In this episode of The REconomy Podcast™, Deputy Chief Economist Odeta Kushi and Senior Commercial Economist Xander Snyder unpack the seemingly conflicting signals emerging from retail property price data in early 2026. They examine why one major retail price index suggested prices were softening, even as broader price-per-square-foot measures remained more stable. While the softer repeat sales read may initially suggest weakening, the broader evidence points to a more nuanced story. 

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Listen to the REconomy Podcast™ Episode 140:

“Retail has actually been one of the more resilient asset classes in commercial real estate, in part due to the dearth of new construction. There are still some weak spots, but generally speaking, retail has held up better than a lot of people expected, especially in what's called experiential or service-oriented locations.” – Odeta Kushi, Deputy Chief Economist

Transcript: 

Odeta Kushi - Hello and welcome to episode 140 of The REconomy Podcast, where we discuss economic issues that impact real estate, housing and affordability. I'm Odeta Kushi, deputy chief economist at First American, and with me is Xander Snyder, senior commercial real estate economist at First American. Hey Xander.

Xander Snyder - Hey Odeta. I'm looking forward to our chat today because it circles somewhat around one of my favorite topics, which is – the data is ambiguous.

Odeta Kushi - All right, I guess we're just going to jump right into it today, Xander. I'll bite. What's so thrilling about ambiguous data?

Xander Snyder - Well, you see, if two pieces of data are pointing in different directions, that usually means there's something more nuanced going on under the hood that warrants investigation. And, of course, as an economist, there's nothing better than a good "hmm, why is that?" moment to get those analytical wheels turning.

Odeta Kushi - I can certainly relate to that. Questions without clear answers are usually the most fun to tackle. So, today we'll be looking at some seemingly conflicting data on retail property prices from early this year. Retail has actually been one of the more resilient asset classes in commercial real estate, in part due to the dearth of new construction. There are still some weak spots, but generally speaking, retail has held up better than a lot of people expected, especially in what's called experiential or service-oriented locations.

So, when one of the major repeat-sales price indices started showing retail property price declines in early 2026, that got our attention. In fact, there was a lot of email back-and-forth on that topic specifically, because it naturally raised the question – is the retail property market beginning to soften?

Xander Snyder - And I think the best answer to that right now is probably not, at least not in the broad, sweeping way that a headline price index decline might suggest. And that's because there are a few different ways to measure property prices and they don't all tell the same story with retail right now.

Odeta Kushi - Okay, so we're going to get wonky today. The price picture is ambiguous, so that's where we're headed. The price index showing declines is what's called a repeat-sales index. That means only properties that have previously sold are included in the index.

Xander Snyder - The data is ambiguous. Correct. No two commercial properties are the same. And, as we like to say in economics, this makes it a highly heterogeneous good, which is just a fancy way of saying that all the products are different. You can compare that to a hammer as an example. If you track the price of the same model of hammer over time, you get a clean read on price changes. But commercial real estate isn't like that. Every property is different. And what sells in one period may not look like what sells in another period. All of that variation makes it hard to talk about average price trends. A repeat-sales index tries to solve that problem by looking only at price changes for the same building over time. So, if a shopping center sold in one year and then sold again a few years later, that pair can help estimate price movement, while holding the variations in the asset more constant.

Odeta Kushi - Right, and that's one way to measure price growth, but it's certainly not the only way. Another, perhaps simpler approach, is price per square foot. I'm sure we're all familiar with that one, sometimes with adjustments for property characteristics like size, age, and location.

Xander Snyder - Yeah, exactly. To sum up: a repeat-sales index compares the same property over time, which helps control for those differences in what's selling. A price-per-square-foot series just looks at the average pricing of what happened to sell in a given period. Sometimes adjustments are made to make those a little more comparable. So, you can look at the same market, use a different method, and come to slightly different answers.

Odeta Kushi - And this is where, in keeping with Mark's tradition, I'm obligated to make at least one 1980s reference. Think of repeat sales as the Back to the Future approach. You keep going back to the same property at different points in time and asking what's changed. A price-per-square-foot measure is more like taking in the whole mall scene in a John Hughes movie and asking what the average looks like right now.

Xander Snyder - That might be the most Mark-approved explanation of a repeat-sales index that I've ever heard

Odeta Kushi - Thank you. I think he would be proud. I work hard so Mark doesn't have to do all of the generational heavy lifting.

Xander Snyder - Yes, indeed. So, here's where the retail story got a little less clear. The repeat sales data suggested some weakness, but broader average pricing measures did not show the same sort of declines. In some cases, prices per square foot were still up. And when you look across multiple data providers, some series look softer, while some look stable. That doesn't mean one of them has to be wrong. It just means they're measuring different things.

Odeta Kushi - And when we first started digging into this retail price decline, a natural question was whether this was just a sales composition issue. That kind of mix shift would mainly affect broad averages like price per square foot, but it's still worth checking to understand the overall market backdrop. Maybe more lower-priced retail formats are traded. Maybe there was some sudden rotation into cheaper property types. Or perhaps shops were selling instead of centers, or lower quality assets were making up a bigger share of transactions.

That would actually be a pretty straightforward explanation for why some price measures might look weaker, even if the market itself hadn't broadly rolled over.

