Competition Law and Economic Simulation Infrastructure Monopolies

1. Introduction

Economic simulation infrastructure monopolies refer to situations where one undertaking obtains substantial market power over the infrastructure, data, software, computing resources, models, or platforms required to create and operate economic simulations.

Economic simulation infrastructure may include:

macroeconomic modelling platforms;

computational economic models;

digital-twin infrastructure for markets;

large-scale economic datasets;

cloud computing used for economic modelling;

specialised simulation software;

AI models used for economic forecasting;

econometric databases;

financial-market simulation systems;

agent-based modelling platforms;

scenario-analysis infrastructure;

economic forecasting APIs.

The competition-law concern arises when control over such infrastructure enables an undertaking to exclude competitors, raise rivals' costs, restrict access, tie complementary services, discriminate between users, or leverage infrastructure power into downstream markets.

A simple structure is:

Data + computing + models + software + APIs + distribution → economic simulation infrastructure → downstream economic analysis

The central competition-law question is:

When does control over economic-simulation infrastructure become market power capable of restricting effective competition?

2. Meaning of an Economic Simulation Infrastructure Monopoly

An ordinary monopoly may involve control over a physical product.

An economic simulation infrastructure monopoly is more complex because the bottleneck may consist of several interconnected resources.

Example

Company A controls:

a unique macroeconomic dataset;

the most widely used simulation software;

specialised computing infrastructure;

proprietary economic models;

an API used by financial institutions.

Competitors may technically be able to develop their own products, but if reproducing all these components is extremely costly, Company A may possess significant infrastructural market power.

3. Components of Simulation Infrastructure

A. Data

Economic simulations depend heavily on:

GDP data;

inflation data;

employment statistics;

trade data;

consumer data;

financial data;

business data;

historical datasets.

B. Computational infrastructure

Large simulations may require:

cloud computing;

GPUs;

high-performance computing;

distributed computing;

storage;

networking.

C. Software

Examples include:

econometric software;

modelling engines;

simulation environments;

optimisation systems;

statistical platforms.

D. Models

A company may control proprietary:

forecasting models;

behavioural models;

macroeconomic models;

financial-risk models.

E. Interfaces

APIs can determine whether third-party developers can access:

data;

models;

simulation outputs;

computational functions.

4. Why Infrastructure Can Create Market Power

Economic simulation infrastructure can generate several forms of competitive advantage.

1. High fixed costs

Developing infrastructure may require substantial investment.

2. Economies of scale

The average cost of providing simulation services may decrease as usage increases.

3. Data advantages

More users may generate more information.

4. Network effects

Developers may prefer the platform that already has the largest ecosystem.

5. Switching costs

Customers may become dependent on:

proprietary formats;

APIs;

workflows;

models;

historical data.

6. Learning effects

The platform may improve through accumulated usage.

5. Monopoly Versus Dominance

An important competition-law distinction is:

Economic simulation infrastructure monopoly does not necessarily mean unlawful conduct.

A company may become dominant because it has:

superior technology;

better software;

lower costs;

better models;

greater investment;

first-mover advantages.

Competition law generally does not prohibit success through competition.

The legal concern arises when market power is maintained or exploited through anti-competitive conduct.

6. Relevant Market Definition

The relevant market could be defined narrowly or broadly.

Possible Market 1

Economic simulation software

Possible Market 2

Economic modelling infrastructure

Possible Market 3

Economic forecasting services

Possible Market 4

Specialised economic datasets

Possible Market 5

High-performance computing for economic simulation

Possible Market 6

Simulation APIs

Possible Market 7

Cloud-based economic modelling platforms

The correct market definition depends on:

substitutability;

customer needs;

technical characteristics;

pricing;

switching costs;

geographic scope;

availability of alternatives.

7. Essential-Facilities Problem

One of the most important competition-law issues is whether simulation infrastructure constitutes an essential facility.

Suppose:

Company A controls a computing platform that competitors allegedly cannot economically reproduce.

Company B requests access.

A refuses.

The competition question becomes:

Is the infrastructure merely valuable, or is it genuinely indispensable for effective competition?

The traditional essential-facilities doctrine imposes a high threshold.

8. Refusal to Deal

A dominant infrastructure provider may have a legitimate interest in deciding with whom it does business.

But competition law may intervene in exceptional circumstances where refusal:

eliminates effective competition;

concerns an indispensable input;

cannot be objectively justified;

prevents competitors from operating in a downstream market.

9. Interoperability

Interoperability is particularly important.

Suppose a dominant simulation platform uses a proprietary format.

Competitors cannot easily:

import models;

export datasets;

migrate simulations;

access APIs;

transfer historical results.

This may create technical lock-in.

