2007 Year End December Market Action

It’s here! RMLS December Market Action. Without further adieu, here’s the punchline:

Month-over-month, the average sale price increased 8.3% when comparing the month of December 2007 with that of December 2006 and median sale price increased 1.1%.


Surprisingly, at least to me, 2007 condo appreciation is listed at 13% over 2006 prices and that follows years of 14%, 14%, and 12% over the prior respective year. I expected condos to be the anchor on the market, not the buoy. RMLS defines appreciation as: Appreciation percents based on a comparison of average price for the last 12 months (1/1/07-12/31/07) with 12 months before (1/1/06-12/31/06). That’s the same metric used for the poll on the right.


Closed sales dropped 29% which makes it even more amazing that Realtor associations are reporting record membership. Inventory rose both for the year and the month. By area breakdown, the Milwaukie/Clackamas area was the only one reporting a loss. All other areas had positive appreciation but none over 10% Portland: West (3.6%), North (8.4%), Northeast (6.4%), Southeast (7.1%). When will RMLS break SW and NW Portland apart for reporting purposes?

I’ll stop there for today. In the coming posts, we’ll look at how our poll results reflected the market, how the market has fared in a longer term view and consider how we sum up our market.

30 Comments on “2007 Year End December Market Action

  1. “Month-over-month, the average sale price increased 8.3% when comparing the month of December 2007 with that of December 2006 and median sale price increased 1.1%.”

    Note that the gap between median price and average price increased by $24,100.

    2007 Gap = 352,000-276,500 = $76,500
    2006 Gap = 324,900-273,500 = $51,400
    For a difference of 76,500-51,400 = $24,100

    My interpretation of this: In the light of the contraction of home sales (from ~32k to ~28k), higher valued homes are outselling lower valued homes. The data is skewed to the right by big fish, so the so-called “textbook appreciation” is artificially increased.

    Other possibilities?

  2. That is a logical conclusion, if we had more access to the data it would be fun to figure out.

    I was looking at my spreadsheet to see exactly how many closed sales there were in Jan 07 thru Dec 07 and I came up with 26,532. Then I looked at the RMLS report for December 2007 and see they said there were 28,173. I thought, hey, I must have fudged a number here on my spreadsheet… Nope.

    There seems to be sales that are unaccounted for in the Market Highlights section. The YTD sales don’t match up when you add up the monthly closed sales. For example:

    Closed Sales Reported (D=difference):
    01.2007: 1,594, YTD: 1,594, D: 0
    02.2007: 1,899, YTD: 3,561, D: 68
    03.2007: 2,775, YTD: 6,359, D: 23
    04.2007: 2,594, YTD: 9,162, D: 209
    05.2007: 2,802, YTD: 12,142, D: 178
    06.2007: 2,731, YTD: 15,001, D: 128
    07.2007: 2,624, YTD: 17,908, D: 283
    08.2007: 2,554, YTD: 20,607, D: 145
    09.2007: 1,866, YTD: 22,688, D: 215
    10.2007: 1,864, YTD: 24,677, D: 125
    11.2007: 1,733, YTD: 26,535, D: 125
    12.2007: 1,496, YTD: 28,173, D: 142

    Totals: 26,532, TYD: 28,173, D: 1641

    According to their summary page 6.2% of total sales were added (on average) between months. I haven’t gone through each MLS looking for them. It would have to be a slower day to go looking for them.

  3. Ralph-

    It’s quite disturbing to me that you not such a simple inconsistency in the reports. Although I have been wondering about the data for some time, this really makes me question the RMLS data.

    I still wonder how the BVH auction results might be included in the data.

    Note further that even if all the high valued homes are falling in value, the average and median prices continue to rise as a result of the shift in distribution of sales.

    Even without further data, can you think of any other reason why the gap between average and median prices has increased so much? It’s up about 50%!


  4. I put together this chart for the last 5 years over Average Price as a Percentage of Median. Some interesting patters appear to me, but I can only guess at what it could mean.

  5. That months of inventory number is going to look pretty bad this spring – inventory is starting to rise pretty sharply earlier than I’d expect.

