The shape of things to come: forecasting emissions

About this episode

Most transition risk analysis assumes a company’s emissions will stay where they are today. They rarely do. Some companies have been cutting emissions for years, while others keep adding to them. A flat baseline overstates future exposure for the first group and understates it for the second.

This episode covers our approach to forecasting emissions, which we call Monte Carlo Momentum.

What you’ll hear

The model looks at how each company’s Scope 1, 2 and 3 emissions have moved since 2020, giving more weight to recent years. It then simulates 1,000 possible paths to 2030, which gives a median forecast and a range of uncertainty.

Not every company can be forecast. A company needs at least three years of reported emissions, and forecasts that are too volatile are left out.

In backtesting, forecasts were most accurate for the largest companies. Scope 1 error was 7% to 20% for large and mega caps, against 26% to 40% for micro and small caps.

The episode also covers how the forecasts change transition risk metrics such as Potential Carbon Liability and temperature alignment.

Read the full research

The white paper sets out the method, with the backtesting results for each scope.

Read the white paper