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A Note to Readers, Critics, and Anyone Currently Pointing at the Sky
Over the years, I’ve been challenged—sometimes politely, sometimes less so—on a few of the economic conclusions I’ve written about here. That’s fine. Markets invite disagreement. Opinions without evidence deserve it. I have also been challenged on a typo or misspeak. It happens when you write.
This piece is my response. Not a rebuttal. More like an extended footnote that accidentally became a paper.
Because saying “prices are going up” is not analysis.
It’s the baseline.
The baseline is sticking a finger in the air, feeling a breeze, and declaring yourself a meteorologist. It’s comforting. It’s usually right. And it’s almost entirely useless.
Analysis is asking why prices move, when they stop behaving the way they used to, and what pressure looks like before it announces itself loudly and expensively.
I’ve called normalization on 30A well before it was socially acceptable. I’ve called out hysteria while others were busy laminating it. Not because I’m clairvoyant—but because I don’t confuse trend continuation with understanding.
If you’ve been reading me for a while, the real argument has always been there. It just wasn’t shouted. It’s buried in how volume behaves year over year, how pricing power persists (until it doesn’t), and how inventory—ever the slow learner—responds last.
So if you’re looking for proof that I’m not baselining my commentary when I talk about great homes, great markets, or moments worth acting on, this is it.
Grab a coffee. Possibly two.
This one asks a little more of the reader than “prices usually go up.”
That’s the real abstract.
Now onto the humorist essay disguised as a research paper.
A Directional–Persistence Framework for Interpreting Housing Market Pressure
Or: Why the Model Beats the Baseline, and Why the Baseline Isn’t the Point
Richard Jabbour
Independent Market Research
Monthly Data, 2014–2026
Abstract
Housing market commentary often relies on a deceptively strong baseline assumption: prices generally go up. While historically true, this belief provides little guidance during regime transitions—the moments when real risk and real opportunity appear. This paper evaluates whether year-over-year directional persistence in unit sales and median pricing, and their interaction, can statistically explain subsequent inventory behavior. Using twelve years of monthly data, we compare this framework against naïve baselines and demonstrate that inventory inflection points are predictable when markets enter sustained states of behavioral conflict. The results are statistically robust. Their importance, however, remains subordinate to a larger truth: none of this matters if you forget why you wanted clarity in the first place. Translation. If something is going in a direction for a while…..even if it is about to change directions it takes a minute to slow down and turn around.
1. Introduction: The Baseline Is Comfortable—and Useless
If you want to sound smart about real estate, you can say one sentence and usually be right:
“Over time, prices go up.”
They do.
Which is precisely why that statement is useless. Overtime, you cannot get a piece of double bubble for a penny anymore. I mean overtime, the penny does not exist. Soon the nickel.
A baseline that is almost always correct is also almost never helpful. It tells you nothing about when pressure is building, when risk is rising, or when opportunity is quietly forming while everyone else is still nodding along. The earth is indeed orbiting the sun…Why?
This paper starts from a different premise:
If a model cannot outperform the baseline belief that prices trend upward, it has no value.
So the question isn’t whether prices rise over decades. The question is whether behavioral signals—specifically volume and pricing direction over time—contain information that improves our understanding of what happens next, particularly to inventory.
2. Data and Methodology
2.1 Dataset
Monthly housing market observations
January 2014 through January 2026
One row per month; no annual aggregation
Variables:
Unit sales
Dollar volume
Median sold price
Inventory levels
All variables are evaluated year-over-year (YoY) to remove seasonality and focus on behavioral change rather than calendar noise.
2.2 Direction, Not Magnitude
Each YoY change is encoded directionally:
1 = higher than same month prior year
0 = lower than same month prior year
Why strip out magnitude?
Because markets do not react to decimals. They react to consistency.
People feel trends, not regression coefficients. Said differently. Uh. There is no way to say it differently.
2.3 Persistence as Pressure
To model pressure rather than noise, we compute trailing six-month directional counts for sales and prices. This reflects how market participants actually experience change: not as a single data print, but as a creeping realization that “this keeps happening.” Or keeps happening until it doesn’t. This is worth 4 minutes of your time!
3. Beating the Baseline: Direction Has Memory
Before inventory, we test a simpler claim:
Does sustained directional change in unit sales predict future sales direction?
Yes. And materially so.
Six-month directional persistence predicts next-month YoY sales direction with ~70% accuracy
Post-2020 accuracy rises to ~77%
Baseline accuracy (“prices usually go up” logic): ~54%
This matters for one reason:
The model beats the baseline.
Markets remember what buyers do. When participation weakens or strengthens consistently, it tends to persist. This alone invalidates the idea that month-to-month data is random noise.
4. Inventory: Where the Baseline Completely Fails
Inventory is where most narratives collapse.
