Structure and Function of the Ocean Economy

1. Outcome

This Circular provides guidance on compiling indicators characterising the structure and function of the ocean economy. Upon completing this Circular, readers will understand how to derive key structural indicators from ocean economy accounts, including sector composition by industry classification, sectoral shares of gross value added (GVA) and employment, growth and productivity indicators, net ocean GVA adjusted for resource depletion, and trade and investment patterns. The guidance also provides a step-by-step compilation procedure for extracting ocean economy sub-matrices from national supply and use tables and deriving structural indicators from them. The guidance responds to high demand from governments seeking to characterise their ocean economies for national budget processes, economic planning, and international reporting--including reporting against Sustainable Development Goal 14 (Life Below Water), particularly target 14.7 on economic benefits from sustainable use of marine resources. These indicators build directly on the ocean economy thematic and extended accounts described in TG-3.3 Economic Activity Relevant to the Ocean and support applications in national budget processes addressed in TG-1.1 OA and National Budget Processes. The relationship between ocean economy structure and multilateral environmental agreement indicators, including SDG 14, is addressed further in TG-2.10 MEA Indicators.

2. Requirements

This Circular requires familiarity with:

• TG-0.1 General Introduction to Ocean Accounts -- for the conceptual framework and key components of Ocean Accounts
• TG-0.2 Overview of Relevant Statistical Standards -- for the international statistical standards underpinning ocean accounting, including the SNA 2025, SEEA, ISIC classification, and the methodological principles that govern thematic and extended accounts
• TG-3.3 Economic Activity Relevant to the Ocean -- for the methodological framework for compiling ocean economy thematic and extended accounts, including industry classifications and supply and use tables

3. Guidance Material

Governments preparing national budgets need to demonstrate the ocean economy's contribution to GDP, employment, and exports (TG-1.1 OA and National Budget Processes). Budget officials require quantified evidence of a sector's contribution to national income and employment to justify public expenditure on ocean management, fisheries governance, port infrastructure, and marine environmental protection. The indicators in this Circular provide the analytical tools for these demonstrations, translating the detailed accounting data compiled under TG-3.3 into policy-ready metrics that can populate the budget presentation structures described in TG-1.1 Section 3.3. Specifically, TG-1.1 identifies a four-row indicator structure--GDP contribution, employment, exports, and fish protein supply--that budget submissions should address; the indicator derivation methods in this Circular show compilers how to produce each of these figures from ocean economy accounts.

Understanding the structure and function of the ocean economy is essential for effective ocean governance and sustainable development. Structural indicators reveal how the ocean economy is composed across different sectors, how it contributes to national economic output and employment, and how it is evolving over time. These indicators inform policy decisions ranging from infrastructure investment to education and training, from trade policy to environmental management.

This Circular presents a framework for deriving structural and functional indicators from ocean economy accounts. The approach follows established practices from the System of National Accounts (SNA 2025)^[1], draws on analogous approaches developed for tourism in the Statistical Framework for Measuring the Sustainability of Tourism (SF-MST)^[2], and builds on the ocean economy thematic and extended accounting methodology described in the SEEA Ecosystem Accounting^[3]. The SF-MST provides a particularly useful analogue because, like ocean economy measurement, tourism measurement involves delineating a functional segment of the economy that cuts across multiple ISIC industries rather than corresponding neatly to a single industrial classification. Both frameworks address the challenge of identifying and measuring economic activity defined by its relationship to a particular domain (the ocean or tourism) rather than by industry classification alone, and the indicator derivation approaches developed for tourism can be adapted effectively for ocean economy structural analysis.

3.1 Ocean Economy Structure Framework

The structure of the ocean economy describes how economic activity is distributed across different industries, products, and institutional sectors. A comprehensive structural analysis enables comparison of the ocean economy to the broader national economy, identification of dominant and emerging sectors, and assessment of concentration and diversification.

