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NATDAQ · Natural Capital Exchange · A division of EPC Holdings Ltd · Sovereign issued · Validated · Authorised
NNATDAQ
Methodology

The assumptions are open. The structuring is ours.

NATDAQ's per-country forecasts use two layers of inputs. The first layer — public-source coefficients drawn from FAO, IMF, World Bank, EPA, IUCN, and academic literature — is published below. Sovereigns can challenge any value, substitute their own national figures, and re-run the model.

The second layer — the EPC structuring model that converts these inputs into Tree Note, Conservation Note, and MSW Note pricing — is proprietary to EPC Holdings and made available to sovereign counterparties under engagement.

01 · Inputs are open
Every coefficient cites its source

If you don't agree with a number, replace it. Each row links to FAO, IMF, World Bank, EPA, or peer-reviewed literature.

02 · Structuring stays sovereign
The asset stays on your balance sheet

The EPC structuring model converts inputs into note pricing. The natural asset, the underlying programme, and the data remain with the sovereign.

03 · Build your own model
Take the inputs, run your own

Treasury, statistics office, or central bank can plug in country-specific data and replicate the model under engagement with EPC.

Conservation Note · Disclosed structuring

Conservation Note pricing — disclosed in full.

The Conservation Note structuring constants are disclosed openly so sovereigns can audit, replicate, and stack the model themselves. Tree Note and MSW Note structuring details remain proprietary to EPC and are made available under engagement.

ConstantValueNotes
Sovereign-floor price$100 per hectare per yearEPC structuring (disclosed); auditable line-by-hectare
Note tenor20 yearsEPC structuring (disclosed); stack annually for permanent conservation funding
Forestry revenue component50% of annual revenueEPC structuring (disclosed); sustainable forestry within the conserved estate
Ecosystem-outcome revenue component50% of annual revenueEPC structuring (disclosed); carbon, ESG, SDG, CSR, water, sustainability

Forestry — jobs, GDP, rural economy

CoefficientValueUnitWhat it drivesSource
forestry_jobs_per_usd_million_direct_developing
750jobs_per_usd_millionDirect on-the-ground forestry jobs per USD 1m operational capital, developing-country plantation establishment + management. Reflects low capital cost per planter / silvicultural worker.FAO 'Creating forestry jobs to boost the economy' (https://www.fao.org/4/i1025e/i1025e02.htm); ILO Green Jobs in the Forest Sector.
forestry_jobs_per_usd_million_direct_developed
60jobs_per_usd_millionDirect on-the-ground forestry jobs per USD 1m operational capital, developed/middle-income country (mechanised silviculture and harvest).FAO 'Creating forestry jobs to boost the economy', ibid.
forestry_indirect_to_direct_jobs_ratio
1.5ratioIndirect downstream jobs (sawmill, pulp, panel, transport, dry-fibre processing) per direct on-the-ground forestry job.FAO Li, Mei, Linhares-Juvenal, Cardoso 2022, 'Forest sector contribution to national economies' (https://openknowledge.fao.org/server/api/core/bitstreams/07651741-46ba-478b-8bf2-304d8bb7875b/content), 62-country IO model.
forestry_gdp_multiplier
2.3ratioGDP uplift per USD 1 invested over a full rotation. EMDE = 3.5; advanced = 1.5; sovereign-blended mid-case 2.3. Caveat: collapses to ~0 under low institutional efficiency (IMF WP 20/199).IMF WP 20/199 'The Fiscal Multiplier of Public Investment' (https://www.imf.org/-/media/Files/Publications/WP/2020/English/wpiea2020199-print-pdf.ashx).
forestry_rural_economy_multiplier
1.8ratioRural-economy income multiplier — USD 1 of farmer working capital injection generates this much downstream rural GDP. Higher in low-income agricultural economies (1.6–2.5 in SSA per LCA index).Haggblade, Hammer & Hazell (1991); IFAD Rural Development Report 2019; World Bank rural diagnostics.

