Show HN: Estimating startup viability using Nobel Prize economics

I was on holiday recently and I thought it might be fun and broadening exercise to start learning more about the most recent Nobel prize winners for economics reasearch. As it turns out their work was about looking at various ways of estimating and predicting the value of entering new markets with innovation, which is a very interesting space.

Most advice on how to fund and start a start-up relies on pattern-matching: “Raise 18 months of runway.” “Get to $100K MRR before Series A.” These heuristics can help, but they don’t consider the wider picture of the market you might be thinking of entering.

The Aghion-Howitt quality ladder model—the framework behind Philippe Aghion and Peter Howitt’s 2025 Nobel Prize in Economics—explains innovation and creative destruction at a fundamental level. I’ve built an interactive calculator that applies this Nobel Prize-winning theory to evaluate startup viability with economic rigor.

The Economic Foundation

The Aghion-Howitt framework (1992) treats innovation as discrete quality improvements that replace existing products. When you build a startup, you’re creating a quality improvement over existing solutions. The framework helps answer: Is this improvement valuable enough to justify the cost of building it?

The Core Equation

The model centers on a simple inequality:

Where:

• EV = Expected value of your business (survival probability × business value), this nomenclature is easier for me to understand
• wη = Entry cost to build and launch

Viability reduces to a simple question: can expected returns justify upfront investment?

Let’s break down each component:

Business Value (V)

Your business value is determined by the perpetuity formula adjusted for growth:

Where:

• π = Annual profit at Series A scale (target customers × profit per customer)
• r* = Adjusted discount rate accounting for displacement risk and churn
• g = Growth rate from innovation (g = λ·log(γ))

The adjusted discount rate accounts for real risks:

This means higher displacement risk and customer churn directly reduce your business value.

Expected Value

Your expected value is survival probability multiplied by business value:

Where λ represents displacement risk—the probability that competitors or market changes make your solution obsolete. Higher displacement risk means lower expected value.

Entry Cost (wη)

The actual capital required to build and launch:

For UK startups, this includes:

• Employee salaries with employer NI (typically 1.2-1.4x base salary), 1.15 if you’re running lean
• Infrastructure (legal, accounting, software, initial tech)
• Time to build (runway in months)

The Calculator

Try the interactive calculator below with your startup idea. Start with a preset to see how different archetypes perform, then adjust parameters to model your specific situation.

What the Model Teaches Us

After experimenting with the calculator, several patterns emerge about startup viability:

Churn Destroys Value Exponentially

At 3% monthly churn, only 69% of customers remain after a year. This cuts LTV by more than half compared to 2% churn (78% retention). Retention trumps acquisition for most businesses.

Gross Margin Matters Immensely

Sub-60% gross margins prevent SaaS-level valuations. You’ll be valued like a services or logistics business (lower multiples), affecting fundraising, exit potential, and strategic flexibility.

Defensibility Compounds Over Time

A business with 60% switching costs and 40% network effects achieves 46% defensibility, dramatically reducing effective displacement risk. Early moats matter more than fast growth.

Entry Costs Arrive Before Revenue

Entry cost (wη) arrives upfront before you generate revenue. A £50k reduction in entry cost has the same impact as increasing expected value (EV) by £50k, but is usually faster to achieve. Lower entry costs reduce the viability threshold.

How to Use the Calculator

Now that you’ve seen the core insights, here’s how to model your specific startup:

1. Start with a Preset

Try the presets to understand different startup archetypes:

• Realistic Optimized: Balanced assumptions for a typical UK SaaS startup
• Lean Startup: Minimal viable team, focus on efficiency
• Best Case: Strong unit economics with competitive advantages
• Defensive Moat: High switching costs and network effects

2. Adjust Entry Costs

Model your build phase honestly:

• Team size: How many people needed to build the MVP?
• Salaries: UK market rates for your roles (£40-80k typical for tech)
• Employment multiplier: Include employer NI (13.8%), pension (3-10%), equipment
• Months to build: Be realistic—most products take 6-12 months
• Infrastructure: Legal (£5-15k), accounting (£3-8k/year), software licenses, cloud

3. Define Unit Economics

This is where most startups succeed or fail:

• Monthly revenue per customer: Customer payment amount
• COGS: Direct costs to deliver (hosting, fulfillment, materials)
• Operating costs: Support, platform fees, transaction costs
• Gross margin: Target 60%+ for SaaS valuations