Analytical dimensions

Structural analysis of the ocean economy operates across four key dimensions^[4]:

1. Industry composition -- the distribution of ocean economic activity across industries classified according to ISIC, revealing which types of production dominate the ocean economy (e.g., fishing, shipping, offshore energy)

2. Product composition -- the distribution of ocean-characteristic products according to CPC, revealing what goods and services the ocean economy produces

3. Institutional sector composition -- the distribution of ocean economic activity by institutional sector (corporations, government, households, non-profit institutions), revealing ownership and control patterns

4. Spatial composition -- the distribution of ocean economic activity across regions or coastal zones, revealing geographic concentration and regional dependencies. The spatial dimension is particularly important for ocean economies because economic activity is inherently concentrated in coastal areas. The SF-MST provides guidance on sub-national measurement (Section 2.5) that is directly applicable to regional ocean economy analysis, including destination-level measurement approaches that can be adapted for coastal economic zones^[5]. Spatial analysis of the ocean economy connects to the treatment of coastal tourism in TG-3.3 Section 3.4 and may inform future guidance on regional ocean accounts compilation.

Relationship to thematic and extended accounts

Structural indicators are derived from the ocean economy thematic and extended accounts described in TG-3.3 Economic Activity Relevant to the Ocean. The SNA 2025 uses the term "thematic and extended accounts" in place of the former "satellite accounts" terminology used in earlier editions (SNA 2025 Chapter 38, para 38.2)^[6]. The supply and use tables (SUTs) compiled for the ocean economy provide the data foundation for structural analysis^[7]. From balanced SUTs, the following can be derived:

• Output by industry and product
• Gross value added by industry
• Employment by industry
• Imports and exports of ocean-characteristic products
• Gross fixed capital formation by industry

These aggregates form the basis for the indicators presented in subsequent sections.

SUT-to-indicator derivation trace

The derivation of structural indicators follows a specific path from the cells of the ocean economy SUTs compiled under TG-3.3 Section 3.4 (Table 1) to the indicators presented in this Circular. Compilers should trace each indicator to its source aggregate to ensure consistency between accounts and indicators:

• GVA share by industry -- the GVA row in the Use Table provides gross value added for each ocean industry column (e.g., Marine Fishing, Aquaculture, Shipping, Ports, Tourism). Each cell is the numerator for the sector GVA share indicator in Section 3.2.
• Employment share by industry -- the labour inputs row (hours worked or persons employed) at the bottom of the Use Table provides the numerator for the employment share indicator.
• Export share -- the Exports column in the Use Table, summed across ocean-characteristic product rows (fish products, transport services, tourism services), provides the ocean economy exports aggregate used in Section 3.5.
• Investment indicators -- the GFCF column in the Use Table shows capital formation by product type; the GFCF row by industry provides the industry-level investment data for investment rate calculations.
• Productivity -- labour productivity for each ocean industry is computed by dividing the GVA cell for that industry by the corresponding labour inputs cell.

This explicit mapping ensures that every indicator in this Circular can be traced back to a specific cell or aggregate in the ocean economy SUTs, providing a clear audit trail from accounts to indicators to policy applications.

3.2 Sector Composition Indicators

Sector composition indicators describe the relative importance of different industries within the ocean economy. These indicators enable identification of dominant sectors, comparison with national industry structure, and tracking of structural change over time.

Classification framework

Ocean economy industries are classified using the International Standard Industrial Classification (ISIC)^[8]. Following the categorisation in TG-3.3 Section 3.3, ocean industries are grouped as:

Core ocean-dependent industries (wholly ocean-related):

• ISIC Division 03: Fishing and aquaculture
  • Class 0311: Marine fishing
  • Class 0321: Marine aquaculture
• ISIC Division 50: Water transport
  • Class 5011: Sea and coastal passenger water transport
  • Class 5012: Sea and coastal freight water transport
• ISIC Division 06: Extraction of crude petroleum and natural gas (offshore portion)
• ISIC Class 3511: Electric power generation (offshore wind, tidal, wave)

Ocean-related industries (partially ocean-related, requiring estimation of ocean share):

