Kumu / Micro/Macro Econ / Economic Profit & Rent
Economic Profit & Rent — Earnings Analysis
Four people in one city, and one question a client actually asks: who is making money here? A full-time app driver, a part-time app driver, a full-time yellow-cab driver, and an office worker each get a full profit-and-loss — and the verdicts flip once you charge each person what their next-best alternative would have paid.
Then the harder question. If the drivers are not making economic profit, somebody was. The money turns out to be capitalized inside a tin shield bolted to the hood of a cab — and your model reproduces its price at the peak and after the collapse, with one division.
Optional · ungraded · self-paced
This engagement is optional. Case 1 — Perfect Competition — is the graded case this term; this one is here for anyone who wants to keep going. Nothing is submitted, nothing is due, and you work it at your own pace. The stages, the repo, and the method are identical — only the obligation is gone.
The economics, briefly
Accounting profit subtracts the money that left your bank account. Economic profit also subtracts what you gave up to be here — the implicit cost, which is the net earnings of your next-best alternative. Earn exactly your opportunity cost and economics calls you normally profitable: no reason to move, and no reason to stay either. Economic profit is what you earn above that line, and it is the only kind that answers "should I be doing this?"
The second half is about who captures a surplus when it exists. A factor in genuinely fixed
supply — 13,587 medallions, and no more — earns economic rent: payment above what
is needed to keep it in use. And an asset that earns rent indefinitely is worth
rent ÷ required return. That single formula is what turns a $36,000 annual lease into
a million-dollar asset, and what destroys it again when entry arrives from a direction the moat
never covered.
The four working lives (annual)
| App driver, full time | App driver, part time | Yellow cab, full time | Office job | |
|---|---|---|---|---|
| Gross | $86,400 | $43,200 | $108,000 | $57,600 |
| Explicit costs | $35,880 | $20,340 | $48,420 (incl. $36,000 lease) | $5,400 (commute) |
| Accounting profit | $50,520 | $22,860 | $59,580 | $52,200 |
| Implicit cost | $52,200 | $26,100 | $52,200 | $50,520 |
| Economic profit | −$1,680 | −$3,240 | +$7,380 | +$1,680 |
Three things to notice. The part-timer is hit hardest, because the car's costs do not scale — a full payment and full insurance sitting on half the revenue. The cab driver appears to win, and then hands $36,000 a year to somebody who never drives. And every verdict here is one input away from flipping: set days per month to a civilian 22 and read them again.
The medallion — rent, capitalized
| Before entry | After entry | |
|---|---|---|
| Lease | $3,000/mo → $36,000/yr | $1,500/mo → $18,000/yr |
| Required return | 3.5% | 6.0% (riskier) |
| Capitalized value | $1,028,571 | $300,000 |
| Observed price | >$1M at the peak | ≈$335K |
One division reproduces both observed prices within about 10%. App vehicles went from roughly 40,000 to more than 120,000; fares fell, so the lease fell, and the income stream got riskier, so the required return rose. Both moves shrink the same fraction — which is why an asset lost 70–85% of its value without anyone revoking a single license.
The moat is the point. The cap blocked entry into yellow cabs. It never blocked entry into rides. Rent survives exactly as long as the moat surrounds the market rather than the product. Be honest about the second cause too: predatory medallion lending inflated the peak, so entry was not the only villain.
What you'll be able to do afterwards
- Take any earnings statement from accounting profit to economic profit, charging implicit costs net-to-net and scale-matched
- Explain normal profit as a cost rather than a result
- Identify economic rent, and say what is holding it in place
- Capitalize a rent stream into an asset price, and decapitalize an observed price back into the rent it implies
- Predict what entry does to both — and recognize when a moat protects the wrong thing
How the engagement runs
Two stages, the same rhythm as the earlier cases: specify the model before it exists, have AI build it from your spec, audit what comes back — then explain what it means and recommend something.
Brief, Spec, Build, Audit
Name who you think is actually ahead, and why. Then specify both sheets — the four P&Ls and the capitalization — precisely enough to build from, have AI build the workbook, and audit it against your own validation rules.
Analysis, Memo, Prompt Log
Why the verdicts land where they do, where the money went, what entry did to the asset — and a recommendation written to somebody who has to decide something about it.
Where this closes the arc
Three engagements, one argument told three times. In the first, nobody had power over price and the only question was how much to produce. In the second, a patent handed one firm the power to choose the price. Here the profits look real until you count what the owner gave up — and most of what is left turns out to belong to whoever holds the scarce asset.
The medallion's rent behind a moat is the seed patent in miniature: same moat → rent → entry logic, a different legal wrapper. Drawing that link properly, rather than name-dropping it, is one of the things Stage 2 is really asking for.
Where AI fits, and where it doesn't
| Good uses — log them | Yours alone |
|---|---|
| Explaining accounting vs economic vs normal profit until it clicks; quizzing you | The hypothesis, written before you model anything |
| Building the workbook from your committed spec; debugging what it returns | Writing the spec — and auditing the result against it |
| Attacking your draft explanation of the medallion collapse | Writing the analysis, the memo, and the reflection |
One specific thing to check for here: economic profit versus normal profit is a reliable place for a model to stumble, and it stumbles confidently.