Method, assumptions and conventions

A.1 Status of figures

Each figure and table carries a status. Sourced values are read directly from a published source listed in Annex C. Derived values are arithmetic on sourced inputs, such as shares, unit values, conversions and the implied iron-unit balance; the inputs are always stated. Assumed values are planning assumptions chosen by Cameroon Steel and shown with a range. Illustrative results, such as the scenarios of Chapter 7, combine sourced data and assumptions to describe possible outcomes; they are not forecasts. Indicative project figures are taken from the Cameroon Steel reference configuration RC-1, a planning estimate, and describe a plan that may change [S33].

A.2 Definitions and data sources

Apparent steel use is production plus imports minus exports of finished steel products, as defined by worldsteel [S02]. For Cameroon it is an industry estimate of about 450 kt a year, cross-checked against production and trade data (Chapter 3) [S01][S80][S05]. Per-capita values for Cameroon divide that estimate by the World Bank population estimate for 2025 (29.88 million) [S14]; the provisional census count of 22.7 million is shown as a sensitivity [S15].

Trade data come from two sources. The national statistics institute (INS) publishes annual tonnages and values in FCFA by customs chapter, the latest provisional data covering 2025 [S19][S114][S115][S107][S07]. UN Comtrade provides product-level data in US dollars by HS heading and partner, to 2023 for Cameroon and to 2023 or 2024 for its neighbours [S05][S06]. The two sources differ in valuation and coverage. This paper uses INS for totals and Comtrade for structure, and prefers tonnages to values where the latter look inconsistent with market prices (Chapter 4).

Global and African data use World Steel in Figures 2026 (data finalised 8 June 2026) and the April 2026 Short Range Outlook, which were the latest vintages at the research cut-off of 10 October 2026 [S02][S39]. Overcapacity figures are OECD estimates as published in 2025 and 2026 [S09][S40]. Prices are dated snapshots from the Arab Iron and Steel Union and market reports; no free public series of annual average billet or rebar prices exists [S22].

A.3 Conventions

A.4 Scenario model

The scenarios of Chapter 7 use a single equation: apparent steel use in year t equals projected population in year t multiplied by steel use per person in year t. Population follows the World Bank’s estimates and projections (source 40, updated July 2026), interpolated geometrically between the five-year points [S18]. Steel use per person starts at 15.06 kg in 2025 and grows at a constant rate in each scenario.

Table A.2 assumedScenario assumptions and ranges

Source: Cameroon Steel. Every percentage point of annual growth in steel use per person changes 2040 demand by about 15% (derived).

The 2025 product split is built as follows: reinforcing bar 180 kt and wire rod, wire and nails 38 kt from Ocitram’s demand figures [S03]; flat steel about 95 kt from 2023 imports of cold-rolled (47.5 kt) and coated (30.5 kt) products and the 2022 tonnage of hot-rolled products (18.0 kt) [S05]; sections and structures about 50 kt from 2023 imports of structures (25.7 kt) and an estimate of about 24 kt for sections, derived from their 2023 value of US$26.3m and the 2020 unit value [S05]; tubes about 25 kt from local demand of 14 kt and 2023 imports of welded tubes of 9.5 kt plus a small allowance for seamless tubes [S03][S05]; and other finished steel of about 62 kt as the residual. The split is approximate and is used to show direction, not precise volumes.

The iron-unit gap is calculated as (rebar + wire products + 50% of sections and structures + 31 kt of exports) / 0.95, minus local scrap. Its 2025 value, about 174 kt, compares with actual billet imports of 161.4 kt in 2023 [S05]. Sensitivities: with scrap growing at 6% a year, the base-case gap in 2040 is about 240 kt; with 70% of sections rolled locally it rises by about 25 kt (derived).

The regional envelope applies the same per-capita growth rates to the combined population of Chad, Gabon, the Republic of Congo, Equatorial Guinea and the Central African Republic, which the World Bank projects to grow from 37.5 million to 55.0 million between 2025 and 2040 [S18]. The 2023 starting value is US$190.8m of chapter 72 imports [S06], converted at US$700 to 900 per tonne to 212 to 273 kt. The 2040 envelope is about 335 to 430 kt (low), 450 to 580 kt (base) and 600 to 775 kt (high) (derived).

A.5 Billet cost comparison

Section 8.6 compares, per tonne of billet delivered to a Douala re-roller, the landed cost of an imported billet with the cash cost of a billet melted at Kribi from imported metallics, in three cases (low, central and high) whose inputs are listed in Table 8.2.

The landed import equals (FOB price + freight and insurance) × 1.102 + port handling, clearance and delivery. The factor 1.102 applies the 10% common external tariff and the 0.2% African Union levy to the value including freight [S23][S124].

The Kribi billet equals 1.15 × delivered metallics price × 1.102 + electricity in kWh per tonne × power price ÷ 600 + consumables + labour + maintenance and overheads + delivery. The metallic charge of 1.15 t per tonne of billet follows from the RC-1 metallic yield of 0.88 and a caster yield of about 0.99 [S33]. Electricity per tonne of billet is (450 to 490 + 70) kWh per tonne of liquid steel ÷ 0.99, rounded to 525, 545 and 565 kWh [S125][S33].

The three cases combine favourable, central and unfavourable values of every input; they are not probability bounds. Sensitivities (derived): each US$10 per tonne on the price of metallics moves the cost of a Kribi billet by about US$13; each 10 FCFA per kWh by about US$9; each US$10 per tonne of freight moves the landed import by about US$11; removing the duty on metallics lowers the Kribi cost by US$47 to 52; an exchange rate of 570 FCFA per US dollar instead of 600 adds US$1 to 5 to electricity. Capital charges, working capital and ramp-up losses are excluded, and no investment amount is used anywhere in this paper.

A.6 Limitations

The scenarios use no econometric model, because the data to estimate one for Cameroon do not exist. They do not model prices, substitution between products or the effect of new domestic capacity on imports. They assume that the product mix shifts gradually and that domestic mills continue to supply long products. They should be read as a structured way of asking how large the market and its gaps could become, not as predictions.

Prices in Chapter 8 are point-in-time quotations from different dates and bases. The comparison of the October 2023 homologated price in Douala with October 2026 international quotations is indicative only. Conversion costs, freight and port charges in Cameroon are not published; the billet cost comparison of section 8.6 therefore uses assumed ranges for them, and the re-rolling margin is not estimated.