• ISIC Class 1020: Processing and preserving of fish, crustaceans and molluscs
• ISIC Class 3011: Building of ships and floating structures
• ISIC Class 3012: Building of pleasure and sporting boats
• ISIC Class 5222: Service activities incidental to water transportation
• ISIC Class 5224: Cargo handling (port cargo handling share)
• ISIC Class 5510: Short-term accommodation activities (coastal tourism share)
• ISIC Class 7210: Research and experimental development (marine research share)
• ISIC Class 8423: Public order and safety activities (coast guard, maritime enforcement share)
• ISIC Class 9319: Other sports activities (marine sports and recreation share)

This listing is illustrative and should be verified against the more comprehensive classification in TG-3.3 Section 3.3, which provides the authoritative industry concordance for ocean economy accounts. Compilers should adapt the industry scope to their national circumstances and document the specific ISIC classes included. For offshore oil and gas extraction and offshore renewable energy, additional classification detail is provided in TG-3.10 Offshore Energy.

Key composition indicators

The following indicators characterise sector composition^[9]:

Output share by industry $$\text{Output share}_i = \frac{\text{Output}_i}{\sum_j \text{Output}_j} \times 100$$

where $i$ denotes an individual ocean industry and $j$ indexes all ocean industries.

GVA share by industry $$\text{GVA share}_i = \frac{\text{GVA}_i}{\sum_j \text{GVA}_j} \times 100$$

This indicator reveals the relative contribution of each industry to total ocean economy value added.

Employment share by industry $$\text{Employment share}_i = \frac{\text{Employment}_i}{\sum_j \text{Employment}_j} \times 100$$

Employment may be measured as number of persons employed, number of jobs, hours worked, or full-time equivalent (FTE) positions^[10].

Herfindahl-Hirschman Index (HHI) for concentration $$\text{HHI} = \sum_i \left(\frac{\text{GVA}_i}{\sum_j \text{GVA}_j} \times 100\right)^2$$

The HHI ranges from near zero (highly diversified) to 10,000 (single industry). In antitrust analysis, an HHI above 2,500 is conventionally treated as indicating high concentration^[11]. For ocean economy sectoral analysis, however, compilers should interpret HHI values with caution. Small island developing States (SIDS) and countries with narrow resource endowments may exhibit structurally higher concentration in their ocean economies--dominated, for example, by fisheries and tourism--without this necessarily indicating a policy concern in the same way that high market concentration does. Compilers should present the HHI alongside the detailed composition data in Table 3.1 so that users can assess whether concentration reflects structural characteristics of the economy or an imbalance that warrants policy attention.

Comparative analysis

Sector composition indicators gain meaning through comparison. Recommended comparisons include:

1. Comparison to national economy -- comparing ocean industry shares to their shares in the national economy reveals specialisation patterns

2. Comparison over time -- tracking composition changes reveals structural transformation (e.g., growth of offshore energy relative to traditional fishing)

3. International comparison -- comparing ocean economy structure across countries reveals different endowments and development patterns

Table 3.1 presents sector composition indicators for a hypothetical medium-income coastal state ("Country A") with a total GDP of approximately USD 50 billion, total employment of 10 million persons, and an ocean economy representing 3.5 per cent of GDP. All monetary values are expressed in millions of US dollars.

Table 3.1: Ocean economy sector composition (Country A, illustrative)

The HHI computed from the GVA shares in Table 3.1 is approximately 2,034 (= 32.0^2 + 24.0^2 + 18.0^2 + 10.0^2 + 7.0^2 + 4.0^2 + 5.0^2), indicating moderate concentration. Two sectors--coastal and marine tourism and offshore energy--together account for 56 per cent of ocean GVA, a pattern common in medium-income coastal states with established hydrocarbon production.

To make comparative analysis concrete, Table 3.1a presents a recommended format for comparing ocean economy structure against the national economy. This comparative presentation, adapted from the SF-MST approach to characterising tourism industries (SF-MST Table 3.3), enables identification of sectors in which the ocean economy is relatively more or less intensive than the national economy as a whole.