Competition concerns can arise if interoperability restrictions are used strategically to exclude competing platforms.

10. Tying and Bundling

A dominant simulation-infrastructure provider might require customers to purchase:

simulation software + cloud computing

or:

economic data + proprietary modelling platform.

This can make it difficult for competitors specialising in only one component to compete.

Potential theories include:

tying;

bundling;

leveraging;

foreclosure.

11. Self-Preferencing

Consider a vertically integrated platform:

Infrastructure → simulation platform → economic consultancy

The infrastructure provider may give its own downstream consultancy:

faster computing;

better APIs;

greater data access;

privileged model access;

preferential technical support.

Competitors may receive inferior access.

This can create a vertical foreclosure problem.

12. Discriminatory Access

A dominant infrastructure provider might provide:

Its own affiliate

unlimited API access;

high computational limits;

real-time data;

premium technical support.

Competitors

delayed data;

lower computing limits;

restricted APIs;

higher fees.

Such discrimination may become competition-law relevant when it lacks objective justification and has exclusionary effects.

13. Excessive Pricing

Another possible theory is excessive pricing.

Suppose a company controls an indispensable economic-simulation infrastructure and charges extremely high access fees.

Competition law may ask whether:

the price is excessive;

the price is unfair;

the undertaking has substantial market power;

customers lack realistic alternatives.

This doctrine is generally difficult to establish and should not be assumed merely because infrastructure is expensive.

14. Predatory Pricing

The opposite situation is possible.

A dominant platform could temporarily offer simulation infrastructure:

below cost

in order to eliminate smaller competitors.

After competitors exit, prices could then rise.

This can raise predatory-pricing concerns, although proving the necessary economic elements can be demanding.

15. Exclusive Dealing

A dominant infrastructure provider could require customers to agree:

"You may use our simulation infrastructure only for economic modelling and may not use competing infrastructure."

Long-term exclusivity may increase switching costs and prevent rivals from obtaining sufficient scale.

16. Data as an Infrastructure Bottleneck

The most important bottleneck may not actually be computing.

It may be data.

For example:

Historical transaction data + proprietary economic indicators + real-time market data

could provide a major advantage in simulation accuracy.

If competitors cannot obtain comparable datasets, the data layer can become an infrastructural bottleneck.

17. AI and Economic Simulation

AI makes the issue more complicated.

A modern simulation ecosystem could look like:

Data → foundation model → economic model → simulation engine → AI prediction → automated decision

The company controlling the AI/model layer may also control the underlying infrastructure.

This can create:

data advantages;

computational advantages;

model advantages;

ecosystem effects;

API dependence.

Competition authorities may therefore need to analyse multi-layer market power, rather than examining only one product.

18. Case Law

There is no mature body of cases specifically labelled "economic simulation infrastructure monopolies." The following cases are therefore important comparative authorities because they establish principles concerning infrastructure, interoperability, data, refusal to supply, tying, ecosystem leverage and dominance.

Case 1: United Brands v Commission

Case 27/76

United Brands is a foundational EU authority on dominance.

Principle

Dominance involves a position of economic strength enabling an undertaking to behave to an appreciable extent independently of competitors and customers.

Application

An economic-simulation infrastructure provider could potentially be dominant where:

alternatives are weak;

switching costs are high;

infrastructure is difficult to reproduce;

customers are dependent on the system.

Key lesson

Infrastructure control must be assessed through actual market power, not simply ownership of technology.

19. Case 2: Bronner v Mediaprint

Case C-7/97

This is one of the most important authorities for refusal to provide access to infrastructure.

Principle

The Court applied a strict test before requiring a dominant undertaking to provide access to infrastructure.

Among the important considerations is whether the facility is genuinely indispensable and whether alternative solutions are realistically available.

Application

A simulation platform should not automatically be classified as an essential facility merely because competitors would benefit from access.

Key lesson

Useful infrastructure is not necessarily indispensable infrastructure.

20. Case 3: Commercial Solvents

Joined Cases 6/73 and 7/73

Commercial Solvents concerned upstream control and downstream competition.

Principle

A dominant undertaking controlling an important upstream input cannot use that position to eliminate downstream competition in circumstances covered by Article 102.

Application

Suppose:

Company A controls the dominant simulation engine.

and also operates:

Company A Economic Advisory Services.

If A restricts competing consultants' access to the simulation engine, upstream infrastructure power could potentially be leveraged into the downstream market.

Key lesson

Control of an upstream infrastructure can affect downstream competition.

21. Case 4: Microsoft v Commission

Case T-201/04

Microsoft involved interoperability information and Microsoft's position in software markets.

Principle

The case is particularly important for understanding:

interoperability;

technical information;

platform ecosystems;

leveraging;

foreclosure.

