including humanitarian support and climate action, and is part of the related UN-wide efforts, led by UNCTAD with UN DESA and UNDP to pool expertise across the UN and provide effective tools and methods to cost the achievement of SDGs across the transition pathways (Figure 1). That effort is carried out in collaboration with UN Women to ensure gender focus and with IFAD, IEA, ILO, ITU, ESCWA, UNEP, UNESCO, UN-Habitat, UNICEF and other interested partners.

The method used in this study is based on countries’ official statistics on government expenditure by sector² compared to development outcomes measured using countries’ SDG indicator data. Indicators of government effectiveness, political stability and absence of violence and terrorism, as well as FDI (net inflows) were used as control variables. While the input data consist of official statistics, the analysis is based on SFM and as such the results are estimates that include uncertainty (see Annex I). However, we hope that even provisional estimates regarding optimal spending have the potential to inform policies on how to accelerate progress towards SDGs.

While this study focuses on the total costs of achieving SDG transition pathways for the covered SDG indicators, UNCTAD World Investment Report has previously estimated the SDG investment gap to finance capital expenditure -—
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The work presented in this study stems from a UN-wide collaboration -—
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The United Nations has identified the below six transition pathways (Figure 1) to maximize efforts towards achieving the 2030 agenda and to enable translating global commitments to support for country-level implementation.

Figure 1. Six transition pathways to sustainable development include 12 SDGs

Source: UNCTAD mapping based on -—
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The costing exercise covers 20 SDG indicators to date

The aim of this experimental study is to cover SDG indicators included within the six transition pathways with sufficient country coverage and in a way that can be costed. The SDG indicator framework includes 231 unique SDG indicators, of which 163 are classified as tier I -—
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Out of 163 tier I SDG indicators, 109 fall within the transition pathways and 91 of these could in principle be costed at a country level. Indicators that are global in scope, like ‘the number of countries…’, cannot be costed for national achievement, and some are not relevant to all countries globally. Furthermore, even for some tier I indicators country coverage is low, especially for developing economies. Therefore, this first analysis estimates the costs of meeting the target values of the 20 SDG indicators and their breakdowns within the pathways (Table 1).

This study analysed a time series spanning from 2005 to 2021. The indicators spread across nine SDGs among the twelve included in the transition pathways. This analysis could potentially be extended to other SDG indicators and countries following further data collection efforts.

This study applies an SFM method which is valuable for analysing the structure and interactions of producer performance, its determinants and synergies. It is interesting when applied to SDG achievement since countries’ performance is subject to strong influence by government decisions, priorities and expenditures. The public sector plays a central role in steering the pursuit of the 2030 Agenda and seeking financing to that end, especially in health and social sectors, but arguably also in environmental protection. This study incorporates both recurrent and capital expenditures. However, due to the focus on government expenditures, the role of private investment is not fully captured, and it is significant for specific SDGs, like investment in digital technology, and varies by country, e.g., as some countries may have a notable share of privately provided health or education services. This is mitigated by control variables on government effectiveness, political stability and absence of violence and terrorism, and FDI net inflows. Furthermore, the selection of categories included is based on the statistical significance between government expenditure and the related policy measures. The 2023 World Investment Report will complement the picture with its focus on the private investment perspective.

Major increases needed to support social protection and decent jobs

Critical to the advancement of SDGs 1, 2, 3, 4, and 5, this pathway is about pursuing wellbeing, access to essential services, equality and human rights. This exercise considers the costs of achieving the targets for access to basic services (target 1.4), investment in rural infrastructure and agriculture (SDG indicator 2.a.1), education completion and proficiency in reading and mathematics (target 4.1), and reducing child mortality (target 3.2), fighting tuberculosis (SDG indicator 3.3.2) and ensuring access to vaccines (3.b.1). The study also considers the requirements of achieving gender equality in the parliaments and local government (5.5.1) and in time use on unpaid domestic and care work (5.4.1).

From 2023 to 2030, achieving these indicators is estimated to require an average annual per capita cost of US$1 194 (or 13.7 per cent of GDP) in the 21 developing economies covered.⁴ This value illustrates the total financing required to achieve the SDG indicators covered for the social protection and decent jobs pathway and could be funded from various sources of financing.

Achieving the indicators costed⁵ presents unique challenges and opportunities for countries. Afghanistan grapples with elevated neonatal mortality rates for neonatal (SDG indicator 3.2.2) and under-five year-olds (3.2.1), coupled with restricted access to vaccines (3.b.1) and low education results (4.1.1 and 4.1.2). Addressing these challenges in Afghanistan would demand significant yearly spending, approximately 22 per cent of GDP or around US$3.3 billion per year. Some countries, like Armenia, have made commendable progress with near-universal access to basic services (1.4.1) and an impressive vaccination rate (3.b.1) but challenges remain with the high mortality of under-five year-olds (SDG indicator 3.2.1) and the low gender parity in national parliaments (5.5.1). In Azerbaijan, prioritizing education has resulted in high completion rates (SDG indicator 4.1.2), but further improvements are needed in health (3.2.1, 3.2.2, 3.3.2 and 3.b.1) and women's political participation (5.5.1).

Bolivia, along with other countries, faces challenges in health and education results, marked by high under-five year-olds’ mortality (3.2.1) and prevalent tuberculosis (3.3.2). Other countries, such as China and Thailand, have made substantial progress while focused efforts are still needed. China stands out with its robust agriculture orientation of government spending (SDG indicator 2.a.1). Additionally, 94 per cent of China's vast population has access to basic services (1.4.1). Kazakhstan has excelled in education results (4.1.1 and 4.1.2) and vaccination rates (3.b.1). The Maldives, for instance, have achieved complete access to basic services (1.4.1). Thailand, despite challenges, is making promising strides toward eradicating tuberculosis (3.3.2).

It is essential to note that improvements in unpaid care and domestic work participation (SDG indicator 5.4.1) present a long-term challenge for the countries surveyed. For instance, Bolivia's score stands at 1.69,⁶ indicating a significant imbalance in unpaid care responsibilities. Afghanistan, with a score of 8.57, shows a stronger need for considerable efforts in achieving gender equality in unpaid domestic and care work. This goal, crucial for gender equality and economic productivity, may not be attained until after 2030, underscoring the need for persistent focus and strategic actions.

Digitalization is a key driver of progress across the 2030 Agenda

This pathway promotes tech-driven economies, enhancing innovation, job creation, and economic outcomes contributing to SDG 9. Digitalization influences structural change through its impacts on productivity, employment, sectoral linkages and trade -—
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—-, and has therefore important effects across the 2030 Agenda. Digital divides and related skills bias may also hamper progress in structural transformation towards higher value-added activities.

On the digital transition pathway, the two first indicators costed include the manufacturing share of value added in GDP (SDG indicator 9.2.1), and the universal coverage of mobile networks (9.c.1). Their achievement from 2023 to 2030 is estimated to cost US$325 per capita annually (3.4 per cent of GDP) for the 21 developing economies covered.

There are large country differences in progress within this pathway, and in the role of the government therein. For instance, Afghanistan, despite its needs, shows promise with a manufacturing share of value added at 27 per cent of GDP (SDG indicator 9.2.1) and a 57 per cent mobile network coverage (9.c.1). China and Türkiye show strong progress within the digital transition pathway with high manufacturing value added share and near-universal mobile network coverage. Smaller economies like Armenia and Mongolia impress with 100 per cent mobile network coverage and have in practice bridged the digital divide for mobile access.

However, achieving universal mobile network coverage and increasing manufacturing share to over 20 per cent of GDP presents challenges for many countries. Sustained efforts, including bolstering digital literacy, digital infrastructure investment, and creating a favourable environment for innovation and entrepreneurship, are vital for harnessing digital transformation's potential for growth. UNCTAD’s efforts to support entrepreneurs in this regard are discussed in UNCTAD In Action.