Table 3.1a: Ocean economy versus national economy structure (Country A, illustrative)

The data in Table 3.1a reveal that while the ocean economy accounts for 3.5 per cent of GDP, it accounts for only 3.0 per cent of employment, implying slightly above-average labour productivity. The ocean economy's share of exports (5.2 per cent) exceeds its share of GDP, indicating an outward orientation driven by fish product exports and maritime transport services.

Budget-ready summary

Table 3.1b maps the indicators derived from Tables 3.1 and 3.1a directly to the four-row budget presentation structure specified in TG-1.1 Section 3.3 (Table 1). This table provides the format in which ocean economy indicators should be presented in national budget submissions to demonstrate the sector's contribution to the national economy.

Table 3.1b: Ocean economy contribution -- budget presentation format (Country A, illustrative)

3.3 Growth and Productivity Indicators

Growth and productivity indicators measure the dynamic performance of the ocean economy. They reveal whether the ocean economy is expanding or contracting, whether growth is generating productivity improvements, and how ocean economy performance compares to the broader economy.

Growth indicators

Nominal growth rate $$\text{Growth rate}t = \frac{X_t - X{t-1}}{X_{t-1}} \times 100$$

where $X$ is the variable of interest (output, GVA, employment) and $t$ is the reference period.

Real growth rate -- adjusts for price changes using appropriate deflators^[12]: $$\text{Real growth rate}t = \frac{X_t / P_t - X{t-1} / P_{t-1}}{X_{t-1} / P_{t-1}} \times 100$$

where $P$ is the relevant price index. The choice of deflator is important for ocean economy aggregates because price movements in ocean industries can diverge substantially from economy-wide trends. Offshore energy output, for example, is strongly influenced by international oil and gas price indices, while maritime transport output responds to freight rate indices such as the Baltic Exchange indices. Compilers should use industry-specific deflators where available rather than applying the aggregate GDP deflator to all ocean industries. Where sector-specific deflators are unavailable, compilers should document the deflator used and assess the potential bias introduced. Methodological guidance on deflation and volume measurement is provided in SNA 2025 Chapter 18, and further context on the statistical standards governing price and volume measures is available in TG-0.2 Standards Overview.

Compound annual growth rate (CAGR) -- measures average annual growth over multiple periods: $$\text{CAGR} = \left(\frac{X_T}{X_0}\right)^{1/T} - 1$$

where $T$ is the number of years.

Productivity indicators

Productivity measures the efficiency with which inputs are transformed into outputs. Two measures are particularly relevant for ocean economy analysis^[13]:

Labour productivity $$\text{Labour productivity} = \frac{\text{GVA}}{\text{Employment}}$$

This can be expressed per person employed, per job, or per hour worked. Labour productivity in ocean industries can be compared to national averages to assess relative efficiency.

Capital productivity (where capital stock data are available) $$\text{Capital productivity} = \frac{\text{GVA}}{\text{Capital stock}}$$

Capital stock data for ocean industries are often limited, particularly for industries such as offshore energy and maritime transport where assets are mobile and may be registered in multiple jurisdictions. Where direct capital stock data are unavailable, compilers may estimate capital stocks using the perpetual inventory method, applying asset-specific depreciation rates to historical investment series. The asset valuation methodology described in TG-3.1 Asset Accounts provides relevant guidance on produced capital valuation that can be adapted for ocean industries, particularly for vessels, port infrastructure, and offshore installations^[14].

Multi-factor productivity growth requires more sophisticated analysis combining labour, capital, and intermediate inputs, typically using growth accounting or index number methods^[15].

Ocean economy contribution to GDP growth

A particularly policy-relevant indicator is the contribution of the ocean economy to overall GDP growth^[16]:

$$\text{Contribution to GDP growth} = \frac{\Delta \text{Ocean GVA}}{\text{GDP}_{t-1}} \times 100$$

This measures the percentage point contribution of ocean economy growth to national GDP growth. This indicator is directly relevant for the budget justifications addressed in TG-1.1 OA and National Budget Processes and for demonstrating the economic importance of ocean management investment.