Application

An economic simulation platform may become a bottleneck if competitors cannot effectively interoperate with:

its data;

models;

APIs;

file formats.

Key lesson

Technical interoperability can be a competition parameter.

22. Case 5: Google Shopping

Case T-612/17; C-48/22 P

Google Shopping concerned the treatment of competing services within Google's search ecosystem.

Principle

A dominant platform's treatment of competing services can raise Article 102 concerns where its conduct produces exclusionary effects.

Application

Suppose an economic simulation platform operates its own:

forecasting marketplace.

If it uses control over the infrastructure to favour its own forecasting service over competing services, the Google Shopping framework provides an important analogy.

Key lesson

Infrastructure neutrality can become important when a platform competes with businesses dependent on that infrastructure.

23. Case 6: Google Android

Case T-604/18

Google Android concerned contractual arrangements surrounding Android and Google's digital ecosystem.

Principle

Dominance in one layer can potentially be leveraged through contractual arrangements into connected markets.

Application

An economic simulation infrastructure provider could potentially require:

cloud customers to use its modelling software;

software users to purchase its datasets;

API users to adopt its downstream services.

Key lesson

Ecosystem contracts can extend infrastructure power into neighbouring markets.

24. Case 7: Tetra Pak II

Case C-333/94 P

Tetra Pak is an important authority on leveraging and tying.

Principle

Dominance in one market can, under appropriate circumstances, support abusive conduct affecting another market.

Application

A dominant simulation-data provider might bundle:

proprietary economic data + proprietary simulation software.

Competitors supplying only software could potentially be disadvantaged.

Key lesson

Control over one indispensable or powerful layer can be leveraged into another layer.

25. Case 8: Intel

Case C-413/14 P

Intel concerned exclusionary rebates and the assessment of competitive effects.

Principle

The Court emphasised the importance of examining whether allegedly exclusionary conduct is capable of restricting competition, particularly where effects-based analysis is appropriate.

Application

An infrastructure provider offering:

substantial discounts for exclusive use

could potentially raise concerns if those conditions foreclose competing simulation platforms.

Key lesson

Commercial discounts can become competition concerns when linked to exclusionary conditions.

26. Case 9: Eturas

Case C-74/14

Eturas involved a common electronic booking platform used by competing businesses.

Principle

Digital infrastructure can facilitate coordination among competitors.

Application

An economic-simulation platform could potentially become a mechanism through which competitors obtain common information concerning:

prices;

forecasts;

production;

capacity;

strategic plans.

Key lesson

Shared digital infrastructure can create both efficiency and coordination risks.

27. Case 10: AC-Treuhand

Case C-194/14 P

AC-Treuhand concerned the role of an undertaking facilitating cartel activity.

Principle

Competition-law responsibility can extend beyond conventional sellers where an undertaking knowingly facilitates anti-competitive conduct.

Application

A simulation-platform operator could not assume that being merely an infrastructure provider automatically eliminates competition-law exposure.

Key lesson

Infrastructure providers can become relevant to competition law when their services facilitate restrictive conduct.

28. Case-Law Table

29. Economic Simulation Infrastructure and Merger Control

Merger control can become particularly important.

Imagine:

Company A

Controls the largest economic dataset.

Company B

Controls the leading simulation engine.

Company C

Controls cloud infrastructure.

A merger involving two of these companies could combine:

Data + computation + modelling

This may create a much stronger competitive position than either company possesses separately.

Potential theories include:

horizontal concentration;

vertical foreclosure;

input foreclosure;

customer foreclosure;

data accumulation;

interoperability restrictions;

ecosystem entrenchment.

30. Killer Acquisitions

A smaller economic-modelling startup may have:

innovative algorithms;

specialised datasets;

novel simulation technology.

A dominant infrastructure provider could acquire it before it becomes a serious competitor.

Even where the startup has little current revenue, competition authorities may consider whether it represents an important future competitive constraint, subject to the applicable merger-control rules.

31. Switching Costs

Simulation platforms can create particularly high switching costs because users may have:

thousands of historical models;

proprietary code;

stored datasets;

customised workflows;

trained employees;

API integrations;

regulatory approvals;

internal documentation.

Therefore:

Technical compatibility can be as important as price.

A platform that makes migration artificially difficult may strengthen its market position.

32. Interoperability Remedies

Competition authorities could potentially require:

open APIs;

data portability;

standardised formats;

model portability;

technical documentation;

interoperability protocols.

Such remedies seek to reduce artificial switching costs while allowing firms to compete on the quality of their underlying technology.

33. Data-Access Remedies

Possible remedies include:

Non-discriminatory access

Equivalent customers receive equivalent access.

