Scenarios Exploring Possible Futures

Shared socio-economic pathways

Content

TBD.

Transcript

Appendix

Learning objectives

After this chapter, you should be able to:

  • Explain what a scenario is and how it differs from a prediction.
  • Describe why Earth–economy models rely on families of futures.
  • Interpret scenario outputs as conditional stories about systems.
  • Distinguish baseline, policy, and counterfactual scenarios.
  • Explain how scenarios are used to test robustness under uncertainty.
  • Recognize why “business as usual” is itself a powerful assumption.

Why the future is not a forecast

When people ask:

  • “What will the world look like in 2050?”

They are often expecting a number:

  • a temperature,
  • a GDP level,
  • an emissions path.

Earth–economy modeling answers a different question:

What would the world look like if these assumptions were true?

A scenario is a structured “if–then”:

  • If population grows this way,
  • if technology costs fall at this rate,
  • if policies follow this path,
  • then these outcomes follow.

Scenarios are not predictions.
They are conditional stories about systems.

The anatomy of a scenario

A typical Earth–economy scenario specifies:

  • population growth,
  • income growth,
  • technology trajectories,
  • energy systems,
  • land-use rules,
  • climate policy,
  • and governance capacity.

From these, the model generates:

  • production paths,
  • land allocation,
  • emissions,
  • climate outcomes,
  • ecosystem change,
  • income and welfare,
  • and inclusive wealth.

The scenario is the worldview.
The model is the engine.

Baselines, policies, and counterfactuals

Three kinds of scenarios recur:

1) Baseline (or reference)

  • “What happens if we continue along current trends?”
  • Encodes assumptions about:
    • growth,
    • demography,
    • technology,
    • and policy inertia.

This is not neutral.

A baseline embeds:

  • political expectations,
  • technological optimism or pessimism,
  • and beliefs about governance.

“Business as usual” is itself a hypothesis.

2) Policy scenarios

  • Add a specific intervention:
    • carbon pricing,
    • conservation targets,
    • energy transitions,
    • land-use rules.

Compare:

Baseline world vs policy world

The difference is the estimated effect.

3) Counterfactuals

  • Ask “What if this had not happened?”
  • Used to evaluate:
    • past reforms,
    • historical choices,
    • alternative paths.

They expose the path dependence of development.

Families of futures

Under deep uncertainty, no single scenario is credible.

Instead, Earth–economy modeling uses ensembles:

  • high and low population,
  • fast and slow technology,
  • strong and weak governance,
  • optimistic and pessimistic climate response.

Each run is a plausible world.

What matters is not:

  • “Which is right?”

but:

  • “Which strategies perform well across many?”

This is how scenarios become tools for:

  • robustness,
  • stress testing,
  • and resilience design.

Reading scenario outputs

A scenario output is not a prophecy.

It is a statement of the form:

If the world behaves like this, then these outcomes follow.

Good interpretation asks:

  • Which assumptions drive the result?
  • Which mechanisms dominate?
  • Where do thresholds appear?
  • Who gains and who loses?
  • What happens to stocks over time?

The output is a system narrative.

Scenarios and the Doughnut

The Doughnut defines a region of success.

Scenarios trace paths.

A scenario can:

  • cross ecological ceilings,
  • leave people below social foundations,
  • oscillate between the two,
  • or converge toward the safe-and-just space.

Earth–economy modeling allows us to ask:

Which futures stay inside the Doughnut?
Which policies bend paths toward it?

This is not utopian.

It is computational.

A simple toy example

Using the toy model:

  • Scenario A: no carbon price, no conservation.
  • Scenario B: modest carbon price.
  • Scenario C: carbon price + forest protection.

We may find:

  • A: fast growth, rising carbon, falling forest.
  • B: slower growth, lower emissions, moderate forest loss.
  • C: slightly slower growth, stable carbon, stable forest.

The model does not tell us what will happen.

It tells us:

  • what would follow if each world were real.

Policy is choosing which world to try to build.

Open resources you can remix for this chapter

All are compatible with a CC BY-NC-SA Quarto book.

  • InTeGrate teaching materials (many CC BY-NC-SA)
    Use for: scenario construction and futures thinking.
    https://serc.carleton.edu/integrate/teaching_materials/index.html

  • Natural Resources Sustainability: An Introductory Synthesis (CC BY-NC-SA)
    Use for: systems, resilience, and sustainability framing.
    https://uen.pressbooks.pub/naturalresourcessustainability/

  • Principles of Economics (UMN Libraries Publishing, CC BY-NC-SA)
    Use for: counterfactual reasoning and policy analysis.
    https://open.umn.edu/opentextbooks/textbooks/principles-of-economics

Exercises

  1. Scenario design.
    Write two short scenarios for your country in 2050:

    • one optimistic,
    • one pessimistic.
      Specify at least three assumptions in each.

  2. Baseline critique.
    Find a “business as usual” projection.
    Identify one hidden assumption.

  3. Policy stress test.
    Choose a sustainability policy.
    Describe how it might perform under:

    • fast growth,
    • slow growth,
    • weak governance.

Chapter roadmap

  • Next, you will move from modeling to policy design studios.
  • You will apply Earth–economy thinking to real tradeoffs.
  • The goal is not to “solve” sustainability—but to reason about it like a system designer.