We first test a naïve but common assumption:
If sales and prices are up (or down) year-over-year, inventory should follow.
It doesn’t.
Directional signals alone fail to predict inventory movement. Statistically. Repeatedly.
This failure is not a disappointment—it’s a clue.
Inventory is not reactive.
It is delayed. This is why most people are missing my NORMALIZATION call for the last 6-12 months. Inventory levels and absorption are slowly changing dimensions. It takes a while for Horton to Hear the Who….
It reflects decisions made under uncertainty by people who do not want to admit they are wrong. Participants think that the current point data is relevant. In December of 2018 absolute inventory of houses for sale on 30a was about 615 homes. In January of 2026 at the time of this writing it was 629. What? They will point to absorption and say there is a ton of inventory. Indeed absorption in 2026 is slower than in December of 2018 when there were 78 homes sold. In January of 2026 there were 59 homes sold. And so it goes save of 19 homes the absorption will be the same in Jan 2026 as December of 2018. And inventory is noticeably falling now too. Year over year unit sales are up 12%.
5. The Model That Actually Explains Inventory
When we introduce two elements—persistence and interaction—the picture changes.
Model Components
Trailing six-month directional persistence in:
Unit sales
Median price
A sales × price interaction term
Dependent variable:
YoY inventory direction
Results
Highly statistically significant
Pseudo R² ≈ 0.24
Strong improvement over baseline and direction-only models
This model does what the baseline cannot: it explains why inventory changes in the forward direction and more importantly that predicting it will, where I have met the most push back, have statistical relevance over the mere finger in the air baseline.
6. The Four Market States (And Why People Miss Them)
The interaction term reveals four repeatable regimes that develop over a slower time frame based on current trailing data:
Sales ↑ / Prices ↑
Inventory compresses. Consensus is comfortable.Sales ↓ / Prices ↓
Inventory expands. The downturn is obvious.Sales ↓ / Prices ↑
Seller denial. They fail to see price stability emerging. Inventory builds quietly, then all at once.Sales ↑ / Prices ↓
Buyer control but sellers are late. Inventory collapses faster than intuition expects.
The baseline story (“prices usually go up”) is blind to regimes 3 and 4—precisely where risk and opportunity live. We are presently between 3 and 4. Where sales are beginning to rise a bit back towards the sustainable 55-70 homes per month here on 30a and where pricing is flat. Some sellers are still missing the change cue thinking that today’s data matters… the what you see is all there is WYSIATI thinking of Kahneman. Forward thinkers see the change are a now content to wait for balance.
7. Why This Is Useful (And Why It Isn’t)
This framework helps you:
Avoid false confidence
Recognize pressure before headlines change
Stop confusing price stickiness with market strength
But let’s be honest.
At some point, the analysis ends and life shows up anyway.
What if your spouse gets sick? What happens if you are 10 years older now and haven’t acted? I do not mean to be silly at all. I do know that in our market the reality is some, many, most, really cannot afford financially to consider this kind of option. But it is those that can that I think about all the time. What constitutes “can”? There I wonder. I find myself a pretty good sample of one and why I did, but I also find that the few hundred people I have worked with are a good sample too.
What if the spreadsheet is perfect and the life timing is right but the numbers are not 100% spot on? and you still miss the years that mattered because you were busy being “right” or working 10 hours days even after you already had 4 cars?
C.B. “You cannot build sand castles on the beach with your grandbabies on a pile of Bitcoin”.
You cannot replay a sunset walk with a statistically significant p-value.
You cannot buy back ordinary Tuesdays.
But more on Wealth Benchmarks later I suppose.
8. Conclusion: Do the Work—Then Put It Down
This model beats the baseline.
It explains inventory behavior better than price narratives.
It anchors economic thinking in observed behavior, not hope.
That’s the point of doing the work.
I stand by my beliefs that this market is now normal again after silliness. Inventory will ebb and flow again within a regular band. Monthly unit sales will fluctuate around the historic median of about 58 units. Exactly where we are now. MORE ON THAT TOO. Median prices will be volatile and some home prices will go up and some will go down but the average will be flat for a little while (like a couple of more years). Some micro markets on 30a will rise in price but not because of the Case Shiller measure. New Homes in Alys Beach are new Homes. A new home in Seaside (yes Seaside is rebuilding and becoming rather pricy) will be rather valuable. An old tear down in Old Seagrove…..Lot value.
The other point—the more important one—is knowing when to stop.
Clarity is not the goal.
Freedom is. Statistics won’t sit well without a beach walk “in the in between.”
So understand the pressure. Feel what you want. Make the decision.
And then, for God’s sake, close the laptop and go live your life. I have already spent 1 hour developing this paper when Gayle and I could have just taken another beach walk today!
Because the clock is running whether the market is up or down. And like our good friend Justin Timberlake found out one……..for some….it gets to zero and I am not sure there is a time bank.