The Farm Profit Lab
Run a 1.5-acre market garden as a price taker. Choose beds of tomatoes, carrots, and mesclun; diminishing returns make every extra bed more labor-hungry, so marginal cost rises — and the profit-maximizing plan is where price meets marginal cost. This is the Perfect Competition case study's Excel model, made touchable.
Planting plan
Predict first: which crop deserves the most beds, and where should each one stop? Then check yourself against the optimizer — and make it explain itself via the marginal analysis below.
Season P&L
Marginal analysis
Marginal cost vs price
Things to try
- Slide tomatoes up one bed at a time and watch the marginal analysis: the moment "+1 bed of Tomatoes" turns negative, you've crossed P = MC. Check the chart agrees.
- Find the tomato MC dip. Around 6 beds, marginal cost falls — the farmer's own (expensive) hours run out and cheaper temp labor takes over. Then diminishing returns win again. MC curves aren't always smooth.
- Ask why carrots max out. At the optimum, one more carrot bed would still add profit — but the 20-bed cap says no. That's a binding constraint, and the forgone profit is its shadow price.
- Grow only carrots. Every plan loses money — yet the best all-carrot plan still beats zero beds. Price covers variable cost, so you operate at a loss in the short run. Shutdown logic, live.
- Interrogate Kumu (✳) — have it quiz you on why the optimum is where it is before you press the button.
From lab to project
The course workbook (farm-profit-optimizer-template.xlsx) is this exact model with
named ranges and Excel Solver. If you can predict what this lab will do, you can build, solve,
and — most importantly — explain the spreadsheet version.