    The lending environment will continue to tighten this year as the sheeple realize just how the bad underlying economy is.

    The only reason PDX is on the “Still appreciating” list is because of the way the stats are calculated here with a running year window.

    Straight YOY is good enough for everyone else in the nation – why not here ?

    Maybe because it would show that Portland isn’t going to get bypassed by the crash.

  6. Ralph-

    Looking at your chart around December 06, the ratio was about 118%, and now it’s about 127%, or a 50% increase from the base of 100% (ratio data). I also find it interesting that it appears that we have gone from the recent low to hit a recent record.

    Maybe Charles can provide further insight as to the RMLS data as well as this increasing ratio.

  7. I can hypnotize… I think it goes back to big fish. I ran a report earlier on the west side of Portland. The highest priced sale was $4,000,000; roughly 10 times the median or average price. The low was $80,000ish. It doesn’t take many outliers to skew the average price. Looking at Ralph’s graph over the last four years the difference between the high and low is 10%. My feeling is that can largely be explained by outlier properties.

  8. Have we entered a period of more outlier properties, or is the bottom end not selling so well, possibly because of the subprime lending mess?

    I agree that the “textbook appreciation” is sensitive to outliers, but I really think the bigger issue (given the drastic reduction in sales) is the lack of sales at the bottom end.

  9. Opaque statistics that don’t add up and are designed to “spin” the market.

    Whats the point of discussing RMLS stats?

  10. I thought about this a little more. I make the following assumption: All reported data is correct. This, of course, is subject to assumption failure.

    In December 2006 the number of closed sales was 2120 with an average price of $324,900. This means that there was about $689M in total real estate sales activity.

    In December 2007 the number of closed sales was 1496 with an average price of $352,000. This means that there was about $527M in total real estate sales activity.

    Thus in 2007 the total sales activity was down $162M. In percentage terms, the activity is down about 23.5%. Computation: (527-689)/689. A reduction of $162M in sales activity also means that there is about a 23.5% reduction in real estate commissions.

    Assuming an average commission of 6% on sold property:

    2006 Agent commissions = 689M*0.06 = 41.3M
    2007 Agent commissions = 527M*0.06 = 31.6M
    Gross reduction = 41.3M-31.6M = $9.7M

    This during a period that Charles reports “that Realtor associations are reporting record membership.” In other words, the pie keeps getting smaller, and the number of hands trying to take from it keeps increasing.

    So here we have it:

    1. Total December sales volume down about 23.5% or $162M from 2006.
    2. The gap between median price and average price was near a five-year minimum last year.
    3. The gap between median price and average price is at a five-year maximum this year.
    4. Using trend analysis, the gap is increasing.
    5. The number of sales/buyer agents is increasing.
    6. The number of properties sold during December is drastically down from the prior year; “Closed sales dropped 29%.”
    7. The number of sales for the entire 2007 year is also down by about 13% from the entire 2006 year.
    8. The total sales volume for the year is down $793M, or about 7.6% (corresponding agent commissions down about $48M, assuming 6%).
    9. Asking prices continue to erode.
    10. “Month-over-month, the average sale price increased 8.3% when comparing the month of December 2007 with that of December 2006 and median sale price increased 1.1%.”
    11. Months of Inventory is over 8, and about 4 times what it was 2 years ago.
    12. “Textbook appreciation” is up.

    What does all of this mean, and what does the future hold is a bigger question.

  11. I’ve also been thinking about it. If you sell 1000 $300,000 units the average and median price is $300,000. If you toss in one $4M unit (1001 total units) the median price remains $300,000 but the average moves up to $303,696 and 101.2% over median price according to Excel. Can the Big Fish Theory explain the difference in median/average?

  12. Charles-

    If we use big fish to explain the large rise in average price, then we are pushed toward using the median as a better measure of central tendency.

    What we have is a reduction in gross volume by about 23.5% and a reduction in the number of sales by 29%. I would suggest that this does indicate big fish. In conclusion, I do think that the appreciation is representative of a shift in the distribution of sales, most likely a result of the subprime mess.