4. Estimate Market Dynamics

• Monthly churn: 2-3% is excellent for B2B SaaS, >5% is problematic
• TAM: Total addressable market in number of customers
• Series A target: Typically 600-1200 customers depending on ACV

5. Assess Competitive Position

This is where the Aghion-Howitt model shines:

• Quality improvement (γ): How much better is your solution? 2-3x is incremental, 5-10x is transformative
• Displacement risk (λ): What’s the probability competitors or market changes make you obsolete?
• Switching costs: How hard is it for customers to leave? (Data lock-in, integrations, training)
• Network effects: Does value increase with more users?
• Competitor strength: How formidable are incumbents?

6. Interpret the Results

The calculator shows:

• Viability gap: The £ difference between EV and wη
• Positioning score: Overall competitive strength (0-100)
• Key metrics: LTV, CAC payback, gross margin, burn rate
• Insights: Specific warnings and recommendations based on your inputs

Limitations and Considerations

This model has limitations:

1. Assumes stable parameters: Real markets have uncertainty and variance
2. Ignores pivots: You might change direction based on learning
3. Linear customer growth: Reality is usually more sporadic
4. No seasonality: Many businesses have seasonal patterns
5. Assumed CAC: Uses £2k generic CAC rather than your actual numbers
6. Heuristic defensibility weights: The calculator weighs switching costs and network effects equally (50% each) in reducing displacement risk. While economic literature confirms these are key moat factors, there’s no established theory quantifying their precise relative importance. Similarly, the multipliers for competitor strength (0-50% increase) and regulatory risk (0-30% increase) are calibrated heuristics, not derived from first principles

Treat this as a structured framework for analysis, not a predictive oracle. The model’s value is in forcing you to think rigorously about:

• What makes your solution valuable?
• What threatens your position?
• What’s the minimum viable investment?
• When should you abandon the idea?

The Nobel Prize Connection

The 2025 Nobel Prize in Economics recognized three economists for explaining innovation-driven growth:

• Joel Mokyr (Northwestern University / Tel Aviv University) - “for having identified the prerequisites for sustained growth through technological progress”
• Philippe Aghion (Collège de France, INSEAD, LSE) and Peter Howitt (Brown University) - “for the theory of sustained growth through creative destruction”

Aghion and Howitt’s quality ladder model—the mathematical framework this calculator implements—explains how innovation creates economic value by replacing existing products with better ones. When you build a startup, you’re not just creating a business. You’re participating in the process of creative destruction that drives economic progress.

This calculator translates Nobel Prize-winning economic theory into actionable business decisions. When circumstances change, mechanism-based reasoning adapts; pattern-matching fails.

Further Reading

If you want to dive deeper into the economic foundations:

• Aghion & Howitt (1992): “A Model of Growth Through Creative Destruction” - The original paper establishing the quality ladder framework
• Acemoglu (2008): “Introduction to Modern Economic Growth” - Comprehensive textbook on endogenous growth theory and innovation economics
• Tirole (1988): “The Theory of Industrial Organization” - Essential reading on market structure, competition, and strategic positioning
• Christensen (1997): “The Innovator’s Dilemma” - Bridges theory and practice by explaining how displacement actually happens in markets

For practical startup guidance grounded in these principles:

• Kerr & Nanda (2015): “Financing Innovation” - Explains how VC economics and funding structures shape viable startup strategies
• Ries (2011): “The Lean Startup” - Practical methodology for rapid iteration that aligns with learning about displacement risk
• Blank (2013): “The Four Steps to the Epiphany” - Customer development framework for validating quality improvements

Conclusion

Most startup advice is pattern-matching: “X worked for Y company, so try that.” This calculator offers something different: mechanism-based reasoning about why businesses succeed or fail. I hope you found it as useful as I found instructive when thinking through some of these ideas.

The Aghion-Howitt model won’t tell you whether to build your specific idea. But it forces you to confront the hard questions:

• Is your quality improvement (γ) large enough?
• Can you build defensibility before competitors respond?
• Does your entry cost (wη) leave enough margin for error?
• Will your unit economics survive real-world churn and competition?

Answer these honestly, and you’ll know a bit more about whether you have a viable business—before you spend 9 months and £200k discovering the answer the hard way.

Build something valuable. Build something defensible. And use economic theory to improve your odds.