Education to unlock innovation for sustainability

The education transition pathway underlines the significance of quality education (SDG 4), empowering individuals with the knowledge and skills essential for sustainable development and related research and development (SDG 9). The study considers the costs of achieving 90 per cent proficiency in reading and mathematics (SDG indicator 4.1.1), 97 per cent education completion rate (4.1.2), higher manufacturing value added share (9.2.1) and universal mobile network coverage (9.c.1) (the latter two are also included in the previous section).

Achieving these SDG indicators as part of the education transition pathway is estimated to cost US$422 per capita annually for the developing economies studied (corresponding to 4.8 per cent of their GDP). Armenia, and Kazakhstan show high achievement levels, with near-universal education completion rates (SDG indicator 4.1.2) and impressive digital inclusion metrics for mobile network coverage (9.c.1). Conversely, countries like Somalia, and Mauritius lag significantly behind on both indicators. According to -—
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—-, it was estimated that the cost of achieving the key SDG 4 targets, including universal pre-primary, primary, and secondary education in low- and lower-middle-income countries by 2030, would amount to US$461 billion on average between 2023 and 2030. These figures highlight the significant financial resources required to meet the targets and emphasize the importance of adequate funding to support the implementation of education initiatives in these countries.

The later discussion on synergies, underlines the important effect on education spending across the 2030 Agenda, including through enhanced human capital, socio-economic development, reduced inequality, higher innovation, and sustainable industrialization.

Food system transition remains challenging for many developing economies

Overall, the food system transition pathway aligns with the zero-hunger goal (SDG 2) and underscores the essential role of agriculture for food security, to improve rural livelihoods, and to bolster resilience. This study considers the cost of developing rural infrastructure and agriculture (SDG indicator 2.a.1), and protecting important sites for terrestrial, freshwater and mountain biodiversity (15.1.2 and 15.4.1). This costing exercise, however, does not consider the achievement of the zero-hunger target and could be extended in the future.

The estimated average annual per capita cost for developing economies to achieve indicators covered for this pathway is US$225. These contribute to enhanced food security, sustainable agricultural practices, mitigating climate change impacts, and conserving biodiversity.

While some countries have made significant strides in agricultural expenditure orientation (SDG indicator 2.a.1) and protected area coverage for biodiversity (15.1.2 and 15.4.1), others are far from the targets. The agriculture orientation index for government expenditures indicates efforts in supporting the agricultural sector (2.a.1). Some countries, like El Salvador and Thailand, have high scores, demonstrating their prioritization of agricultural development. However, there is room for improvement in many countries where the index remains low.

While some countries, like Thailand, have made notable progress in biodiversity conservation (SDG indicators 15.1.2 and 15.4.1), others struggle to reach higher levels of protected area coverage. The food system pathway presents an opportunity for countries to address the complex interplay between food production, climate change, and biodiversity conservation, and is an important area for further efforts to fill data gaps and enable an extended analysis of indicators and countries.

Energy transition has the potential to boost sustainability across sectors

The energy transition pathway aims to enable access to electricity, renewable energy and reduce energy intensity towards SDG 7 and taking urgent action on climate change towards SDG 13. This study considers the cost of achieving universal access to electricity (SDG indicator 7.1.1), increasing the share of renewables (7.2.1) and reducing energy intensity (7.3.1). The cost of taking action to address climate change merits an extended study and has not been considered yet.

Achieving these indicators requires yearly spending of US$586 per capita (6.7 per cent of GDP) in the 21 developing economies considered. Earlier the Sustainable Energy for All consortium -—
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—- estimated that the requirements are in the range of US$1.0–1.2 trillion annually from 2012 to 2030 to achieve universal access to modern energy services, double the global rate of improvement in energy efficiency, and double the share of renewable energy in the global energy mix. This would have required tripling the level of investments in 2010. But as years have gone by, and as we have also seen some setbacks, the annual spending needs have increased. The report estimated that the bulk of the resources would be needed for energy efficiency and renewable energy interventions.

The -—
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—- estimates that the world must rapidly increase annual clean energy investment to reach US$4.5 trillion globally by 2030 in order to achieve universal access and decarbonise the global energy sector consistent with a trajectory to limit global temperature rise to 1.5 degrees by the end of the century. While investments in clean energy are rising rapidly in developed economies and China, the levels have remained flat in developing economies. This would need to climb 7-fold to reach between US$1.4-1.9 trillion by the early 2030s to align with the outcomes of the Paris agreement, according to the IEA and IFC. Concessional financing will be essential to attract the needed private investment to clean energy in these regions, with the required concessional finance estimated to be between 80 and 100 billion in the years around 2030.

Among developing economies studied, ten have achieved universal access to electricity (SDG indicator 7.1.1), while additional efforts are needed in Myanmar (70 per cent) and Somalia (80 per cent) to get closer to 100 per cent -—
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—-. Renewable energy share (7.2.1), on the other hand, is highest in Somalia, Guatemala, Myanmar and Kyrgyzstan, ranging between 30 and 95 per cent. Yet, Uzbekistan, Iran, Kazakhstan, Maldives, and Azerbaijan remain at below 2 per cent share of renewable energy in total final energy consumption. Almost all developing economies studied are far from reaching the energy intensity target. Among the countries assessed, only Mauritius, Afghanistan, and Türkiye have either met or come close to achieving the target. Additional focus on energy efficiency, especially in the transport sector, is crucial, and energy efficiency has synergetic links to other resource systems, like water and food.

US$1 839 per capita needed each year

The overall cost estimate for reaching the selected SDG indicators is US$1 839 per capita for the 21 developing economies. This does not consider the available financing sources or the potential remaining financing gaps, but rather the overall spending needs per year.

The sum of costs for pursuing the selected SDG targets across the pathways, discussed above, and if pursued individually, would be US$2 751 per capita. Considering synergies across goals and pathways, the actual overall cost, US$1 839 per capita, is only two thirds of the separate costs. This speaks to the systemic nature of the 2030 Agenda. While some SDG indicators are overlapping between pathways, even removing them would leave higher costs for individual pathways. This underscores the importance of leveraging synergies between the SDGs and the transition pathways. This chapter will also discuss those synergies in maximizing positive spill over effects and minimizing trade-offs across the 2030 Agenda.

A comparison of several SDG costing studies reveals a large variation in the estimates of the funding needs to achieve the 2030 Agenda. Estimates from different studies range from about US$250 to over US$1 839 per capita annually (see Annex II). The variation does not seem to be driven only by country or SDG coverage, but also by the choices made related to methodology, sector, and data sources. It should also be noted that the financing needs depend on the time left to pursue the SDGs and the current distance from them. The closer we get to 2030, the higher the annual cost to bridge the gap.

Dollars spent with a gender focus yield better results

Financing for SDGs should consider gender perspectives specifically, because if it does not, it risks reinforcing existing gender biases, or leading to otherwise unexpected outcomes. Gender equality and the empowerment of women and girls is recognized under the 2030 Agenda not only as a standalone goal but also as a prerequisite for addressing the world’s most pressing concerns, including poverty, inequality and climate change, and for greater peace and prosperity. Empirical evidence shows a robust connection between greater gender equality and improvements across key economic outcomes, including growth, productivity, and competitiveness -—
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—-. Vital for upholding the rights and dignity of all women and girls, gender equality is also a multiplier and accelerator of human progress, economic growth and development -—
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Gender equality, however, is still a distant goal that the world has yet to achieve. More women and girls live in extreme poverty today than men and boys, and hunger and food insecurity are a routine part of the lived reality of millions of women and girls. By the end of 2022, around 383 million women and girls lived in extreme poverty compared to 368 million men and boys -—
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—-. In 2021, one in three women experienced moderate or severe food insecurity globally, and more than one in ten women and girls aged 15–49 have been subject to sexual and/or physical violence by an intimate partner in the previous year -—
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Targeting financing across the SDGs with a gender focus, including for social protection and decent jobs, is crucial to get the world back on track. UN Women et al. -—
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—- estimates that over 100 million women and girls could be lifted out of poverty if governments were to employ a comprehensive strategy aimed at improving access to education and family planning, fair and equal wages, and expanding social transfers. Moreover, the analysis presented in the SDG Pulse In Focus shows a synergistic relationship between government spending on key sectors such as agriculture, transportation, energy and housing to accelerate progress towards gender equality.

