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. Then you charge each person what their next-best alternative would have paid, and ask the question again.

Then the harder question: where does a surplus in this market end up? Follow the money to the medallion, 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.

opportunity cost · rent 2 stages · spec-driven build Optional · not graded this term

Optional this term

Optional this term and not graded; work it if you want the practice. Case 1, Perfect Competition, is the graded case; the stages, the repo and the method here are the same.

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 — a fixed number of 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 timeApp driver, part timeYellow cab, full timeOffice 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

Accounting profit is where the case starts, not where it ends. Three questions to carry into the model. What does each person give up to do this work, measured net and at the same scale? Which costs in the cab driver's column are paid to somebody who never drives? And how much does each answer depend on days worked per month?

The medallion — rent, capitalized

Before entryAfter entry
Lease$3,000/mo → $36,000/yr$1,500/mo → $18,000/yr
Required return3.5%6.0% (riskier)
Capitalized value$1,028,571$300,000
Observed price (stipulated for this case)>$1M at the peak≈$335K

One division reproduces both observed prices within about 10%. In the case, app vehicles roughly triple; 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 about 70% 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. Ask whether entry was the only cause: how medallion purchases were financed may have moved the peak too.

What you'll be able to do afterwards

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.

0 of 2 stages complete

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

You draft first and AI reviews; the doer–reviewer dilemma explains why. The line for this case:

Good uses — log themYours alone
Explaining accounting vs economic vs normal profit until it clicks; quizzing youThe hypothesis, written before you model anything
Building the workbook from your committed spec; debugging what it returnsWriting the spec — and auditing the result against it
Attacking your draft explanation of the medallion collapseWriting 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.