Xander Snyder - But the more we investigated that particular explanation, the less convincing it became. Looking at the subtype mix, the broad retail composition just hasn't shifted enough to explain the apparent weakness in the repeat sales index. Centers have stayed pretty stable as a share of all transactions, both in terms of counts and dollar volumes. And the same was true when we looked across other major retail subtypes and different data providers. So, put more simply, the market did not just suddenly lurch toward obviously cheaper kinds of retail properties.

Odeta Kushi - Well, that's important because it rules out one of the easier explanations for the divergent price trends. But we did look at it another way too, essentially asking: if you hold typical pricing within each subtype constant and just change the mix of what sold, does that explain much of the movement? And the answer was basically no. Mix was part of the story at the margin, but not the main event.

Xander Snyder - Exactly. So, at this point, the plot thickened, because if subtype mix wasn't the answer, then maybe the weakness was really about the repeat sales sample itself. The more convincing signal here turned out to be that the repeat sales sample has been aging over time. And it's worth defining one more term before I go further. A matched pair is simply a property that sold once and then sold again, creating a repeat sale. That pair is what repeat sales indexes use as their sample. One matched pair represents a single building sold twice in two different transactions.

What we found when we looked into this is that retail properties sold as matched pairs have on average been getting older over time. That is, the average number of years that have passed since a prior sale has been increasing, and this increase has been going on for several years in a row.

Odeta Kushi - That part about increasing time between sales is at the center of this story. In 2017, the average hold time between sales was a little over six years. By 2025, it was getting closer to eight years. And, in early 2026, it was even higher. So that means matched pairs are not just older, but often more worn down.

Xander Snyder -  Exactly. A property that resells after a very long hold period has had more time to age, more time for deferred maintenance to pile up, more time for leases to roll or expire and become more uncertain, and more time for the surrounding area to change. The tenant roster can look quite different after a long gap like this. Even though repeat-sales indices are designed to control for quality by comparing the same property over time, long holding periods create more room for the property itself to change in ways that don't really reflect the market in a pure sense.

Odeta Kushi - Yes, and that's the plain-English version of repeat sales bias here. It's not just that there may be fewer observations. It's that the properties eligible for repeat sales analysis may become a more selective slice of the market over time. And, if that slice is increasingly made up of older, more seasoned assets, then the repeat-sales index can look weaker than the broader market.

Xander Snyder - Yeah, a good way to say it is this: the repeat-sales index might be telling us more about the pricing of seasoned, re-trading retail assets than about the entire retail market. And, in a market where newer, stronger, or more institutionally-favored assets are also trading at decent prices, the broader averages can look better than the repeat-sales index at the same time.

Odeta Kushi - Yep, and that's the nuance. It's not that one series is true and the others are false. It's that the repeat sales measure may be more vulnerable right now to sample selection effects.
All of this to say, this isn't a "nothing to see here, move along" sort of story. It's more that the evidence doesn't support a broad retail price collapse, and the evidence increasingly points toward the measurement methodology being part of why the repeat sales series looked soft in the first two months of the year.

Xander Snyder - In other words, how you measure matters. If you only looked at one number, you might conclude that retail is suddenly in trouble. But, if you line up the repeat sales data, the price-per-square-foot data, and the subtype mix analysis and compare them all to one another, what emerges is a market where the measurement framework does change the message somewhat. And that in itself can be informative about the state of the market.

Odeta Kushi - Point being, if the broad subtype mix had shifted sharply toward cheaper product, that would be one kind of story. That doesn't seem to be what's happening here. Instead, if the repeat sales universe has been getting older and more selective over time, that gives us a much more plausible bridge between the soft repeat sales read and the stronger, broader pricing measures.

Xander Snyder - Exactly. And it also importantly gives us some sense of what to watch next in the retail market. For example, I'll certainly be looking at whether the data starts converging in the second quarter. Will the different pricing measures start telling more of a similar story? If the repeat sales weakness is the start of broader repricing, then other indicators should begin to soften too. But, if that's not the case, then the argument for sample bias gets stronger.
I'm also going to be looking for data revisions, because some of the early 2026 data is still preliminary. If later releases revise that weakness away or reduce it, that would support the idea that we're looking at noise or sample quirks, rather than a clear market signal.

Odeta Kushi - So, to bring things to a close today, the current takeaway is not that retail prices are definitely falling across the board. It also doesn't mean that the weakness in the repeat-sales index should be dismissed. Rather, it's just that the apparent weakness needs additional interpretation.

Xander Snyder - Right. The broad subtype mix does not appear to be the main culprit. The more persuasive explanation is that the matched pair sample has been aging, and an older, more selective repeat sales universe can make that index look weaker than the broader market.

Odeta Kushi - That's a very elegant way of saying don't let any single chart do too much of the talking.

Xander Snyder - Exactly. It's certainly something we're going to keep our eye on as the second quarter picture comes into clearer focus.

Odeta Kushi - We will, and I have a feeling this is one we'll be revisiting before too long. That's it for today. Thank you for joining us on this episode of The REconomy Podcast. If you have an economics-related question you'd like us to feature in a future episode, you can email us at economics@firstam.com. And as always, if you can't wait for the next episode, you can follow us on LinkedIn. Until next time.

Thank you for listening, and we hope you enjoyed this episode of The REconomy Podcast from First American. We're pleased to offer you even more economic content at firstam.com/economics. This episode is copyright 2026 by First American Financial Corporation. All rights reserved.

This transcript has been edited for clarity.