3.4 Net Ocean GVA

Gross measures of ocean economy value added do not account for the depletion of the marine natural resources on which many ocean industries depend. The SNA 2025 treats depletion of non-produced natural resources as a cost of production (SNA 2025 Chapter 15, para 15.137), and TG-1.1 Section 3.1 identifies net domestic product (NDP) as the conceptually preferred measure of economic growth^[17]. For the ocean economy, this has particular significance because fisheries, offshore minerals, and other extractive ocean industries draw down natural capital stocks.

Net ocean GVA is defined as:

$$\text{Net ocean GVA} = \text{Gross ocean GVA} - \text{Depletion of marine natural resources}$$

Depletion of marine natural resources includes:

• Depletion of fish stocks -- the decline in the economic value of fish stock assets due to harvesting in excess of natural regeneration. Estimation methods are described in TG-3.1 Asset Accounts, drawing on stock assessment data from TG-6.7 Fisheries Stock Assessment.
• Depletion of seabed minerals -- the decline in the economic value of offshore mineral and hydrocarbon reserves due to extraction. Valuation follows the SNA 2025 treatment of subsoil assets (Chapter 15, rows 22--23 of the Use Table).

Where depletion estimates are available, compilers should present both gross and net measures of ocean GVA side by side. The difference between gross and net ocean GVA reveals the extent to which the ocean economy's recorded economic contribution depends on the drawdown of natural capital. A large and growing gap between gross and net ocean GVA signals unsustainable resource use patterns that should inform policy deliberations under medium-term expenditure frameworks (TG-1.1 Section 3.4). In the Country A illustration (Table 3.1), if fish stock depletion is estimated at USD 35 million and offshore mineral depletion at USD 60 million per year, net ocean GVA would be USD 1,655 million--approximately 5.4 per cent below the gross figure of USD 1,750 million.

3.5 Employment Structure

Employment structure indicators characterise the labour market dimensions of the ocean economy. These indicators inform policies on education, training, migration, and social protection.

Employment levels and shares

Ocean economy employment share $$\text{Employment share} = \frac{\text{Ocean employment}}{\text{Total national employment}} \times 100$$

This headline indicator reveals the ocean economy's importance as an employer.

Industry-specific employment -- employment in each ocean industry, enabling analysis of which sectors are most labour-intensive^[18].

Employment characteristics

Beyond aggregate employment, structural analysis should capture employment quality and composition^[19]:

Status in employment

• Employees (wage and salary workers)
• Employers
• Own-account workers
• Contributing family workers

Working time

• Full-time versus part-time employment
• Average hours worked
• Seasonal patterns in employment

Demographic characteristics

• Gender composition (share of women in ocean employment)
• Age structure
• Educational attainment
• Nationality (share of migrant workers)

Decent work indicators following the ILO Decent Work Measurement Framework^[20]:

• Share of formal versus informal employment
• Wage levels relative to national average
• Working conditions indicators
• Social protection coverage

The distinction between formal and informal employment is particularly relevant for small-scale fisheries, where employment is often characterised by own-account work, seasonal or part-time engagement, and limited coverage by labour regulations or social protection schemes. Measuring employment in small-scale fisheries presents methodological challenges: workers may not appear in business registers, labour force surveys may undercount seasonal or part-time fishing activity, and the boundary between subsistence fishing and commercial fishing can be difficult to establish. Compilers should consider supplementing standard data sources with fisheries census data, community-based surveys, and vessel registry information. Employment patterns in aquaculture, including the prevalence of informal and seasonal work in coastal communities, are addressed in TG-3.9 Aquaculture. The connection between employment data and stock management is discussed in TG-6.7 Fisheries Stock Assessment.

Table 3.2 presents employment structure indicators for Country A, populated with synthetic data reflecting typical patterns observed in medium-income coastal states.