    That being said, I am very concerned about the gross volume. Gross volume is down by about 23.5% (Dec 2006 to Dec 2007). This is amplified with the inventory in months. We have gross sales volume going down and inventory going up. Does appreciation matter given high inventory when sales volume is going down so much?

    In other words the sales that are being made are on the top end, rather than the bottom end. In fact the average sale missing is about $260,000. I computed this by using the $162M in missing gross sales and dividing it by the 624 missing closed sales. $162M/624 = $260k. In other words, the sales volumes would have matched up better if we would have had an addition 624 homes sell at 260k. If this would have happened, then both the December 2007 average and median prices would have adjusted downward by quite a bit.

    I purchased some I Bonds back when the government calculation inappropriately computed inflation too high, in my opinion. The problem was that Katrina caused a disruption in fuel supply, and so the price of fuel spiked. The established US Government calculation over-weighted the impact of this. In other words, I was able to extract value from the government based wholly on their metric system. It appears the government was wrong–I did very well.

    This whole situation with the appreciation going up reminds me of Mediant Fractions and the Simpson Paradox:

    Mediant Fractions explained:

    A nice Java demo of Simpson Paradox:

    Wolfram’s Farey Sequence:

    Further thoughts?

  13. If you want to succeed in business, surround yourself with people smarter than you. I think JP just took the math part of this discussion to another level (one of the links wanted me to purchase the Simpson Paradox applet). I understand it but don’t feel qualified to discuss it in depth.

    Ultimately, we need to get back to his list of 12 points and the question we both asked:
    What does all of this mean, and what does the future hold is a bigger question.

  14. Forget the 12 points for a moment. What is most important here is that we are all safe and sound. When I read that the Turners were outselling their competition, I was very happy.


    Sure gross sales volume in the total market is down by about 25%, but the Turner’s volume is up. I am not recommending anyone to become a new agent with this data.

    Interestingly enough, from a marketing standpoint (specifically defining the customer), it appears that Charles is in a very good position. His customer base is largely unaffected by the subprime mess, so he is helping push that appreciation number higher.

    My first conclusion from all of this: Now is not a good time to become a real estate agent, unless you have some solid connections to the top end, and even then there is a great deal of risk for a new entrant. It’s not just anyone who can sell those $500k+ homes. (I also note that Charles has earned an MBA–I am sure that helps maintain his edge with the top end customer base. I don’t want to ignore that Jennifer earned an MBA also.)

  15. Further thoughts?

    Anyone have the standard deviation figured? 🙂

  16. Perhaps this is a purely North Portland perspective, but in addition to a “big fish data skew”, a “lack of small fish” can also skew the average, and could be responsible for some degree of the average price increases.

    In my neighborhood (Boise/Humboldt), even though the price of a standard 2-3 br. renovated home has gone down, the ratio of fixed up houses to fixers is leaning more to fixed.

    Also, in an area where density become marketable- i.e. wealthy people don’t mind living in multi-family housing- you see the prices of the land minus the structure exceed the structure plus land value.

    Distressed 2br homes, for example, have increased greatly in value because they are so easy to knock down and replace with a duplex.

  17. george-

    Your “lack of small fish” claim is easily be refuted by the relatively stable median price.

  18. (more commentary after george’s comment)

    13. For the year 2007 versus 2006, both the median price and average price have increased by about $20k, or about 6.5% (there are two bases here, so I just approximate). This is a positive indicator, and it says that the purchase price of homes have increased by $20,000.

    Note that this is very positive, as the final purchase price has increased by $20k both in median and average terms. Rather than get into complicated metric system reasons why there is a difference between the two, I will just suggest that the people are spending $20k more on average on a home purchase. Unfortunately the $20k more is being spent on fewer homes, as the number of sales is down.

    The questions:

    1. Who are the missing buyers?
    2. What was the purchasing behavior of these buyers?

    And the big question:

    What did a median home look like in December 2006 versus December 2007? In other words, did you get more or less home for the extra $20,000?

