Buy vs rent guide
Sensitivity analysis for buy vs rent: which inputs matter most
A buy vs rent comparison uses a dozen or more inputs, and they do not matter equally. Sensitivity analysis changes one input at a time to find the ones that swing the answer, so you can spend your effort on the numbers that count. This guide ranks them on a fixed example.
The method in one paragraph
Pick a base case. For each input, choose a low and a high value that you consider plausible, run both, and record the buyer minus renter net worth after the stay. The size of the gap between the two results is that input's swing. Sort by swing and you have a ranking.
The base case here is a $600,000 home with 20% down at 4.5%, a 25-year amortization and five-year term, 3.5% yearly appreciation, $2,300 monthly rent growing 3% a year, a 5.5% investment return, 2% inflation, a 1% yearly maintenance allowance, a 0.65% property tax rate and a 10-year stay in Alberta. The base result is +$41,686. These are planning inputs, not market data.
Ranked results
The ranges below are illustrative spreads, not statements about what will happen. Different ranges would change the ranking, which is a limit of this method and is discussed below.
| Input (low to high) | Result at low | Result at high | Swing |
|---|---|---|---|
| Home price growth (1.5% to 5.5%) | -$90,001 | +$199,385 | $289,386 |
| Yearly maintenance (0.5% to 2% of value) | +$87,432 | -$49,807 | $137,238 |
| Mortgage rate (3.5% to 6%) | +$95,323 | -$41,347 | $136,670 |
| Investment return (3.5% to 7.5%) | +$99,779 | -$25,898 | $125,677 |
| Starting rent ($2,000 to $2,600) | -$12,073 | +$95,444 | $107,516 |
| Renewal rate (3% to 7%) | +$73,823 | -$13,200 | $87,023 |
| Years held (7 to 15) | +$11,268 | +$91,982 | $80,714 |
| Rent growth (1% to 5%) | +$8,941 | +$77,919 | $68,979 |
| Property tax rate (0.5% to 1.0%) | +$55,409 | +$9,663 | $45,746 |
| Sale commission (2% to 5%) | +$59,459 | +$32,799 | $26,660 |
| Down payment (10% to 35%) | +$21,100 | +$32,287 | $11,187 |
| Inflation (1% to 3%) | +$43,420 | +$39,861 | $3,559 |
Reading the ranking
Three groups emerge. The first is the dominant input, home price growth (see home price appreciation assumptions). The second is a cluster of mid-sized drivers that are each worth a careful look: maintenance, mortgage rate, investment return, the rent you compare against, renewal rate and stay length.
The third group matters much less in this example: sale commission, down payment size, property tax within a plausible band, and inflation on its own. That does not make them irrelevant for your decision; a different property or province can change them. It means they are rarely the reason a comparison flips.
Notice the surprise in the middle: maintenance. The 0.5% to 2% range swings the result by roughly $137,000, as much as the mortgage rate does. It is often the least examined number, and the one that varies most with the age and type of home. See maintenance and repairs in buy vs rent.
Two inputs at once
One-at-a-time tests miss interactions. Pairing the top input with the investment return shows how the two halves of the bet combine.
- Moving down a row or across a column changes the answer, and moving diagonally can cancel out.
- The sign flips inside the grid, which means these two assumptions together decide the winner for this example.
- Rent growth pairs with home price growth in the same way; at 1% home price growth, even 5% rent growth leaves the buyer $83,083 behind.
| Home price growth | 3% return | 5.5% return | 8% return |
|---|---|---|---|
| 1% | -$49,140 | -$119,317 | -$204,231 |
| 2% | +$11,308 | -$59,300 | -$144,686 |
| 3.5% | +$112,970 | +$41,686 | -$44,440 |
| 5% | +$229,289 | +$157,292 | +$70,387 |
Limits of the method
The ranking depends on the ranges you pick. A wider range for a minor input can make it look major; a narrow range for a big one can hide it. The ranges above were chosen to be broadly comparable, not equally likely.
Sensitivity analysis also ignores that inputs move together in real life. Rents, prices, rates and returns are linked, which is why scenario analysis exists alongside it. And the Monte Carlo view adds randomness: on the base case buying finishes ahead in about 61% of simulated paths, 69% with calmer volatility (3 points for homes and 8 for investments) and 57% with wilder volatility (9 and 16). The probability depends on the volatility you assume.
How to run your own
You do not need a spreadsheet to do this. Use the break-even tool or the main calculator on the home page and follow these steps:
- Enter your real price, rent, rate, down payment and stay length.
- Change one input at a time over a range you can justify, and note the result each time.
- Rank by swing, and circle any input where a plausible range flips the winner.
- Spend your research time on the circled inputs: get a quote for the rate, look at comparable rents, ask an inspector about maintenance.
- Finish with two or three scenarios from scenario analysis.
Questions people ask
Which input matters most in a buy vs rent comparison?
In this example it is home price growth, whose swing is more than twice that of any other single input. Your own case may differ, so run the test with your numbers.
Why does maintenance rank so high?
It is a recurring cost on a large asset, so moving it between 0.5% and 2% of value a year compounds over the stay. It is also often poorly estimated.
Can I trust a ranking based on my chosen ranges?
Treat it as a guide to where to look next. Different ranges can reorder the list, so choose ranges that reflect real uncertainty about your own situation.
What is the difference between sensitivity and Monte Carlo analysis?
Sensitivity changes one input at a time by fixed amounts. Monte Carlo draws many random paths around the assumptions and reports how often buying finishes ahead.
Official references
Educational information, not financial, tax, legal or mortgage advice. Rules and rates change; confirm current details with an official source or a qualified professional.