Conservation — ecosystem services, jobs, note tenor & discount

CoefficientValueUnitWhat it drivesSource
conservation_jobs_per_1000_ha
2jobs_per_1000_haDirect conservation management jobs (rangers + management) per 1,000 ha actively-managed protected area. IUCN target 2.0; current global average 0.14; high-end (Tanzania NP) 7.7.Appleton et al. 2022, 'Protected area personnel and ranger numbers are insufficient', Nature Sustainability (https://www.nature.com/articles/s41893-022-00970-0).
conservation_note_discount_rate
0.05annual_rateDiscount rate applied to ecosystem service revenue stream when computing conservation note NPV. Sovereign-equivalent OECD blended rate.OECD long-dated sovereign curve average 2024-25.

Municipal Solid Waste — recoverable value, jobs

CoefficientValueUnitWhat it drivesSource
msw_recoverable_value_usd_per_tonne_developed
130usd_per_tonneBlended recoverable value per tonne MSW, developed market (gate fee $62-110 + post-sort commodity value $30-120). Mid-range for OECD.EREF 2024 Landfill Tipping Fee Survey (US avg $62/t, NE $81); CEWEP Municipal Waste Treatment 2023 (EU avg $110); EPA REI 2020 commodity values.
msw_recoverable_value_usd_per_tonne_developing
40usd_per_tonneBlended recoverable value per tonne MSW, developing market (gate fee $2-25 + lower recovery). Mid-range.Aleluia & Ferrão 2017, Waste Management 69:592–608 (https://www.sciencedirect.com/science/article/pii/S0956053X1730627X); UNEP GWMO 2024.
msw_jobs_per_100k_tonnes_year
60jobs_per_100k_tonnesDirect MSW jobs (collection, sorting, transfer, landfill operation) per 100,000 tonnes/year processed. Range 45-80.EPA Recycling Economic Information 2020 (https://www.epa.gov/smm/recycling-economic-information-rei-report); ILO 'From Waste to Jobs' 2019.
msw_indirect_jobs_per_100k_tonnes_year
250jobs_per_100k_tonnesIndirect MSW jobs per 100,000 tonnes/year — recycling/remanufacturing, EfW downstream, equipment supply. Range 200-360.Eco-Cycle / ILSR (36 jobs / 10kt recycled downstream); ILO 2025 Decent Work in Recycling brief.

Cross-cutting — sovereign multiplier

CoefficientValueUnitWhat it drivesSource
channel_finance_gdp_multiplier
2.5ratioSovereign-blended GDP uplift per USD 1 deployed. Range: advanced economies 1.5; EMDE 3.5; sovereign-blended 2.5. CAVEAT: collapses toward zero under low institutional efficiency — sovereign credit reviewers will model the downside themselves.IMF Fiscal Monitor Oct 2014 Ch.3; IMF WP 20/199 'The Fiscal Multiplier of Public Investment' (https://www.imf.org/-/media/Files/Publications/WP/2020/English/wpiea2020199-print-pdf.ashx).

Job-production forecast — at a glance

Forestry · developing market
750 jobs / $1m annual op-cap
On-the-ground plantation labour profile (FAO 'Creating forestry jobs')
Forestry · developed market
60 jobs / $1m annual op-cap
Mechanised silviculture + harvest profile (FAO ibid.)
Forestry · indirect downstream
1.5× direct
Sawmill, pulp, panel, transport (FAO Li 2022, 62-country IO)
Conservation management
2 jobs / 1,000 ha
IUCN target; Appleton et al. 2022 Nature Sustainability
MSW direct
60 jobs / 100,000 t/year
Collection, sorting, transfer, landfill (EPA REI 2020)
MSW indirect
250 jobs / 100,000 t/year
Recycling, EfW, remanufacturing downstream (ILO)

All four asset classes contribute. Per-country totals are the sum of forestry + conservation + MSW jobs scaled to that country's natural-capital programme. The country page shows the resulting employment trajectory against the baseline.

Boundaries of disclosure

What stays proprietary.

The EPC structuring model — which converts the public inputs above into Tree Note, Conservation Note, and MSW Note pricing, tranching, AiGLe Grade certification, and institutional cashflow allocation — is proprietary to EPC Holdings Ltd and made available to sovereign counterparties under engagement.

Sovereigns engaging with EPC receive the full structuring methodology, the per-instrument cashflow waterfall, the AiGLe analytical framework, and the right to replicate the model internally with their own statistical office and treasury teams. Public disclosure beyond the inputs above would compromise the institutional integrity of the listings.

To engage: contact@natdaq.exchange