Table 3.2: Ocean economy employment structure (Country A, illustrative)

Several structural patterns are evident in Table 3.2. Marine fishing exhibits the highest informality rate (60 per cent) and the lowest female participation (15 per cent), consistent with the artisanal and small-scale character of much of the sector. Coastal tourism is the largest employer by a substantial margin (153,000 persons, or 51 per cent of ocean employment), but it has the highest rate of part-time and seasonal work, as reflected in the gap between persons employed and FTE employment. Offshore energy employs relatively few workers (24,000 persons) but generates the highest wages and highest productivity index (350), reflecting the capital-intensive nature of offshore oil, gas, and wind operations. These patterns inform workforce development policies, gender mainstreaming strategies, and social protection design for ocean-dependent communities.

Spatial distribution of employment

Ocean employment is inherently concentrated in coastal regions. Spatial analysis reveals:

• Regional employment concentration
• Coastal community dependence on ocean employment
• Commuting patterns between coastal and inland areas

This spatial dimension connects to livelihood dependency analysis in TG-2.3 Livelihood Dependencies.

3.6 Trade and Investment Indicators

Trade and investment indicators reveal the ocean economy's external orientation and its capacity for growth through capital accumulation. These indicators are particularly relevant for open economies with significant maritime trade and foreign investment in ocean sectors.

Trade indicators

Ocean economy exports $$\text{Export share} = \frac{\text{Exports of ocean products}}{\text{Total national exports}} \times 100$$

Ocean exports include:

• Fish and fishery products
• Maritime transport services
• Offshore oil and gas (where applicable)
• Cruise and marine tourism receipts
• Ship repair services

Ocean economy imports -- imports of ocean-characteristic products, including:

• Fishing vessels and equipment
• Maritime transport services (freight payments)
• Offshore drilling equipment
• Imported fish for processing

Trade balance for ocean economy $$\text{Ocean trade balance} = \text{Ocean exports} - \text{Ocean imports}$$

Revealed comparative advantage -- indicates whether a country specialises in ocean products relative to its overall trade pattern^[21]: $$\text{RCA}_i = \frac{(X_i / X)}{(X_i^{world} / X^{world})}$$

where $X_i$ is exports of ocean product $i$ and $X$ is total exports. An RCA > 1 indicates comparative advantage.

Maritime transport services trade requires careful treatment due to the distinction between resident and non-resident operators. The spatial treatment of economic activities within the Exclusive Economic Zone is addressed in TG-3.3 Section 3.1. The Balance of Payments Manual (BPM6, and its successor BPM7) provides detailed guidance on recording maritime transport services in the current account, including the allocation of freight charges between importing and exporting economies and the treatment of services provided by non-resident carriers^[22]. Compilers should ensure that trade in maritime transport services is recorded consistently between the ocean economy accounts and the balance of payments.

Investment indicators

Gross fixed capital formation (GFCF) in ocean industries

Ocean economy investment includes:

• Vessels (fishing boats, cargo ships, cruise ships)
• Port infrastructure (harbours, terminals, cargo handling equipment)
• Offshore platforms and installations
• Aquaculture facilities
• Coastal tourism infrastructure

Investment rate $$\text{Investment rate} = \frac{\text{Ocean GFCF}}{\text{Ocean GVA}} \times 100$$

Higher investment rates suggest capacity expansion and future growth potential.

Investment share $$\text{Investment share} = \frac{\text{Ocean GFCF}}{\text{Total national GFCF}} \times 100$$

This reveals the ocean economy's share of national capital formation.

Foreign direct investment (FDI) in ocean sectors -- where data permit, the stock and flow of FDI in ocean industries provides insight into external capital participation. This may be particularly significant in offshore energy, maritime transport, and port operations^[23]. FDI data by detailed industry are often limited and may be subject to confidentiality constraints where few enterprises operate in a given industry. Where direct FDI data are unavailable, compilers may use alternative approaches such as ownership information from business registers, investment project tracking databases, or qualitative assessments based on known foreign ownership in key ocean industries. Detailed treatment of investment analysis for the ocean economy is provided in TG-2.6 Ocean Investment.

