A friend of mine named Eilam, also a numbers sort of guy, made an interesting comment about my previous post in which I dissected the year-to-date real estate numbers for Palo Alto, CA. He challenged me to look still deeper into the numbers and try to figure out whether I had the cause-and-effect in the right order.
I essentially asserted that, “Homebuyers were buying increasingly smaller homes from January to July, and increasingly larger homes thereafter, and that’s what led to prices going down between January to July, and upwards thereafter.”
Eilam asks if instead it might be this way around: “From January to July, homebuyers decided they wanted to buy less expensive homes, so they simply bought smaller ones. Thereafter, they loosened the purse strings, and therefore bought more.”
His exact quote:
Thanks. Good analysis.
However - it does beg a follow-on question. What can we learn from the down-tick and later up-tick in sizes of houses being sold ? Is there rhyme-and-reason underling the observed trend (which you very accurately analyzed) ?
I think ’sizes=total price’ (i.e. it isn’t that people are all of a sudden interested in larger or smaller houses at certain times of the year).
What is interesting to ask is: is this a pattern change in demand or in supply (i.e. is the reason smaller houses were selling for a while because larger ones were not on the market, or because they were on the market but people were not buying ?).
Also - what would be interesting is to overlay it with a possible ‘culprit’: interest rates.
Is the swing in ‘house sizes’ (again in my mind possibly an ‘alter-ego’ of total-purchase-price) correlated to changes in interest rates ?
Great question — I would have expected nothing less from Eilam — and my answer for now is, “I’m not really sure.”
Here’s what I (think I) know and don’t know so far:
- Since Altos Research’s data only goes back a year, I’ll have to go to another data source to find out if this is a seasonal trend — ie for whatever reason, people buy increasingly smaller homes in the first half of the year, and increasingly larger homes later on. I strongly, strongly doubt that’s the case. I have the data that will answer that question locked up in a 250MB Access database, but I haven’t had time to release and analyze it.
- Interest rates may indeed be the reason. I don’t have a quick-and-dirty way of putting interest rates and Altos Research data on the same graph, so for now this will have to do:
Palo Alto median home prices:
Interest rates (from Freddi Mac)
30-year fixed mortgage rates climbed steadily from 6.15% in January to 6.76% in July, and then crept down to 6.40% in September. As mortgage rates were climbing, home prices were going down, and when mortgage rates started going back down, home prices started going back up. Eilam’s theory may indeed be correct in that prospective homebuyers ratcheted down their size requirements to stay within a budget.
If this theory is correct, we should see a similar pattern in other towns. The results below don’t show a similar pattern; I’ve included towns both more and less expensive than Palo Alto.Menlo Park:
- Conclusion? I’m still not sure! Possibilities:
- It’s unlikely that Palo Alto home buyers are more interest-rate sensitive than their neighbors in Menlo Park, Redwood City, Los Altos, and Woodside.
- It’s possible that people who buy homes during the school year tend to have fewer or no kids and thus need less space, and those who buy during the summer tend to have more kids and need more space. Sounds like a good theory, but wouldn’t it be the same for other towns as well?
- It may just be something completely random, an artifact of the characteristics of the homebuyers that happened to be on the market in Palo Alto this year.
Tags: 94301, For buyers, For sellers, Palo Alto, Real estate, Real estate data
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2 responses so far ↓
1 Greg // Oct 28, 2006 at 8:15 pm
Kevin, I am dying to know how the Palo Alto medians you report compare to sales volume during that period. While the median is decent summary statistic, I think it would be even more interesting and helpful to look and the distribution and number of sales on the graph directly. Could you plot all Palo Alto sales on a day by day basis, so we could see what the cloud of points actually looks like? (BTW, you may need to toss a couple of outliers out so they don’t compress the scale on the other points)
2 Part 3: There’s always a story in the numbers…creating FUD from that story is the media’s job; making sense from it is mine at Three Oceans Real Estate // Nov 8, 2006 at 5:01 pm
[...] A previous post of mine generated an interesting series of email exchanges between myself and reader Greg. Part statistics, part epistomology, and part real estate, I thought the discussion — a tribute to liberal arts education — worth posting on its own. The end state, alas, was inconclusive. [...]
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