According to this study, equal representation of women and men in parliaments and local governments and in unpaid domestic and care work would be attainable by 2034 for 50 per cent of the developing economies included in this study and, with a few exceptions for the 39 developed economies, with the right spending and policy mix. In agriculture, for example, support for women’s access to and control over resources can boost progress on SDG 2 to eradicate hunger in addition to SDG 5 on gender equality. Similarly, public transportation and housing are essential for improving lives and the wellbeing of those left furthest behind, especially the estimated 560 million women and girls living in slum settings around the world -—
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Efforts to develop sustainable agriculture and clean energy technologies⁷, including modern cooking stoves, can reduce women’s unpaid domestic work burden -—
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—-. Among developed economies, the model points to many different ways to optimize government spending to boost progress towards target 5.4 on the value of unpaid work and target 4.2 on pre-primary education, including the synergies of spending on housing and health.⁸ Spending on social protection, including maternity benefits, parental leave and childcare subsidies are key drivers of accelerated progress on target 5.5 to ensure women’s full and effective participation and equal opportunities in political, economic and public life among developed economies in the sample.⁹ Interestingly, the synergistic relationship of spending on agriculture and housing appeared more effective to advance female political empowerment in developing economies.¹⁰

While having a gender lens in designing stimulus packages is important, so is a commitment to stable and consistent spending on gender equality over time. More efforts are needed to track resource flows in support of gender equality and women’s empowerment in countries. In 2021, only one in every four countries had such monitoring in place. However, translating resource flows into systems change is crucial for sustainable outcomes -—
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—-. These findings reaffirm the importance of developing gender-sensitive tools to support decision-makers in identifying priorities for accelerated and inclusive progress towards the 2030 Agenda.

Optimizing spending - more with less and sooner?

The above cost estimates are based on an analysis of two scenarios for spending on SDGs. Business-as-usual, BAUS, assumes that the current spending trajectory continues. We arrive at the costs of achieving the targets without any reorientation. This means the costs may be high, and fewer goals are achieved with the same cost. In the optimal scenario, OS, we consider the best practice identified by the SFM. This methodology is useful in analysing producer performance and investigating its determinants -—
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—-, and can provide useful insights on best practices to increase efficiency and achieve SDGs with less costs. It helps to determine optimal growth rates for sectoral spending. The cost estimates discussed above in this chapter are based on the OS scenario.

With a strategic reallocation of sectoral spending, more countries can achieve SDGs sooner with less costs. Figure 2 shows the number of countries achieving the selected SDG indicators by 2030, and how their number increases from the BAUS to the OS. Certain SDG indicators are likelier to be achieved than others, namely those located on the right of the figure. For example, 17 of the 21 developing economies analysed are likely to achieve the targets for under-five and neo-natal mortality rates (SDG indicators 3.2.1 and 3.2.2) in the BAUS option, and up to two countries more in the OS scenario. Universal access to basic services (1.4.1) is challenging as only six countries will achieve it by 2030 unless OS solutions are found which would enable 19 countries to reach the target. Strategic allocation of investment is particularly important for achieving universal vaccination coverage (3.b.1), higher education completion rates (4.1.2), and to reach higher manufacturing value added (9.2.1) and renewable energy share (7.2.1.), as well as universal access to electricity (7.1.1). Here the difference of BAUS and systematic OS strategies that consider synergies are the largest.

Deep cultural transformation to boost SDG achievement

Effective investment combinations can drive the achievement of some SDG indicators very close. In 2024, Egypt and El Salvador are on the brink of achieving universal access to basic services (SDG indicator 1.4.1), with over 80 per cent already achieved in 2021. Azerbaijan and Thailand show promise in excelling at education completion (4.1.2). Kyrgyzstan and Uzbekistan have made significant strides in ensuring universal access to electricity (7.1.1). China, Egypt, and South Africa have demonstrated progress in mobile network coverage (9.c.1). Challenges remain for universal coverage of populations with vaccinations planned in the national programme (SDG indicator 3.b.1). (Figure 3)

Even if not immediate, several SDG indicators are on track for achievement before 2030 assuming efficient allocation of spending. This could happen for Egypt, Thailand, and China with universal access to vaccines (SDG indicator 3.b.1), Bolivia, Maldives, and Myanmar in education completion (4.1.2), and Guatemala, Indonesia, and Uzbekistan in access to electricity (7.1.1). El Salvador, Indonesia, and Kazakhstan have the potential to achieve broad mobile network coverage (9.c.1). However, challenges lie ahead for other developing economies in achieving targets measured by these indicators.¹¹ Regardless of optimal spending scenarios, some indicators on the far right and out of sight remain challenging to reach. Optimal scenarios need to be supported with other policy measures to address many cultural and other barriers to progress.

High public spending helps but is no guarantee

Higher government spending is generally associated with better outcomes in achieving SDGs. To assess this, we compared government spending with the -—
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—- scores (Figure 4). However, this relationship is not consistent across all countries, as highlighted by Afghanistan's high government spending (48 per cent relative to GDP) but low SDGs Index score (49). Finland, with high government spending, equalling 56 per cent of GDP, emerges as the top performer also in terms of the SDG Index score of 88. Notably, Ireland stands out as interesting case, where government spending is relatively modest (25 per cent) compared to GDP, but the country achieves a comparatively high SDGs Index score (80). This highlights the importance to consider factors beyond spending, such as governance and policy implementation. Adequate funding combined with strategic planning and stakeholder collaboration are necessary for achieving the SDGs.

Understanding synergies is key to SDG achievement

The analysis shows strong interconnections between government spending across sectors and SDGs. This underscores the critical need for an integrated, holistic approach to financing the SDGs. Spending on education is particularly effective in fostering achievement of outcomes across all SDGs. Similarly, spending on 'information and telecommunications' and 'health' can substantially enhance ‘education’ outcomes, creating mutual benefits.

The highest synergy coefficient of 7.5 is found for 'health' and 'education' spending. A synergy coefficient of 7.5 implies that a unit increase in combined spending on 'health' and 'education' is associated with a 7.5-fold improvement in achieving the SDGs. This suggests that the combined output of the education and health sectors has a significantly stronger impact on the SDGs compared to the sum of their individual outputs. Working on these two sectors together can lead to enhanced performance in achieving the SDGs, surpassing what could be achieved by focusing on them independently. Similarly, combined spending on 'agriculture' and 'education', or on 'housing' and 'education' yield notable synergy coefficients of 6.8 and 6.0, respectively. Synergies are also found in combined spending on 'health' and 'social' sectors, and on 'transport' and 'social' sectors, with coefficients of 2.5 and 1.7, respectively.

Systematic strategies that consider spillover effects and trade-offs can multiply effectiveness. The following figure illustrates the synergies of sectoral spending.

The analysis finds positive synergies between spending on ‘environment’ with that on ‘agriculture’, ‘housing’ and ’transportation’, illustrating the cross-cutting synergies of an environmental focus for the achievement of many SDGs. Yet, a trade-off is observed for spending on ‘fuels and mining’ and ‘environment’, primarily due to the environmental degradation caused by fossil fuels.

Understanding these synergies is essential for strategic public spending decisions, to optimize positive impacts and minimize trade-offs.