FRAND-type licensing

Access is offered on fair, reasonable and non-discriminatory terms where legally appropriate.

Data portability

Customers can export their historical simulation information.

API access

Third-party providers can integrate with the infrastructure.

Independent governance

A neutral body may supervise access arrangements.

34. The Problem of Over-Regulation

Competition authorities should also avoid forcing companies to disclose everything.

Excessive compulsory access could:

reduce innovation incentives;

undermine intellectual property;

expose trade secrets;

reduce investment in infrastructure;

create cybersecurity risks.

This is why Bronner remains important.

The fact that competitors would prefer access is insufficient.

35. Economic Simulation Infrastructure and Public Interest

Economic simulation infrastructure may have significant public importance because simulations can be used for:

monetary policy;

fiscal policy;

financial stability;

climate policy;

energy planning;

infrastructure investment;

economic forecasting.

This creates a difficult boundary between:

private competition law

and

public economic infrastructure policy.

A government may decide that certain datasets or computational systems should be publicly accessible for reasons beyond competition law.

That is a regulatory policy decision and should not automatically be treated as an Article 102 obligation.

36. Competitive Risks by Layer

37. Economic Simulation Infrastructure as a Multi-Sided Market

A simulation platform may connect:

economists;

universities;

governments;

financial institutions;

businesses;

software developers;

data providers.

This creates multi-sided network effects.

More users may attract:

more developers → more models → more customers → more data → better simulations → more users.

This can make market entry increasingly difficult over time.

38. Competition Law and Dynamic Efficiency

Economic simulation markets require special attention to dynamic competition.

Competition authorities should consider:

innovation;

future technologies;

AI development;

model improvements;

new datasets;

cloud alternatives;

future entrants.

A company with a high market share today may face substantial technological competition tomorrow.

Conversely, a seemingly small infrastructure advantage may become much more significant if network effects create rapid market tipping.

39. Practical Legal Test

When analysing an economic-simulation infrastructure monopoly, use the following sequence:

Step 1 — Define the market

What exactly is the infrastructure?

Step 2 — Identify the bottleneck

Is it:

data?

computing?

software?

models?

APIs?

distribution?

Step 3 — Measure market power

Consider:

market share;

barriers to entry;

switching costs;

network effects;

substitutes.

Step 4 — Identify conduct

Is there:

refusal to supply?

tying?

discrimination?

exclusivity?

self-preferencing?

excessive pricing?

predatory pricing?

Step 5 — Determine effects

Does the conduct:

raise rivals' costs?

exclude competitors?

reduce innovation?

increase switching costs?

reduce consumer choice?

Step 6 — Examine justification

Are there:

security reasons?

privacy requirements?

intellectual-property concerns?

technical limitations?

efficiency benefits?

Step 7 — Consider remedy

Would:

interoperability;

portability;

access;

divestiture;

behavioural restrictions

restore effective competition?

40. Key Legal Principles

Principle 1

Infrastructure ownership is not itself unlawful.

Principle 2

Dominance is not itself prohibited; abuse of dominance is.

Principle 3

Not every valuable dataset is an essential facility.

Principle 4

Interoperability can be a significant competitive parameter.

Principle 5

Vertical integration can create efficiency as well as foreclosure risks.

Principle 6

Digital infrastructure can facilitate both competition and coordination.

Principle 7

Merger control can address structural risks before exclusionary conduct occurs.

Principle 8

Remedies should be proportionate and should preserve incentives for innovation.

41. Exam-Ready Conclusion

Economic simulation infrastructure monopolies represent an emerging form of digital and knowledge-based market power. Unlike a conventional monopoly over a physical product, the bottleneck may involve a combination of data, computing power, software, proprietary models, APIs, technical standards and network effects.

Competition law can address the resulting concerns through established doctrines concerning dominance, refusal to supply, essential facilities, interoperability, tying, exclusive dealing, discriminatory access, self-preferencing, vertical foreclosure and merger control. The principles in United Brands, Bronner, Commercial Solvents, Microsoft, Google Shopping, Google Android, Tetra Pak II, Intel, Eturas and AC-Treuhand provide useful comparative frameworks.

The most important limitation is that economic simulation infrastructure is not automatically an essential facility merely because it is valuable or expensive to reproduce. Competition intervention requires careful examination of market definition, dominance, indispensability, competitive effects and objective justification.

Ultra-Basic Formula

Critical simulation infrastructure + substantial market power + exclusionary conduct + competitive foreclosure = potential competition-law problem.

One-Line Revision Rule

Competition law does not prohibit a monopoly over economic-simulation infrastructure as such; it targets the acquisition, maintenance or exercise of infrastructure-based market power where the conduct unlawfully restricts effective competition.