Sustainable ocean finance

Beyond conventional GFCF, the investment dimension of the ocean economy increasingly includes sustainable ocean finance instruments such as blue bonds, blue loans, and blue equity investments. These instruments channel capital towards ocean-related activities that meet defined environmental sustainability criteria. While sustainable finance flows are not recorded as GFCF in the national accounts (they represent financial transactions rather than acquisition of produced assets), their scale and growth constitute an important structural characteristic of the ocean economy's financing landscape. The methodology for measuring sustainable ocean finance, including classification criteria, data sources, and indicator definitions, is addressed in TG-2.6 Ocean Investment Section 3.4.

Table 3.3 presents trade and investment indicators for Country A.

Table 3.3: Ocean economy trade and investment (Country A, illustrative)

Government expenditure on ocean-related functions

Government expenditure on ocean-related activities can be identified using the Classification of the Functions of Government (COFOG)^[24]. Table 3.4 maps specific COFOG classes to ocean-related government functions, adapted from the SF-MST approach to identifying tourism-related government functions (SF-MST Table 3.9)^[25].

Table 3.4: COFOG classes relevant to ocean economy functions

This mapping supports analysis of public investment in ocean management addressed in TG-1.1 OA and National Budget Processes.

3.7 Compilation Procedure

Compiling ocean economy structural indicators requires a systematic procedure for extracting ocean economy data from national supply and use tables and deriving indicators from them. The procedure described below is adapted from the SNA 2025 treatment of supply and use tables (Chapter 15, paras 15.9, 15.130--15.139) and draws on the analogous approach developed for tourism in the SF-MST (paras 2.30--2.31, 3.27--3.28)^[26].

Step-by-step compilation

Step 1: Identify ocean economy industries by ISIC code. Using the TG-3.3 Section 3.3 concordance (Table 2), identify all ISIC classes that constitute the ocean economy in the compiling country. For each class, determine whether it is wholly ocean-dependent (ocean ratio = 1.0) or partially ocean-related (ocean ratio < 1.0). This classification corresponds to the identification of "tourism characteristic activities" in the SF-MST framework (SF-MST para 2.31).

Step 2: Extract ocean economy sub-matrices from national SUTs. From the balanced national supply and use tables, extract the columns corresponding to identified ocean economy industries. This creates an ocean economy supply table and an ocean economy use table that are subsets of the national tables. If the national SUTs are published at a level of aggregation above individual ISIC classes (e.g., at division level), compilers may need to use supplementary data sources--business surveys (TG-4.2) and administrative records (TG-4.3)--to disaggregate the relevant columns.

Step 3: Determine the ocean economy ratio for each industry. For partially ocean-related industries, estimate the share of output directly attributable to ocean-related activity. This is analogous to the tourism ratio described in SF-MST para 3.28: the total output of ocean-characteristic products by an industry divided by its total output. For example, if 40 per cent of short-term accommodation output in a coastal region serves marine tourism demand, the ocean economy ratio for that industry is 0.40. Methods for estimating these ratios include analysis of establishment-level survey data, use of tourism statistics for coastal areas, and expert judgement informed by administrative records.

Step 4: Calculate Ocean Economy Direct GVA. For each ocean industry, multiply the industry's gross value added from the Use Table by its ocean economy ratio:

$$\text{Ocean Economy Direct GVA} = \sum_i (\text{GVA}_i \times \text{Ocean ratio}_i)$$

This yields the total value added directly attributable to ocean economic activity, following the same logic as the Tourism Direct GDP calculation in SF-MST para 3.27.

Step 5: Adjust for taxes less subsidies on products. To derive Ocean Economy Direct GDP from Ocean Economy Direct GVA, add the ocean-related share of taxes less subsidies on products:

$$\text{Ocean Economy Direct GDP} = \text{Ocean Economy Direct GVA} + \text{Ocean share of (taxes - subsidies on products)}$$

The ocean share of product taxes and subsidies can be estimated in proportion to the ocean economy's share of total final expenditure on ocean-characteristic products.