Investing in data can help target scarce resources

Halfway through the 2030 Agenda, many data gaps, specifically in developing economies hamper the analysis. This study is thus limited to 60 countries, 21 of which developing, where data for selected SDG indicators are available (Map 1). Albeit providing for 45 per cent of world population and accounting for 80 per cent of world GDP in 2021, when developing economies are considered, these values drop to 35 and 58 per cent, respectively. Currently, the coverage of countries in Africa and Latin America is critically low and remains to be extended where complementary national data sources can be found.

Costing the key targets of the SDGs is even more urgent in the present context, as multiple policy priorities, be they short, medium- or long-term priorities, imply greater trade-offs in the allocation of scarce resources. The forecast of financial costs for time-bound and target-based development goals is at the core of the methodology underpinning the SDGs.

Figure 6 shows that data for 28 SDG indicators had to be dropped because they did not have the required time series from 2005 to 2021 and covered less than half of the countries. This was 34 per cent of the 91 SDG indicators that otherwise were included within the pathways and could be costed at the country level. In total, 45 unique SDG indicators (yellow in Figure 4), or nearly 50 per cent, were dropped since for countries where these indicators were available, other input data, like government expenditure statistics were not available, and country coverage dropped too low for the inclusion of the SDG indicator. To date, it was only possible to estimate costs for the achievement of 26 per cent of SDG indicators.

This preliminary work is being extended by trying to find complementary national sources especially for government expenditure statistics. The findings also point to the critical need to invest in data and statistics to fill gaps and produce more comprehensive analysis of SDG financing needs.

Further work to inform efforts to accelerate progress towards the 2030 Agenda

The findings of this study provide early insights into pursuing more systematic and planned financing for sustainable development and gives indications of the financing needs for the countries and the SDG transition pathways for SDG indicators covered in this study. While the full analysis of the costs by SDG and optimal spending allocations are still pending, this study serves as a foundation for further research and extension. The complex nature of the work, involving numerous countries and indicators, necessitates more time for a comprehensive assessment of costs and synergies.

Credible cost estimates can only be compiled with methodologies that rely on reliable data and statistics. This bottom-up estimation starting at country levels and based on analysis of progress using SDG indicators and official statistics on government expenditure by sector enables a detailed analysis of financing needs by SDGs and their indicators or by pathway. The results are far from comprehensive due to the lack of statistics on government spending and owing to the remaining gaps in SDG indicator reporting. Further efforts to examine complementary national data sources will be taken. However, eventually the robustness and comprehensiveness of cost estimates depends on countries’ capacity to compile these key statistics.

This study serves as a starting point by providing the first experimental cost estimates covering selected SDG indicators across the SDG transition pathways. This analysis can be further refined and extended in a UN-wide collaboration and jointly with partner organizations. This could mean extension of country or SDG indicator coverage where data can be identified, focused regional or thematic analysis by different UN entities and others, and a more detailed analysis of gender equality considerations in financing SDGs.

To further improve the methodology, it would be beneficial to explore methodological refinements that incorporate determinants of efficiency related to tax revenue, FDI, debts, and ODA. By examining these factors, this costing exercise can gain a better understanding of their impact on SDG financing and identify opportunities to optimize resource allocation and improve efficiency in achieving the goals. For future analysis, it would be useful to select the most relevant SDG indicators for each SDG transition pathways thus avoiding overlap across pathways as far as possible.

This study informs the formulation of financing strategies by highlighting the importance of joining forces, finding synergies, and fostering collaboration among stakeholders. It emphasizes the need for policymakers to try to understand how different sectors and targets interact with each other. Attempts to identify areas for spill over effects and avoid trade-offs will pay off by accelerating progress towards the SDGs.

Such strategies will consider the central role of education as a trigger for progress, factor in the synergies across health, environment, and other sectors, avoid trade-offs that hamper progress in environmental sustainability and pursue the multiple benefits of gender considerations to accelerate progress by involving everyone.

Annex I. SDG costing methodology

Methodology description

The methodology of this report, based on the conclusions of Schmidt-Traub -—
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—-, emphasizes the importance of harnessing synergies within and across sectors to reduce overall financing needs and maximize the impact of spending. These sectors are interconnected through a dynamic system of feedback loops, leading to jointly significant effects on key indicators. For example, spending on transportation can enhance the effectiveness of education spending, while improved education outcomes can reinforce the impacts of the health sector and enhance livelihoods.

In the context of assessing the achievement of SDGs by countries, this study adopts a standardized frontier technology that is applicable to all countries. It employs the same specification function to transform the sectoral government spending of each country into the attainment of specific SDG indicators. The relationship between inputs and outputs in the SFM is captured through a translog cost function.

To quantify the costs required to achieve the targets of the 2030 Agenda, this study adopts a cross-sectoral approach. This approach allows for the inclusion of multiple fiscal indicators, such as sector-specific expenditures as a percentage of GDP, and it considers the interaction terms between these indicators.

This approach offers several advantages. Firstly, it mitigates the issue of overestimated costs that arise from neglecting policy synergies, ensuring a more accurate estimation of the actual costs involved. Additionally, it addresses the limitations of underestimating costs by accounting for nonlinear relationships, particularly the diminishing marginal returns.

To capture these cross-sectional synergies and nonlinear relationships between multiple policy inputs and outcomes of various SDGs, the model employs a joint production estimation. This allows for a comprehensive assessment of the interdependencies and interactions among different policies and SDG targets.

In line with the work of UNICEF -—
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—-, the cost requirements for achieving SDGs are estimated by using a stochastic frontier model based on a translog production function specification taking the following form:

where:

Ln Y_jt = Selected SDG targets for country j (in log form) – for example, Primary Net Enrolment Rates

Ln X_ijt = Spending per GDP on sector i for country j (in log form)

Ln Z_jt = controle variable of country j (in log form)

u_jt = random errors, it assumed to be independently and identically distributed, vi ∼ N (0, σ_v2)

v_jt = inefficiency term, it assumed to be positively defined with an asymmetric distribution independent of those of the u_t

The β_i (i=1,...,11) are the coefficients which illustrate the estimated elasticity of a key indicator with respect to its own-sector spending. These coefficients capture the direct effect of an increase in per GDP sectoral expenditure on the return of a key indicator.

Furthermore, the translog models include quadratic terms for each sector, represented by β_ik with i=k. These terms are included to reflect the fact that increased cost in the same sector often results in diminishing marginal returns.

The last set of coefficients β_ik with i<k, represent the synergy effects of spending in multiple sectors simultaneously, meaning the extent to which one sector’s spending impacts the effectiveness of another sector’s spending.

In order to evaluate whether a cross-sectoral impact is significant, F-test for an incremental contribution is applied.

Calculating business as usual and optimal spending scenarios

Beyond the complicated mathematical theoretical foundations of transcendental logarithmic models, the econometric tanslog models of panel data of BAUS study the asymptotic properties of a vector of significant parameters based on the underlying stochastic representation of growth of each individual. In this same space, the evolution of each SDG is studied as an endogenous variable explained by the forecast of several exogenous macroeconomic variables. So, we deduct the corresponding costs.

For the OS models which focus more on the properties of the best practices using the statistical convergence of stochastic frontiers of each country class (developed and developing). In general, econometricians choose an optimal scenario by penalizing the quality of adjustment of a model by its complexity, ex-post, during the validation or choice phase. This can sometimes result in actions that reduce the efficiency of the system being measured. Whereas in this study, the optimal scenarios are based on the objective function of a country which is considered as best practice. Then the idea is to take optimal combination of scores of an individual reference in space of expenditures as a measure reference for each country.

