> For the complete documentation index, see [llms.txt](https://help.modelreef.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.modelreef.io/help/drivers-variables-and-timing/economic-drivers.md).

# Economic Drivers

This article focuses on **economic drivers** in Model Reef.

You will learn:

* What counts as an economic driver.
* How to store economic drivers in the Data Library.
* How to connect them to variables and valuation logic.
* Patterns for using market and macro data safely.

Economic drivers describe external or pricing related inputs that influence revenue, costs and valuation.

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### What is an economic driver

Economic drivers typically include:

* **Prices and tariffs**
  * List prices, per unit rates, contract pricing tiers.
* **FX rates**
  * Currency pairs such as GBP to USD, EUR to GBP.
* **Inflation and escalation indices**
  * General inflation, wage inflation, rent escalators.
* **Market indices and benchmarks**
  * Equity indices, sector indices, commodity indices.
* **Interest rates and yields**
  * Base rates, risk free rates, credit spreads, curves.

These drivers are numeric time series that influence the economic environment of the model.
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### Storing economic drivers in the Data Library

Each economic driver is stored as a Data Library entry, for example:

* `Driver - Price - Subscription - Enterprise`.
* `Driver - FX Rate - GBP to USD`.
* `Driver - Inflation - General - UK`.
* `Driver - Index - Commodity Basket`.
* `Driver - Base Rate - Central Bank`.

When you create or import an economic driver, you specify:

* Name and description.
* Frequency (daily, weekly, monthly, etc.).
* Units (for example GBP, index points, percentage).
* Tags such as `FX`, `Inflation`, `Market`, `Rates`.

Economic drivers can come from:

* Manual inputs.
* CSV or Excel imports.
* Stock ticker fundamentals or market data feeds.
* Google Finance, Yahoo style or similar APIs.
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### Using economic drivers in revenue and cost variables

Common patterns include:

* **Price based revenue**
  * `Revenue = Units * PriceDriver`.
  * Example: subscriptions charged per seat at a price that escalates annually.
* **FX translation**
  * `Revenue = ForeignRevenue * FXRate`.
  * `COGS = ForeignCost * FXRate`.
  * Useful when modelling foreign currency operations in a single reporting currency model.
* **Inflation adjusted costs**
  * `Opex = BaseCost * InflationIndex`.
  * `Staff Cost = BaseSalary * WageInflationIndex`.

Economic drivers allow these relationships to be expressed once and reused across the model.
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### Using economic drivers in capex, debt and valuation

Economic drivers also play a role in:

* **Capex modelling**
  * Linking capex estimates to commodity or construction cost indices.
  * Scaling future project costs with inflation drivers.
* **Debt and interest**
  * Indexing loan interest rates to base rates plus spreads.
  * Testing the impact of higher rate curves on interest expense.
* **Valuation**
  * Using risk free rates and spreads as inputs into discount rate assumptions.
  * Linking scenario discount rates to economic driver series.

Economic drivers provide a bridge between market conditions and cashflow projections.
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### Scenario design with economic drivers

When designing scenarios, you can:

* Change economic drivers while keeping operational drivers fixed to simulate macro shifts.
* Or hold economic drivers constant and vary operational drivers to simulate execution risk.
* Or change both to explore combined effects.

Examples:

* Downside scenario with lower price growth and higher interest rates.
* Upside scenario with stronger market growth and favourable FX.
* Stress test scenario with a shock to commodity prices.

Because drivers are scenario specific at model level, each scenario can have its own driver paths.
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### Good practice for economic drivers

Guidelines:

* Keep economic drivers **separate** from accounting variables.
* Use clear naming for scope and units.
* Document sources and update cadence in notes.
* Avoid over fitting to noisy market data; focus on drivers that materially affect decisions.
* Prefer smooth, scenario based paths over raw daily noise for long term planning.

This keeps models robust while still responsive to key economic assumptions.
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## Related articles

* [Mine/Well Production Forecasts](/use-cases/mining-energy-and-natural-resources/mine-well-production-forecasts.md)
* [Build an LBO Model](/how-tos/investment-and-transactions/build-an-lbo-model.md)
* [Driver Escalation Rules](/help/drivers-variables-and-timing/driver-escalation-rules.md)
* [Modifier Driver Fields](/syntax/drivers-syntax/modifier-driver-fields.md)