  19. After noting the “highly positive” note this:

    14. The median December 2006 price ($273,500) was 3,000 above the 2006 calendar year median price ($270,500). This is sharply contrasted with the more recent 2007 data.
    15. The median sale price in December 2007 ($276,500) was about $13,500 below the median price for the 2007 calendar year ($290,000). This is one of the most negative indicators so far.
    16. The December 2007 average sales price is about $9k more than the 2007 calendar year average sales price.

    I apologize for the three posts in a row. I certainly understand that I should consider the multiple aspects and make one post.

    Big question:

    In the light of the increase in average prices, at $276,500 what did a median December 2007 property look like versus the calendar year $290,000 median home?

  20. Easily refuted by stable median sales?

    Please do the math for me, because I don’t see it.

    The way I have seen things happen in North Portland is that there used to be many more properties in the sub $100k sold as “fixers, structure of no value”. Or heck, even lower then that.

    The homes that were in good shape sold for much more and represented the majority of sales.

    If you take the sub $100k’s out of the pool, the median price is just as unaffected as when when you add in a handful of $1mil properties. And the average goes up.

    Also, “big fish” and “small fish” scenarios are not mutually exclusive.

  21. “Easily refuted by stable median sales?

    Please do the math for me, because I don’t see it.”

    I guess you don’t understand what the median price is. We order the homes by lowest price to highest price, and the median price is the one in the middle, or if there are an even number of homes, then it is the arithmetic average of the two in the middle.

    By definition the number of homes that sold to the left of the median is the same as the ones to the right.

    Now we have to look at the distribution. For all practical purposes homes start at some value above zero. Charles suggested a lower bound of about $80k in a data set that he was looking at, but the bigger issue here is that we establish a lower bound of zero.

    The upper end is not bounded in this same manner. In fact Charles mentioned that a home sold for about $4M. If Bill Gates were really interested in a specific home, the sales price could go far beyond $4M, but that would clearly be an outlier. Again the upper end is not bounded like the lower end. In any event, using the $4M as an example, the upper end is several times the median price.

    Taking December 2007, the median price is $276,500. Ignoring some edge issues, this means that 50% of the homes sold for less than $276,500. Also 50% sold for more than $276,500. (Again, I have ignored the center edge issue, which really isn’t that important anyway.)

    We now know that 50% sold:

    1. between $80,000 and $276,500
    2. more than $276,500 (but given the market the top end was probably not much more than $4M)

    In December 2007 more than 50% of the homes sold for under the 2007 calendar year 2007 median price. Also in December 2007 more than 50% sold for under the 2007 calendar year average home.

    Therefore there are plenty of small fish.

    The “textbook appreciation” number is based on the average price, which is increasing in light of the much lower median price. I suggest that one possibility is that homes on the high top end are selling better than in the past.

    The lower end really does not have much room. As a practical matter, that $80,000 home is probably an outlier, so eliminating these outliers, we can probably push the lower bound up. There are plenty of homes, however, that sell for double the average price, so we cannot suggest that the top end is just full of a few outliers.

    So what we have is about 50% of the homes sell in a range of about $100,000. Specifically between about $200,000 and $300,000. Of course I don’t have the specific data set to give precise numbers, but these are accurate (to a degree of certainty that I cannot determine).

    Now let’s look at the gap between median price and average price. This is increasing, and in a year went from a five-year low to a five-year high. Since we have already established that this is little room in the bottom end, relative to a median home, the top end has increased drastically.

    Thus the number of small fish relative to big fish has remained constant, but the big fish have gotten much bigger.


  22. Seems like a little applied knowledge would help you…

    In a typical neighborhood in Portland (lets use Boise), a year or two ago, prices would bottom out at say $100-120k, which would represent land value minus demo cost. (a lot without a house would be worth more then a lot with a severely distressed house)

    In that same neighborhood, there was a practical limit to home values based on the housing stock and market. Say, all the homes were built in a 10 year period, and most were similar square footage, similar vintage. Crime levels, services, schools also define an upper limit to home values.

    At that upper limit 1-2 years ago things would top out at around $300k or so. With a few upper limit outliers hitting $400k or so. A few months ago Boise broke the $500k mark about twice.

