Markets
Supply-Demand Models
For most commodities, supply and demand balance on a timescale of months. For critical minerals, the timescale is years or decades - a mine takes 10–17 years from discovery to production, while EV adoption can accelerate far faster than that. Modelling this asymmetry is one of the central analytical challenges in commodity economics today.
Avg mine development timeline
16 yrs
Discovery to first production, USGS data
IEA lithium demand range by 2040
3–10×
Current demand, across NZE vs STEPS scenarios
Projects that miss initial schedule
~60%
Historical analysis of large mining projects
China share of Li-ion processing
>70%
Binding midstream constraint in most models
Lithium Market Scenario Explorer
Adjust the key variables that drive lithium supply-demand models and see how the projected 2030 market balance shifts. This is a simplified illustrative model - real analyst models contain hundreds of asset-level inputs, but these four drivers explain most of the variance.
Adjust scenario inputs
LFP uses ~40% more Li per kWh than NMC but eliminates Co/Ni
Reflects the % of announced projects that deliver on time
Direct lithium extraction from brine - nascent but watched closely
Projected 2030 market balance
Surplus / Deficit
- kt LCE
Balance signal
-
Projected balance 2025–2030 (kt LCE)
2030 demand
-
kt LCE
2030 supply
-
kt LCE
Incentive price signal
-
Illustrative model only. Base values calibrated to approximate 2024 analyst consensus (IEA APS, BMI base case). All figures in thousand tonnes lithium carbonate equivalent (kt LCE). Not for investment or commercial use.
Reading a Cost Curve
The supply cost curve is one of the most powerful tools in commodity economics. It ranks every source of supply by the cost per tonne of producing it - and the intersection with demand determines the marginal (price-setting) producer.
Stylised lithium cost curve (illustrative)
Cost ($/t LCE)
Infra-marginal producers
High-quality brines (Atacama, Salar) earn supernormal margins. They supply even at prices well below today's incentive price.
Marginal producers
The intersection of the demand line with the cost curve sets the market-clearing price. These producers earn near-zero economic rent.
High-cost / unbuilt
Clay and undeveloped projects need higher prices to be viable. They become "incentive" supply if demand grows past current capacity.
The Six-Stage Modelling Process
How professional analysts build a supply-demand model from first principles, and the two stages where most forecast errors originate.
End-use decomposition
DemandBreak total demand into application segments (EVs, grid storage, consumer electronics, industrials). Each segment is modelled separately with its own adoption curve.
Technology & intensity assumptions
DemandApply mineral intensity per unit (kg Li per kWh, kg NdPr per motor). Model chemistry mix evolution - e.g. NMC→LFP shift reduces Co/Ni, thrifting lowers kg/kWh over time.
Asset-level supply database
Supply Common error sourceCatalogue every producing mine and credible project with nameplate capacity, ramp schedule, probability weight, and unit cost. Historical data shows systematic optimism bias in ramp timelines.
Processing & midstream
Supply Common error sourceMine output ≠ market supply. Track conversion capacity (e.g. spodumene → Li hydroxide, cobalt hydroxide → sulfate) separately - often the binding constraint on effective supply.
Calculate market balance
BalanceSubtract total supply from total demand year-by-year. Positive = surplus (price pressure downward). Negative = deficit (price pressure upward, risk of shortfall).
Cost curve & incentive price
PriceRank supply by marginal cost. Long-run price floors at the cost of the marginal tonne needed to balance supply. Deficits signal price must rise to incentivise new capacity.
Why models consistently overestimate supply
Analysis of historical project forecasts across mining shows a consistent pattern: announced project timelines are over-optimistic by an average of 2–4 years, and capital costs underestimated by 30–60%. Modellers must apply probability weights and schedule adjustments to avoid "paper supply" - capacity that exists in a database but not in the ground. Projects in early-stage permitting typically receive 10–30% probability weights in rigorous models; those with completed feasibility studies and secured financing receive 70–90%.
Who Builds These Models
Six institutions produce the most widely cited supply-demand models for critical minerals, each with different methodologies, coverage, and access models.
Focus minerals
Energy transition minerals: Li, Co, Ni, Cu, REEs, graphite
Flagship product
Critical Minerals Market Review (annual)
Methodology
Top-down scenario + bottom-up asset database
Scenarios published
Strength
Policy credibility, broad scenario range, free access
Limitation
Annual cadence; less granular on specific assets
Focus minerals
Lithium-ion battery supply chain: Li, Co, Ni, graphite, Mn
Flagship product
Lithium-ion battery & EV forecast
Methodology
Bottom-up cell-to-mine flow model
Scenarios published
Strength
Highest granularity on battery chemistry & cell demand
Limitation
Subscription only; battery-focused rather than all minerals
Focus minerals
Broad metals & mining coverage; all critical minerals
Flagship product
Metals & Mining Research Suite
Methodology
Asset-level databases + integrated price models
Scenarios published
Strength
Widest asset coverage; long track record via Roskill
Limitation
Premium pricing; some minerals less granular than BMI
Focus minerals
All minerals on U.S. critical minerals list
Flagship product
Mineral Commodity Summaries (annual)
Methodology
Production statistics + basic balance estimates
Scenarios published
Strength
Free, authoritative production/reserve data
Limitation
No forward projections; 1-year lag on data
Focus minerals
Metals, mining & battery materials
Flagship product
Battery Raw Materials Service
Methodology
Asset-level supply + sector demand modelling
Scenarios published
Strength
Integration with price assessments and financial data
Limitation
Heavy enterprise focus; expensive
Focus minerals
Steel, aluminium, base metals, battery materials
Flagship product
CRU Market Outlook series
Methodology
Bottom-up cost curve + balance models
Scenarios published
Strength
Strong cost-curve methodology; steel/alloys depth
Limitation
Less coverage of specialty REEs and minor metals
Scenario Analysis and the Uncertainty Problem
The IEA's projections for lithium demand in 2040 vary by a factor of three or more depending on which scenario is used. This is not a failure of modelling - it is an honest representation of genuine uncertainty. The energy transition's speed depends on policy continuity, cost trajectories, consumer behaviour, and geopolitical conditions that no model can reliably forecast a decade out.
This is why responsible supply-demand modelling focuses less on the central forecast and more on the key uncertainties. Which variables drive the widest range of outcomes? What conditions would need to be true for a supply deficit to emerge by 2028? What is the fastest-plausible path for DLE technology to relieve brine supply constraints? Structuring analysis around these questions produces more decision-relevant insights than a single point forecast.
For market participants, the practical implication is that any supplier of critical mineral analysis claiming narrow forecast confidence bands should be viewed with scepticism. See Benchmarks and PRAs for how price reporting data feeds into these models, and Trade Flows and Customs Codes for how trade statistics are used to calibrate and validate supply estimates.
Related Market Topics
Substitution and Thrifting
How demand models account for material switching and intensity reduction over time.
Stockpiling and Inventory Cycles
The role of inventories in bridging short-term supply-demand imbalances.
Trade Flows and Customs Codes
How trade data calibrates and validates supply-demand model estimates.
Demand Growth
The structural demand drivers reshaping critical mineral markets this decade.