This approach consists of:

1. Running the Model: The Translog model specification is run under panel data, considering the efficiency term as an error term along with the random term. This allows establishing a frontier and identify the best practice. The results of this model reveal the key determinants of sectoral spending, including direct impacts of sectors, squared terms, and sector interactions - Since the model is non-linear, it provides valuable insights into the relationships between variables.
2. Forecasting the Indicator: To forecast the indicator using the retained model, the input variables need to be incorporated in the model, specifically sectoral spending. There are two alternative approaches:
   1. Assumption 1 (BAUS): In this approach, we assume that sectoral spending (the selected sectors determined by the model) will continue to grow at the same pace. This forecast data is used to calculate the indicator over time and identify the total spending required to achieve the SDG target.
   2. Assumption 2 (OS): In this approach, we consider the best practice identified by the model, using the SFM method. We use the growth rate of spending in this country to forecast the selected sectoral spending and, consequently, the indicator's evolution. This allows calculating the necessary resources needed to achieve the target.

Data sources

The dependent variables, as in the key indicators, were obtained from various databases, including the Global SDG Database -—
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—-. On the other hand, the main inputs data, government spending by COFOG classification used in the SFM model were collected by UNCTAD based on data sourced from the International Financial Statistics -—
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—- and from other international and national sources. Other inputs data, namely, government effectiveness, political stability and absence of violence and terrorism and FDI (net inflows) which were used as variables of control are sourced from and World Bank Governance Indicators -—
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—- respectively.

Estimating the precise requirement for achieving the SDGs is a challenging endeavour. Consequently, both recurrent and capital expenditures have been considered in the costing analysis. The analysis incorporates fiscal inputs in the form of government expenditures as a percentage of GDP across various service categories. The selection of these categories was based on data availability and the statistical significance of the connections between fiscal inputs and different policy measures. The inputs encompass a wide range of sectors, including agriculture; fishing, forestry and hunting; fuel and energy; mining, manufacturing and construction; transport; communication; environment protection; housing and community amenities; health; education; social protection; and other sectors. These have been identified using the COFOG.

Annex II. SDGs costing studies

Notes

1. The developing economies covered are Afghanistan, Armenia, Azerbaijan, Bolivia, China, Egypt, El Salvador, Guatemala, Indonesia, Iran, Kazakhstan, Kyrgyzstan, Maldives, Mauritius, Mongolia, Myanmar, Somalia, South Africa, Thailand, Türkiye, and Uzbekistan.
2. Sectorial spending refers to the government expenditures classified according to the COFOG classification. For the purpose of this study, 11 sectors (or functions based on COFOG) have been defined as follows: Agriculture, forestry, fishing, and hunting; Fuel and energy; Mining, manufacturing, and construction; Transport; Communication; Environment protection; Housing and community amenities; Health; Education; Social protection; and Special others. These sectors (also referred to as functions) were selected to represent specific areas of government spending and to analyze their potential impacts on achieving the SDGs. It is important to note that the terms 'sector' and 'function' are used interchangeably in this study. The terms sector and pathway, as used in this study, should not be confused. The sectors represent the specific areas of government spending that were used as inputs in the model, while the transition pathways refer to the interconnected thematic pathways towards achieving the SDGs. The pathways provide a framework for understanding the holistic progress towards sustainable development, while the sectors highlight the specific components of government spending considered in the analysis.
3. The estimates derived in this study are based on selected countries’ SDG indicators and official statistics on government expenditures, while the WIR figures are derived by SDG-sector from the most recent studies published by specialized agencies, institutions and research entities in their respective areas. This study focuses on selected 21 developing economies while WIR covers all developing economies. Furthermore, we quantify the overall financing requirement to achieve the SDGs, while WIR estimates the investment gap. i.e., the additional investment needed to achieve the SDGs. This study does not consider available financing.
4. The model endeavors to optimize the attainment of the goals by 2030; however, it recognizes that the desired optimization has not been fully achieved within the specified timeframe. Particularly regarding SDG indicators 5.5.1 and 5.4.1, it is anticipated that many countries will not reach these objectives before 2030, despite the allocated investments.
5. This study estimates the costs of achieving selected SDG indicators of the pathway, as listed in Table 1.
6. The ratio is derived by rescaling indicator SDG 5.4.1, proportion of time spent on unpaid domestic and care work by sex, for 2001-2021, to a female-to-male time use ratio, where the target is set at 1.03 for equal time use. Scores exceeding 1.03 refer to a higher female share of unpaid domestic and care work.
7. The synergy coefficient between agriculture and clean energy for developing economies is 0.013 and statistically significant at the 10 per cent level.
8. The synergy coefficient for developed economies is 4.4 for spending in education and is statistically significant at the 10 per cent level; the synergy coefficient for the combined spending in health and education is 1.7 and is statistically significant at the 5 per cent level.
9. The synergy coefficient for developed economies is 2.6 for spending on social protection and is statistically significant at the 10 per cent level.
10. The synergy coefficient for the combined spending on agriculture and housing is 1.5 and is statistically significant at the 10 per cent level.
11. This analysis reflects an optimal scenario based on efficient allocation of government spending, highlighting the positive outcomes of optimized spending. See note on BAUS and OS.

References

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“We used to think of progress as if economy, society and environment were separate spheres and that mindset led to the sustainability and exclusion crisis which we are still in now. In reality, they overlap almost completely, and our mindset is changing. We must improve people’s lives while at the same time we protect the environment. That’s why we have 17 goals with 169 targets.” said Ola Rosling when presenting the progress across all the SDGs for world leaders at the first UN SDG Moment event held in September 2020 -—
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—-. The SDG Moment takes place every September as part of the UN General Assembly, to highlight successes and identify where more action is needed to achieve the Agenda 2030.

One of the challenges facing the achievement of the Agenda 2030 is sustainable economic progress. To this end, UNCTAD has developed an inclusive growth index (IGI) to contribute to the goals equal and inclusive prosperity for all. This chapter presents the index which combines aspects of living conditions, inequalities and environment with the economy. The new UNCTAD IGI builds on earlier work by UNCTAD and EEC inclusive growth -—
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—-, first published in 2019, and aims to inform analyses and discussions on the inclusiveness of economies, particularly when taking into account social and gender inequalities. Moreover, as inclusive economy must also be sustainable to meet the needs of future generations, by preserving natural resources, the index includes a number of environmental indicators.

What is inclusive growth? Concept and background

Rising inequality and its impact on economies and societies have raised concerns among politicians, economists and the global community. Economic performance and in particular well-being should no longer be assessed by economic growth only; equality and environmental sustainability should also be considered. Many emphasize that existing levels of inequality are not only morally unacceptable, but also economically and politically damaging and corrosive -—
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Economic growth is still considered the most powerful instrument for reducing poverty and improving the quality of life -—
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—-. Research suggests that growth in average income explains 70 per cent of the variation in poverty reduction in the short run, and as much as 97 per cent in the longer term. Any remaining poverty reduction is accounted for by changes in the income distribution.

But similar rates of economic growth can have different effects on poverty, employment opportunities and human development depending on the country, the underlying conditions and governance. The extent to which economic growth reduces poverty depends on the degree of equal opportunities and freedom to participate in activities generating economic growth and to benefit from those. Thus, both the pace and pattern of growth matter for reducing poverty and inequality. The challenge for policy is how to combine growth promoting policies with measures that build and enhance equal opportunities to participate in the economy and benefit from it. This includes policies to make labour markets work better, reduce discrimination, support equal access to education and skills, and increase economic and financial inclusion in all parts of society in a sustainable manner that protects the planet.

Translating inclusive growth into a measurable concept is not an easy task, however. Information on whether changes are happening and whether those changes are moving towards inclusive growth cannot be easily captured by one indicator. The challenge is that inclusive growth is a multifaceted phenomenon, the main characteristics of which are not easily presented in a statistical form.

