The housing market has a problem that nobody is talking about correctly. Agents say "there aren't enough homes." Economists talk about "supply constraints." But when you look at 20 years of transaction data and a 275,000-parcel county database, a different picture emerges: the market isn't stuck because of supply. It's stuck because 37% of homeowners are locked into mortgages they can't afford to leave.
This is the rate lock-in effect, and it's the single biggest force shaping the Pikes Peak housing market right now.
Turnover rate measures what percentage of the total housing stock changes hands each year. It's the purest signal of market health — not listing counts, not sales volume, but the rate at which homes actually move from one owner to the next.
In a healthy market (2015–2019), roughly 7% of homes in El Paso County changed hands each year. At the 2020 peak, turnover hit 8.1% — frenzied but driven by real demand. Today it's 4.9%, a level we haven't seen since the aftermath of the 2008 crash.
That's not a small decline. It means roughly 6,000 fewer transactions per year than normal — 6,000 families who would have moved but didn't. Where did they go? Nowhere. They're sitting in homes with mortgage rates they'll never see again.
Here's the math that explains everything. Between 2015 and 2021, approximately 103,000 homes were purchased with mortgages at sub-5% interest rates. That's 37.5% of the entire housing stock in El Paso County.
For these homeowners, selling means trading a historically cheap mortgage for one that costs dramatically more:
The 2020–2021 cohort — roughly 32,000 buyers — has it worst. They purchased at an average of $424K with rates near 3%. Moving to an equivalent home today means their mortgage payment jumps $828/month — nearly $10,000 per year — even if they roll all their equity into the new purchase.
That's not a decision. That's a trap.
The correlation between mortgage rates and housing turnover is stark. When rates drop, people move. When rates spike, the market freezes.
Every major rate increase in the last 20 years triggered a turnover decline. But the current episode is uniquely severe because it follows the lowest rates in history. The gap between locked-in rates (2.5–4%) and current rates (6.5–7%) is the widest it has ever been. There's no historical parallel for this many homeowners being this deeply rate-locked.
The lock-in effect doesn't hit every zip code equally. Some areas have seen turnover drop by half; others are barely affected.
The pattern is clear: affordable, starter-home neighborhoods are the most frozen. Zip codes like 80916, 80817, 80923, and 80911 — areas popular with first-time buyers, military families, and FHA/VA borrowers — have seen turnover drop 43–53%. These are the homeowners with the tightest budgets and the least ability to absorb a payment increase.
Meanwhile, higher-end areas like 80132 (Monument: –13%) and 80904 (Old Colorado City/Westside: –20%) are more resilient. Wealthier homeowners have more financial flexibility — some are cash buyers who aren't rate-locked at all, others can absorb the payment jump.
Rate lock-in doesn't just affect the locked-in homeowners. It cascades through the entire market:
The result: a market that looks like it has enough inventory (5,000+ active listings, above the 30-year average) but feels stuck. Homes sit longer, prices stagnate, and agents blame "supply" when the real issue is that 37% of the market's natural sellers have golden handcuffs they can't remove.
There are only a few things that can unfreeze a rate-locked market:
Methodology: Turnover rates computed from 265,000+ closed transactions (Pikes Peak MLS, 2006–2025) divided by estimated residential housing stock (El Paso County Assessor parcel data, 275K+ parcels). Rate lock-in estimates based on financed purchases (excluding cash) at prevailing average mortgage rates by year. Payment calculations assume 30-year fixed, 10% down. Zip-level analysis compares 2017–2019 average annual sales to 2024–2025 average. 2010 and 2016 transaction counts appear low due to partial data in source files.
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