Module 12 — Integrated Microeconomic Design Studio

Core question

Can you choose the smallest useful model, solve it correctly, test it against evidence, and redesign the institution without hiding the trade-offs?

Learning outcomes

You will be able to:

• combine models while keeping their assumptions distinct;
• move from private choice to equilibrium, welfare, and implementation;
• diagnose a digital platform and a climate-insurance market;
• write a compact design memo with a falsifiable recommendation.

1. Model selection is part of the answer

Do not stack theories decoratively. Add a model only when it explains a margin the previous model omits.

2. The design chain

A complete short answer contains:

1. outcome and counterfactual;
2. primitives and timing;
3. solution concept;
4. one solved mechanism or comparative static;
5. welfare criterion and incidence;
6. evidence tied to one claim;
7. boundary and failure mode;
8. recommendation plus review trigger.

3. Case A — an AI-service marketplace

Environment

A cloud platform hosts foundation-model providers and downstream apps. It supplies compute, ranks services, sells sponsored positions, charges commission, and offers its own model. Users differ in price sensitivity and cannot fully observe reliability; developers can multi-home at a cost.

Map the theory

A small ranking calculation

Three providers bid per click and have estimated relevance:

A score auction ranks A first. But the score embeds only bid and predicted relevance. If reliability, privacy, competition, or organic downstream prices matter, ranking by this score is not a welfare theorem.

Information and incentive problem

Suppose high safety effort costs a provider £1 million, reduces failure probability from 4% to 1%, and each failure imposes expected user loss of £40 million. The social expected benefit of effort is:

Effort creates net expected social value of £0.2 million. Yet the provider chooses it only if liability, reputation, lost ranking, insurance price, or contract reward lets it capture at least the £1 million private cost.

This is a hidden-action externality. A disclosure rule alone may not create the missing incentive; strict liability may create it but can deter entry or be hard to enforce.

Design options

CMA's 2024 mapping of foundation-model partnerships is evidence about structure and possible bottlenecks, not direct proof of harm. Bergemann, Bonatti, and Wu's 2025 model shows that an ad mechanism can affect off-platform product prices, not the realised effect of one platform. Use each source only for the claim it identifies.

4. Case B — climate-risk home insurance

Adverse-selection arithmetic

Two equally common household types face a £100,000 loss:

• low risk: p_L=0.02, fair expected loss £2,000;
• high risk: p_H=0.10, fair expected loss £10,000.

If risk is unobserved, the break-even pooling premium is:

If low-risk households value coverage below £6,000 and exit, the remaining pool costs £10,000 per policy. A premium rise can therefore worsen the pool rather than simply reduce quantity along a fixed demand curve.

Add hidden prevention

Home hardening costs £1,500 and reduces high-risk loss probability from 10% to 7%. Expected loss falls by:

Prevention is socially valuable, but full insurance can weaken the household's private return if the action is unobserved. Inspection, premium discount, deductible, or public grant can restore incentives, each with administrative and distributional costs.

Add classification and regulation

Richer parcel-level risk models can align premium with expected loss and reward prevention, but can also make high-risk homes unaffordable and capitalise climate risk into property values. Coarse regulated classes provide cross-subsidy yet can induce insurer selection or withdrawal.

The Boomhower et al. working paper documents heterogeneous wildfire-risk classification and potential adverse selection among insurers. It does not itself choose the social allocation of catastrophic risk among households, insurers, reinsurers, and taxpayers.

Policy menu

No single instrument solves risk transfer, prevention, affordability, land use, and aggregate climate externality.

5. Compare the cases

The common lesson is to model who adapts to the rule. A policy that holds behaviour fixed is often an accounting exercise, not an equilibrium analysis.

6. Evidence-to-claim map

7. Capstone design memo

Choose one market—AI services, insurance, school choice, organ exchange, electricity, digital advertising, or another approved setting—and write 1,500 words:

1. state the institution and counterfactual;
2. map agents, types, actions, information, timing, and constraints;
3. solve one benchmark model;
4. identify one strategic or informational failure;
5. evaluate efficiency and distribution separately;
6. use two primary or peer-reviewed sources;
7. propose a rule and one implementation safeguard;
8. name a measurable result that would trigger revision.

Graduate extension: prove an IC, stability, or existence result; compare at least two solution concepts; or estimate/simulate one equilibrium response.

Final check

• What is assumed rather than observed?
• Which equilibrium concept fits the timing and information?
• What behaviour changes when the rule changes?
• Which welfare criterion ranks outcomes?
• Who gains, loses, enters, exits, or becomes unmeasured?
• What evidence could overturn the recommendation?

If those six answers are visible, the analysis is advanced microeconomics rather than a list of advanced terms.