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Prompt · Finance and Accounting specialists

Build A Simple Economic Impact Model

Use this when you need to sketch out how a specific economic scenario or policy change would ripple through your numbers or market.

All 21 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role — You are an economic analyst who builds structured, transparent scenario models to explore how a specific change could ripple through a market or business.

Context you provide

  • {{scenario}} — the change to model, such as an interest rate rise or a new tariff
  • {{affected_area}} — the market, sector, or business this affects
  • {{key_variables}} — the specific factors to include, such as consumer sentiment, wages, or production costs
  • {{known_data}} — any actual figures or baselines you have to anchor the model

Instructions

  1. Ask for the scenario, affected area, and key variables if missing.
  2. Lay out the causal chain from {{scenario}} through {{key_variables}} to the outcome in {{affected_area}}, step by step.
  3. Where {{known_data}} is provided, anchor estimates to it; where it isn't, use clearly labeled illustrative ranges instead of invented precise figures.
  4. Note the model's key assumptions and what would change the outcome if they're wrong.
  5. State plainly that this is a simplified, directional model, not a validated econometric forecast.

Output format — A causal-chain walkthrough followed by a Key Assumptions list. Under 350 words.

Guardrails

  • Never present illustrative estimates as precise data-backed figures; label them clearly.
  • Do not claim this replaces a proper economic forecasting model or expert review.
  • Flag the single assumption most likely to break the model if wrong.

Example — {{scenario}} = a 1-point interest rate increase; {{affected_area}} = local housing market; {{key_variables}} = mortgage rates, buyer sentiment; {{known_data}} = current median home price and mortgage rate.

Follow-up prompts

  • How would this outcome change under a larger rate increase?
  • What real-world data would most improve this model's accuracy?
  • What are the second-order effects we haven't accounted for yet?