In 2012, the United Nations Secretary-General Ban Ki-Moon, speaking at a High-Level meeting on ‘Happiness and Well-being: Defining a New Economic Paradigm’, noted the importance of establishing ‘a Sustainable Development Index, or a set of indicators to measure progress towards sustainable development’ -—
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—-. There are initiatives to measure the inclusiveness and sustainability of wealth by taking into account human, social, produced and natural assets. For instance, the United Nations University’s International Human Dimensions Programme on Global Environmental Change in collaboration with UNEP has developed an Inclusive Wealth Index -—
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—- Comprehensive Wealth Index considers produced, human, and renewable and nonrenewable natural capital, as well as net foreign assets. There is a proliferation of other summaries of inclusiveness, well-being and sustainability. These summaries propose either a composite index or a dashboard approach and have different perspectives, data sources and approaches. This reflects the complexity of measuring the world and the issues that now are included in the ‘progress’ umbrella, such as environmental sustainability; economic stability and sustainability; social equality and health, life satisfaction, and general well-being.

Inclusive growth in the 2030 Agenda

The 2030 Agenda emphasizes the development of productive capacity as the basis for achieving inclusive and sustainable development. As part of that broad shift in emphasis towards economic, equality and environmental issues, the notion of inclusive growth has received a prominent place in the 2030 Agenda, reflected by SDG 8 in particular – ‘promoting sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all’ and Target 17.19 – ‘ by 2030, build on existing initiatives to develop measurements of progress on sustainable development that complement GDP, and support statistical capacity-building in developing countries’.

While the global SDG indicator framework does not directly measure inclusive growth, it includes a number of elements relevant to the concept, including related indicators of economic growth and environmental sustainability which is important from a temporal equality perspective. SDG 8 addresses full employment and decent work; SDG 16 aims to build just and peaceful societies; SDG 10 addresses reducing inequalities by closing socio-economic gaps within and across nations, generations and households; SDG 5 aims to reduce gaps between men and women; SDG 1 and SDG 2 aspire to build a more caring community that protects vulnerable population groups and provides for their most basic needs. Thus, linkages between SDG 8 and other SDGs are several and taken together are consistent with the concept of inclusive growth.

Beyond the 2030 Agenda, there are several dashboards, indicators or analytical approaches that set out to measure inclusive growth or elements of inclusive growth. For instance, increasing economic inclusion is set as one of the goals of the ADB Strategy 2020 -—
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—- defines inclusive growth as economic growth with equality of opportunity. Their indicator framework proposes a set of 35 indicators centered on poverty, social inclusion, social safety and governance. Achieving inclusive growth is one of the three priorities of the -—
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—- strategy called "Europe 2020". In this approach, inclusive growth is defined as support for the population through the provision of high employment rates, investment in acquisition of skills, fighting poverty and modernising the labour market.

The definition of inclusive growth must, therefore, go beyond equal participation and consider how the benefits are shared equally. In this study, we define inclusive growth by building on the 1948 Universal Declaration of Human Rights and in line with the overarching principle of the 2030 Agenda to leave no-one behind. Thus, inclusive growth is defined as equal and non-discriminatory opportunities, for everyone, to both participate in the economy and to benefit from economic growth with consideration of environmental sustainability and emphasis on gender equality.

UNCTAD IGI considers economy, living conditions, equality and environment

The first iteration of IGI consisted of three pillars, namely economy, living conditions and equality -—
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—- and was composed of 21 indicators, including one environmental indicator (CO₂ emissions under pillar 2). This new, expanded IGI includes more equality metrics addressing gender inequality more broadly (see gender section), and includes a new separate pillar dedicated to environmental issues (see environment section). These were highlighted as potential development areas of the original index, and can now be addressed also due to progress with data availability for countries. The extended IGI is comprised of four pillars and 27 indicators (see Table 1).

Taking relevance and general statistical quality into account, a review of data availability was conducted of all the major global statistical databases. As a result, the 27 indicators were selected as being the most relevant to inclusive growth from this angle and offered the best availability of robust data across countries and time (see Box 1).

Developed countries surprisingly different in inclusive growth

The new composite index of inclusive growth can provide insights about country performance regarding gender equality, living conditions or environmental sustainability as compared to economic development.

In general, higher levels of inclusive growth are associated with more economically advanced countries. Luxembourg, Iceland and Norway are among the highest-ranked countries¹ based on the overall index score. The top-ranking 30 countries are all developed economies (see Map 1). Luxembourg (the highest) and Lesotho (the lowest) were not maintained across the other three pillars. Although, Luxembourg also ranked highest in pillar 4, environment as well. The country has been successful in promoting sustainable transport and was the first country in the world to completely abolish public transport fares in February 2020 -—
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—-. Free public transportation is intended to reduce private car traffic, which is a major driver of climate change including CO₂ emissions and pollution, and also to address income inequality.

The overall index shows that more inclusive growth is often not achieved until a certain level of economic growth and prosperity is reached. However, some developing countries score higher than many developed countries. Developing countries in Africa tend to show the lowest index scores, with an average of 35.

Developed countries appear to be the most heterogeneous group characterized by the largest gap in the overall index scores. For example Luxembourg was ranked highest for the economy pillar (100) whereas the republic of Moldova was ranked lowest (11.6). Gaps between developing economies can also be large, for example Singapore scored the highest, with 81.8, compared with only 2.8 in Sudan. Even more noticeable is the difference in living conditions between countries, with Singapore scoring 88.6 and Niger at 7.0. LDCs are the most homogeneous group, with differences in index scores not exceeding 16 points for pillar 1, economy. Both developing and developed country groups are heterogeneous in terms of living conditions, equality, and environment.

The world is highly unequal in living conditions

As noted by UNCTAD member States in the Bridgetown Covenant -—
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—-, high levels of inequality are the main obstacle to sustainable economic growth and poverty reduction. Economic recovery requires evolving policies at all levels to address these issues. Prosperity gaps between and within countries have been widening for decades. Even Before the pandemic, nearly 700 million people were living in extreme poverty, and this vulnerability meant billions of people lacked access to modern technologies, including some now considered essential, such as the internet. Women around the world remain, on average, poorer and more vulnerable than men, regardless of their country of origin. Unfortunately, the remarkable expansion of global trade, investment and technology in recent decades has not benefited everyone.²

An analysis of the living conditions pillar reveals, indeed, large disparities between regions reflecting a lack of opportunities. The wide spread of countries in Figure 1 shows that living conditions in different parts of the world today are very unequal. All developed countries score above 60, except for Romania, Albania and Greece. In the rest of the world, countries like Turkey, Malaysia, Chile and Mauritius all score above 70, while others, such as Nigeria or Guinea reach a living condition score of 13 and 10, respectively. In developing Africa, Mauritius, South Africa, Egypt, Tunisia, Algeria, Morocco and Libya scored between 50 and 70. All the remaining African countries scored below 38 for living conditions. The figure also shows the relation between living conditions and equality, with better living conditions often relating to better equality scores as well, and vice versa.

Breaking down the analysis into indicator levels, the biggest challenge for Africa appears to be access to safe water. In 42 African countries, half of the population has no access to clean and safe water. The challenges of inclusive growth cannot be met without infrastructure reforms, such as ensuring sustainable and safe water systems. For developing countries in the Americas, Asia and Oceania, the challenges lie in the areas of income and gender inequality. The availability of Internet connection and logistics performance vary greatly, for example Tajikistan, Afghanistan, Turkmenistan and Bhutan have an average of 1 in 100 inhabitants with a broadband internet connection. The top three developing countries on pillar equality are Kazakhstan, Argentina and Chile. Many African countries exhibit high gender inequality in terms of labour force participation with the ratio of female to male labour force participation below 0.5. At the same time, to reduce inequalities, all people need an equal opportunity to make a living, no matter who they are and where they are located, and most importantly, have their basic human rights met, including with access to safely managed drinking water.

Developing countries differ greatly in environmental performance

At least since the 1960s, ecological economists and researchers, such as Malte Faber, Nicholas Georgescu-Roegen, Kenneth Boulding, and Herman Daly, have developed economics that take into account limited natural resources and consider sustainable development and issues of intergenerational equity. More recent studies have raised discussions over the potential exhaustion of economic growth in a system where natural resources are limited and keep being depleted. These discussions -—
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—- draw attention to the damaging effects of economic growth to natural life and resources, and the growing waste and pollution problems, not to mention climate change. This discussion is increasingly fueled by growing concerns over social inequality, and the intergenerational sustainability of induced lifestyles.