Step 6: Derive indicators from the ocean economy SUT extract. Using the ocean economy sub-matrices and the ocean economy ratios, compute the full set of structural indicators described in Sections 3.2 through 3.6 of this Circular: sector composition indicators (GVA shares, employment shares, HHI), growth and productivity indicators, net GVA, employment structure, and trade and investment indicators.

Data pipeline

The compilation of ocean economy structural indicators involves a multi-stage data pipeline that spans several circulars in this Technical Guidance series. Raw data are collected through surveys (TG-4.2 Survey Methods) and administrative records (TG-4.3 Administrative Data). These data are harmonised and integrated (TG-4.6 Data Harmonisation) and compiled into ocean economy thematic accounts--including production accounts, supply and use tables, and employment accounts (TG-3.3). The indicator formulas described in this Circular (TG-2.5) are then applied to the compiled accounts to produce the structural indicators. Finally, these indicators are formatted for policy application in national budget processes (TG-1.1) and international reporting (TG-2.10).

3.8 Compilation Considerations

Compiling ocean economy structural indicators requires attention to data quality, consistency, and comparability.

Data sources

Key data sources include^[27]:

• National accounts (supply and use tables, production accounts)
• Business surveys and censuses
• Labour force surveys
• Trade statistics
• Administrative records (vessel registries, port authorities, fishing licences)

Detailed guidance on the utilisation of these data sources for ocean accounting is provided in TG-4.2 Survey Methods, TG-4.3 Administrative Data, and TG-4.6 Data Harmonisation. Effective compilation of ocean economy structural indicators typically requires integration of data from multiple sources, and TG-4.6 addresses the harmonisation challenges that arise when combining data with different coverage, classifications, and reference periods.

Informal economy and indicator reliability

Structural indicators may understate the full extent of the ocean economy where informal economic activities are significant. Small-scale fisheries, artisanal aquaculture, informal coastal tourism services, and subsistence marine harvesting are often inadequately captured by standard business surveys and national accounts. In countries where informal activities constitute a substantial share of ocean-related production and employment, the indicators derived from formal data sources may present an incomplete picture of the ocean economy's true size and structure. Compilers should document the estimated coverage of formal data sources relative to the full ocean economy, identify sectors where informal activity is likely to be most significant, and consider supplementary estimation methods described in TG-4.2 and TG-4.3 for improving coverage of informal activities. Users of ocean economy indicators should be informed of coverage limitations so that they can interpret aggregate statistics with appropriate caution.

Quality indicators

Compilers should document:

• Coverage (which industries and products are included)
• Methods for estimating ocean-related shares of mixed industries
• Frequency of data collection and time lags
• Accuracy estimates and confidence intervals where available

Quality assurance guidance is provided in TG-0.7 Quality Assurance.

Comparability considerations

For time series analysis and international comparison:

• Use consistent industry and product classifications
• Apply consistent valuation principles (basic prices versus purchasers' prices)
• Document changes in methodology that affect comparability
• Use appropriate exchange rates for international comparison

International comparability of ocean economy indicators has been advanced through several ongoing measurement programmes that compilers may find useful as supplementary references. The European Commission's annual EU Blue Economy Report provides a systematic methodology for identifying and measuring ocean economy sectors across EU member states using Eurostat structural business statistics^[28]. The OECD's work on ocean economy measurement, including The Ocean Economy in 2030 (2016), provides a broader international framework for comparable ocean economy statistics. These resources can assist compilers in benchmarking their approaches against established international practices, though the thematic and extended accounting framework described in TG-3.3 remains the primary methodological reference for this Technical Guidance series.

4. Acknowledgements

This Circular has been approved for public circulation and comment by the GOAP Technical Experts Group in accordance with the Circular Publication Procedure.

Authors: CBE, Thauan Santos

Reviewers: Crystal Bradley

5. References