What is a trade-intensity coefficient?

It is the share of GDP per capita that buyers in a market typically spend on imported goods of a given category. Multiplying it by GDP per capita gives a per-person spend estimate, which scaled by population gives a rough addressable market for that product type.

How accurate is this estimate?

It is a top-down planning heuristic, not measured trade data. The coefficients are illustrative and the model ignores tariffs, local production, and competition. Use it to rank candidate markets, then validate the leaders against real customs and trade-flow statistics.

Why use GDP per capita instead of total GDP?

GDP per capita reflects individual purchasing power, which drives how much each buyer can spend on a category. Combining per-capita spend with population separates rich-small markets from large-poor ones, which total GDP alone obscures.

What target share should I use?

Use a realistic share you could capture given competition and your resources, often a low single-digit percentage for a new entrant. The tool keeps share as a separate input so you can run optimistic and conservative scenarios against the same addressable market.

Can I override the coefficient?

Yes. If you have a better trade-intensity figure from industry research or customs data, enter it in the override field. The embedded defaults are starting points to make the tool usable without external data, not authoritative values.

What is the Trade Intensity & Export Revenue Estimator?

Multiplies target market GDP per capita by population and an industry trade-intensity coefficient from an embedded table to produce a rough export revenue potential estimate for market prioritisation. For trade advisors, exporters, and market-entry analysts. It runs free in your browser on Gera Tools, with nothing uploaded.

Trade Intensity & Export Revenue Estimator

Name: Trade Intensity & Export Revenue Estimator
Creator: Gera Tools
License: https://creativecommons.org/licenses/by/4.0/

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When you are choosing which export markets to chase first, you need a fast, consistent way to rank them. This estimator combines a market’s GDP per capita, its population, and an industry trade-intensity coefficient into a rough addressable-market figure, then applies your target share to estimate export revenue potential.

How it works

The model follows a straightforward top-down chain:

spend_per_capita   = gdp_per_capita × trade_intensity
addressable_market = population × spend_per_capita
export_potential   = addressable_market × target_share

The trade-intensity coefficient is the lever that adapts the model to your product category — it represents the share of GDP per capita that buyers in a market typically spend on imported goods of that type. The tool includes illustrative coefficients by industry that you can override with better data from customs statistics or industry reports.

Why GDP per capita — not total GDP

Total GDP tells you the size of the economy, but it combines a small number of very wealthy consumers with a large number of low-income earners in ways that can mislead market prioritisation. GDP per capita captures average purchasing power, which drives how much each person can actually spend on your category.

The difference matters when comparing:

A market of 5 million people at $40,000 GDP per capita: addressable market may be larger despite smaller population
A market of 50 million people at $3,000 GDP per capita: large population but lower per-person spend on imports

The model separates these effects explicitly, giving you a spending estimate per person that you then scale by population.

Worked example

Packaged food exporter evaluating two markets. Illustrative trade-intensity coefficient for packaged food: 2.5%.

Market	GDP/capita	Population	Spend/person	Addressable	2% share = potential
Market A	$12,000	10M	$300	$3.0B	$60M
Market B	$25,000	4M	$625	$2.5B	$50M

Market A ranks higher by addressable market, but Market B’s higher per-capita income may mean lower price sensitivity and easier margin maintenance. Both figures would then be validated against actual customs import data before committing market-entry budget.

What the model ignores — and why that is intentional

This is a prioritisation heuristic, not a demand forecast. It intentionally excludes:

Tariffs and non-tariff barriers — a 20% import duty fundamentally changes the competitive position but varies by product HS code and bilateral trade agreements.
Local production competition — a market may have high GDP per capita but be self-sufficient in your category.
Logistics cost and market access — shipping cost to a landlocked country can eliminate the margin advantage.
Competitor presence — incumbent exporters may hold large market share already.

Use the output to shortlist markets, then validate the top three to five with real customs and trade-flow statistics (UN Comtrade, ITC Trade Map, national customs databases) before making investment decisions.