Countries have responded to these challenges by proposing an ambitious vision for the future in the form of the 2030 Agenda for Sustainable Development -—
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—-. The United Nations Member States pledged to ensure more sustainable and inclusive economic growth, elimination of extreme poverty, reduction of inequalities, and environmental protection.

It is undeniable that we are currently facing some of the most complex and widespread environmental challenges in history. Rapid population growth, climate change, increasing urbanization, and unsustainable consumption have all led to increased stress on the environment and increased conflict over land, water, and energy resources. To effectively address these challenges, it is necessary to measure the interrelations of economy and the environment. However, it is a difficult and complex task, requiring consideration of environmental impact (e.g., environmental impact on biodiversity, human health, ecosystem function, economic production), the spatial and temporal dimensions of environmental degradation (e.g., severity of environmental diseases, occurrence of extreme weather events), and the variety of stakeholder perspectives (e.g., environment activists, corporate executives, farmers, indigenous community members).

According to the IGI concept, economic growth and socially inclusive co-production associated with greater economic opportunity will be unsustainable without efficient and sustainable use of natural resources (water, land, energy, etc.). The key is to create more economic value with fewer resources in order to not compromise people's future well-being. -—
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—-. In its environment pillar, the IGI considers energy intensity, carbon dioxide emissions, water productivity, and protected land area. These address only a subset of ecological challenges, selected based on a literature review and the availability of environmental indicators for a large number of countries. See Box 1 for more details about these indicators.

The environment pillar differentiates developing countries more than economy. Bangladesh and Lesotho, for example, have almost the same score for economic performance (around 8), but around 50 and 25, respectively, for the environment pillar. On the contrary, for developed countries, differences within the economic pillar are greater than those within the environment pillar. On the same environmental score of 40, Iceland and the republic of Moldova scored around 82 and 12, respectively, on the economic pillar. The top 5 developed countries for the environment pillar are Luxembourg (100), Malta (71.4), United Kingdom (68.8), Ireland (68.2) and Switzerland (67.7). Maldives (70.5), Singapore (69.0) and Seychelles (68.6) are the top 3 countries in the developing region. This is largely due to their good performance in water productivity and energy intensity. Switzerland also shows good performance with relatively low CO₂ emissions per unit of GDP.

As mentioned above, this is not representative of all environmental aspects as only 4 indicators are included. Furthermore, these 4 metrics only capture 60 per cent of the total variance. This pillar will be subject to development as countries start producing more environmental statistics and indicators.

Developed countries generate twice as much waste per capita as developing countries

Solid waste management has been gaining importance, especially as the population continues to grow and cities expand. Many developed countries face problems with solid waste because of its high volume and the low rate of recycling. Developing countries tend to have more individual households who manage their own waste, which leads to less reliance on centralized systems. According to the data from World Bank -—
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—-, the amount of solid waste generated per capita in developed countries is around two times that generated in developing countries. This difference is not just due to the higher population density of developing countries, but also due to the higher levels of consumption of developed countries. In developed countries, the main sources of solid waste are from consumption (43 per cent), waste from households (30 per cent), urban development (14 per cent), and industrial production (12 per cent). In contrast, the main source of solid waste in developing countries is from agriculture (58 per cent), with the remainder coming from urban development (26 per cent), waste from households (12 per cent), and industrial production (4 per cent).

Figure 3 shows a positive correlation between economic development and the intensity of waste generation relative to population. Countries that score high on the economic pillar generate more waste per capita than others. These countries are almost all developed countries. Luxembourg has the highest score in the economic pillar, yet it generates almost 800 kg of waste per capita, annually (over 2 kg per person per day). Japan and the Republic of Korea have a better score for waste generation considering the high urbanization and population levels. The republic of Moldova, among some other eastern European economies, scores low in economic performance and generates high amounts of waste per capita -—
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—-. By contrast, countries of developing Africa generate the lowest amount of waste with an average of 0.54 kg per person per day. The same pattern is observed for the rest of the developing countries, including China with high economic performance compared to other developing countries but low waste generation (0.77 kg per person per day). However, there are few exceptions, Singapore has a relatively high economic performance with low waste generation (0.89 kg per person per day). Singapore set up a Zero Waste Masterplan aiming to increase the overall recycling rate to 70 per cent and reduce waste-to-landfill per capita per day by 30 per cent by 2030 -—
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Solid waste affects the quality of water, land and air and large amounts of domestic waste have many negative impacts on humans and ecosystems. Developing countries therefore face the unprecedented challenges of how to avert the low road unfortunately taken by developed countries, and marry economic growth with environmental sustainability. But the question is how?

Rather than following the same unsustainable path that associates higher economic growth with greater solid waste per capita, developing countries may find, with the support of the international community, new paths to move straight from the top left to the top right quadrant of Figure 3, representing higher economic growth with low waste generation.

Decoupling economic growth from natural resource consumption, pollution and waste generation remains a thorny issue for which global actions and solutions are required and pressing. A sustainable future may require not only technological change but also changes in consumption and social practices -—
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Enhanced gender equality analysis of inclusive growth by considering care and social reproduction³

The new IGI puts more emphasis on gender equality than its predecessor by incorporating more gender equality indicators. It takes into consideration the key role of care, drawing on the framework defined by Braunstein, Bouhia and Seguino -—
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Care can be defined as both a process and an output. As a process, it is primarily perceived as a work activity that involves close personal or emotional interaction with those being cared for -—
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—-. As an output, it refers to all paid and unpaid care activities used as inputs in the production and in the maintenance of the labour force. Care activities, whatever form they may take, have considerably contributed to generating, exacerbating and perpetuating inequality between women and men. Everywhere, women are, or have been until very recent times, reported to spend exorbitantly more time on unpaid work and care than men, essentially due to deeply entrenched stereotypes according to which they are more ‘nurturing’ or biologically better endowed to do this work -—
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—-. As a result, forms of social determinism which give women greater responsibility for this work, have prevailed, with social penalties for failure to conform to these gender norms. Gendered norms and stereotypes about care work have been acknowledged as a key contributor to gender inequality in both the market and the home -—
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Inequality stemming from the gender division of care within societies is detrimental as such to women, who have been carrying this ‘invisible’ burden at the expense of their personal, educational and professional growth, but it has also major adverse effects on economic development, especially through its impact on social reproduction. Social reproduction refers to the efforts it takes to produce, maintain and invest in the labour force, and is often expressed in terms of time and money. Braunstein, Bouhia and Seguino -—
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—- illustrate how social reproduction is organised—the extent to which reproduction takes place in the household, public or market sectors, and the gender distribution of the labour in each— and influences current aggregate demand and long-run productivity growth. Those advocating for greater female education and labour force participation assume that women’s care work is solely an impediment to their participation in paid labour. This ignores the labour as a resource that is produced. Care work that women disproportionately perform also has economy-wide benefits by raising human capacities and thus productivity. In the framework of inclusive or comprehensive wealth indices, care work would be seen as an investment in human capital, rather than a cost or a non-productive activity.

The IGI pillar 3 on equality includes conventional measures of gender parity in school and the labour market, through UNESCO’s Gender Parity Index, ILO’s rates for unemployment and labour force participation and the representation of women in national parliaments. The role of care was not directly captured in pillar 3 originally but two important aspects of it, namely public provisioning for care and reproductive infrastructure, were implicitly taken into account in the overall index, through the inclusion in pillar 2 (on living conditions) of several variables reflecting these dimensions. Infrastructure is an often-neglected aspect of the relationships between social reproduction, gender inequality and growth, but a key determinant and outcome of the gender system. It refers to goods like roads, electricity, sanitation and water that decrease the opportunity cost of market work, mostly by lowering the time intensity of care work by women, but also by lowering the price and increasing the availability of care commodities -—
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The first element added to the new IGI is men’s relative contribution to social reproduction, which refers to the gender distribution of both the time and financial costs of social reproduction. The aim is to capture gender differentials in unpaid care time. Regardless of increasing availability of time use studies, there is not even nearly enough data to carry out a historical analysis. The female-to-male ratio of mean age at first marriage was selected from available proxies with the logic that the greater the gap, the greater the gender inequality embodied in intra-household gender relations, and therefore, the more unequal the distribution of unpaid care time. The female-to-male ratio of mean age at first marriage was shown to be highly correlated with the female-to-male ratio of hours spent on domestic work -—
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The gender wage gap is the second element enhancing the new index. It was proxied by the female-to-male ratio of the share of wage and salaried employment in total employment to capture the relative quality and productivity of employment. For developing countries in particular, where self-employment and contributing to family work is often an indicator of residual unemployment, using relative access to wage employment was deemed a reasonable proxy for gender-based wage inequality in the labour market -—
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The last element included is the extent and quality of the market care sector. As women’s service sector work tends to be concentrated in the caring professions, women’s services employment as a share of total employment (men plus women) was used as a proxy for the extent of the market care sector. This measure was discounted by the extent of income inequality in the economy (by raising it to the power of the inverse of the Palma ratio) on the argument that the more inequality, the lower the quality (and pay) of care sector work.

This new gender pillar therefore aims at measuring gender equity as the equal representation of males and females in key social activities such as education and labour participation with a view of ensuring equal opportunities and treatment at the individual level, but also capturing those countries where gender equity is most likely to entail increases in human capacities and settle a genuine virtuous circle of gender equality, through an approach which level up women rather than a race to the bottom. Such virtuous circle of gender equality unlocks the full potential of economies to grow through a better quality and allocation of human capital, but the extent to which this effectively turns into sustainable economic development also depends on aggregate demand and macroeconomic orientation, as pointed by Braunstein, Bouhia and Seguino -—
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Regional disparities in gender inequality persist

Figure 4 reveals contrasted situations with gender equality of inclusive growth across regions. As expected, developed economies tend to show higher scores and are located closest to each other. Nordic countries perform particularly well: all these countries are found at the very top of the distribution, along with some Eastern European economies like Slovakia, Slovenia and Belarus . In contrast, Hungary, Greece and Romania bring up the rear.

Developing Asia is the region with the widest gaps across countries. At the top, some of these countries do better than several developed countries, including a few Central Asian economies (like Azerbaijan and Kazakhstan) and high-income countries like Singapore and the United Arab Emirates. At the same time, a significant number of Asian countries is found at the bottom of the gender equality ranking, including Iran, Jordan and Bangladesh.

The bottom of the distribution is also populated with several African countries, including Egypt, Guinea and Chad. Africa is the continent with the lowest score on average on gender equality (34). However, it hides, like in Asia, stark disparities. Rwanda, Ethiopia and South Africa are the most gender egalitarian, with scores above the median for all countries.

Latin America and the Caribbean appears to be, on average, the most gender egalitarian developing region in the light of this index, with a score reaching 52. It is also more homogeneous. These countries tend to be located in the centre of the world distribution, with Chile, Argentina and Mexico at the top and Paraguay, Honduras and Uruguay at the bottom.

The position of regions relative to each other has not changed much since 2009 (see Figure 4). Although some developing countries clearly improved their situation, the overall catching-up process of the South, observed in previous decades, did not seem to have occurred within these 10 years, pretty much in line with what was observed for other types of inequality. Developed economies have paradoxically reinforced their leading positions, especially with significant improvements in Eastern Europe. African countries have also slightly improved their rankings. Gaps across countries in the African continent have somewhat narrowed, mostly with countries at the bottom of the 2009 distribution catching up those at the top, such as Ethiopia, Ghana and Mozambique (see Figure 5). While developing Americas have maintained their overall position, Asian countries are those which have lost most ranks on average, given few remarkable upgrades combined with significant deterioration notably in Thailand and Kyrgyzstan. Overall, 12 developing countries show outstanding progression by climbing more than 10 ranks. Seven of these countries are located in sub-Saharan Africa.

Gender equality a challenge for low-income countries in particular

Figure 6 reveals a logarithmic pattern: the more economically developed a country, the more gender equality is observed, with marginally declining gains as economic development increases. However, this does not entail a strict causal relationship between gender equality and economic development. Countries showing higher economic development are not necessarily the best gender performers. This is consistent with gender equality, defined with a particular emphasis on care, being a necessary, albeit not sufficient, condition for long-term structural transformation.

Countries that have achieved their structural transformation had to pass stages of development where minimum levels of equal contribution between males and females to social reproduction were required. However, in the shorter term, the extent to which gender equality will foster stable and sustained growth depends on demand and the macroeconomic structure, in particular whether growth is predominantly driven by either the wage or the profit share. In the former case, and if gender equality in care is sufficient enough to contain the adverse effect that greater participation of women may induce on human capacities, and thereby investment, higher wages for women are likely to be good for growth. Gender equality and growth reinforce one another.

The interplay between gender equality and economic structure is particularly challenging for low-income developing countries, as illustrated by the horn shape of the curve in Figure 6. These countries generally struggle to find the right mix to kickstart the virtuous circle where both gender equality and economic orientation contribute to sustainable growth in the same direction, ensuring progress in the SDGs. In this regard, social policies which increase investment in care, going hand in hand with macroeconomic policies targeting aggregated demand, can offer solutions.

Conclusion

The broad concept of inclusive growth envisages economic growth that simultaneously contributes to improving everyone’s quality of life equally. In practical terms however, it remains an open question as to what precisely that means. This has implications for how it should be measured and how it can be achieved.

For the purposes of IGI, inclusive growth was defined as a convergence in the quality of life for all population groups within countries, achieved not only through the governmental redistribution of economic performance outcomes, but also through the creation of favorable, non-discriminatory economic conditions, that allow each population group to achieve self-sufficiently quality of life comparable to other groups and contributing to the improved quality of life of the entire population and in a sustainable manner.

The IGI, accompanied by sub-indices and its pillars, can facilitate an understanding of trade-offs and produce rankings, which can be useful in understanding the impact of policy choices as countries need to prioritise elements of economic development, education, labour and political participation, depending on local circumstances. In this study, a dual approach is adopted whereby inclusive economic growth is examined, using a global composite indicator with rankings, combined with principal components or pillars, and assessing challenges and successes by reviewing results for individual subindicators.

As multiple factors affect the inclusiveness of economic growth, policymakers struggle to design effective measures. Statisticians too face challenges in trying to quantify inclusive growth with its complex interrelations with wellbeing and sustainability. Overall, the IGI shows the wide spread of countries’ performance in living conditions, equality and environmental sustainability, underlining the insufficiency of economic growth as a sole measure of progress of nations. It calls for more comprehensive and balanced policies to advance wellbeing that is sustainable and equal, and strong enough to close persisting differences between countries and regions, and address pressing inequalities of opportunity and outcome.

Notes

1. The overall IGI has been compiled for 96 countries for which all information needed for the 4 pillars were available. Thus, the ranking does not take into consideration the missing countries.
2. Conclusions of UNCTAD's fifteenth session (TD/541/Add.2, paras. 28 and 29).

References

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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 pandemic.

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 LDCs or LLDCs 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 SIDS, 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 SDGs. 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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—- PCI shows that SIDS’ productive capacities are highly correlated with human development, and that GDP 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 EVI, used to determine inclusion and graduation from the LDC 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 FDI, and distance from ODA donors.
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, ICT 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 rate, 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 km 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 Index 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 Index -—
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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, who 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 LLDC 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 SDG 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 index, GII, HDI and EVI.

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 change, transport and ICT -—
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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.