    So the relatively high level of distressed homes had an impact on the average as they counter-balanced the upper end homes. Median AND average at $200k, lets make up a data set of two $200k sales, one $300k sale, and one $100k sale. That would really not be very far from a typical week.

    So, remove those $100k properties from the market and suddenly the average moves away from the median. As a practical matter, this is happening as there are a finite number of lots.

    Let’s go fully nautical here and mix a metaphor- the “big fish” were “anchored” by the “small fish” from affecting the average. Remove the anchor, and the average sails/swims away from the median.

    Of course, my analysis is based on a single neighborhood, but I can think a many more that have very similar things going on.

  23. Guess JP et al have enough data to chew upon til the next month’s report. I am happy that it is keeping them busy.

    But anyways as always Portland continues to do good despite the softening nationwide. Says a lot about the stability here and should add confidence to long term realestate investing here.

  24. Here’s a thought. If houses are not selling how can you demonstrate a decline or appreciation. I have been watching my old neighborhood area(Hawthorne/Buckman/Laurelhurst) and I am seeing some houses priced fairly low and just sitting, some for over 6 months, where as two years ago they would’ve sold at that price in a few hours.

    So, I guess until we see what happens over the next 9-10 months we really can’t make a good assessment of what’s happening here. If these sellers really need to sell, how low will the prices go. Time will tell.

    BTW I am seeing a lot of “motivated sellers” not only on CL but also on RMLS. Let’s see how motivated they really are.

    Another thought to munch on… why would anyone sell in this flooded market unless they had to?!?!

  25. george-

    Your example is not skewed either direction. You have a median = mode = arithmetic average = $200,000. This is very idealized, and it does not represent the true housing market.

    You are right, however, if there was a shift in the distribution of below median home purchases, then the average could be going up while the median sales price remains the same. In fact, it could be that all the lower end homes are approaching the median price, as you suggest. But, we have a falling median price, and the median price for December 2007 is $13,500, or about 4.7% below the 2007 annual median price. In other words, the median sale price is falling, but the average sale price is increasing. In addition we have other data sources that suggest that the asking prices are eroding. (Including, but not limited to, tracking services such as housingtracker.net, personal observations in a multitude of neighborhoods, and the increase in foreclosures)

    I use the “big fish” from a post Charles made about “small fish.” The small fish were blamed for a big drop in prices, so I asked if big fish could explain the increase in prices.


    The numbers being tracked here are current sales prices. In the short-term, there is a possibility that every individual property decreases in value while the average sale price increases.

    The example is this: If every property is reduced in price by 10%, but each individual buyer increases their purchase amount. In this case the buyer looks at a more expensive home, net of the 10% discount.

    Specific example:
    Take an average home at $300,000. I am looking at the average home which cost $300,000, and there is one down the street that I would really like, but I am not willing to pay $350,000 for it. Prices come down by 10%. Now that all prices are reduced 10%, so I can purchase the $300,000 for $270,000. While this seems like a deal, instead I but the $350,000 home for $315,000. According to the sales data, it looks like a $300,000 home went to $315,000, but what really happened was a $350,000 home went to $315,000. I understand this model is way too simple, but it illustrates the weakness of using sales prices when the underlying homes shift.

    One of your most interesting statements is, “If these sellers really need to sell, how low will the prices go.” This is a cash flow discussion. Remember the BVH auction? Yes, prices went down, but there was an injection of medium-high priced homes. The homes sold well above both the median and average prices in the Portland area, yet the management suggested they were sold at a loss.

    I am still waiting for someone to answer this question:

    In the light of the increase in average prices, at $276,500 what did a median December 2007 property look like versus the calendar year $290,000 median home? (Is a median December 2007 buyer getting more or less than the median calendar year buyer?)

  26. JP-

    This is just one persons limited observation: mine! About 8-9 years ago when we bought our first house our price range happened to also be around the median price at the time. You could get a decent 3/2 close-in east side, nothing fancy, though also lots of fixers in that range. Mind you we only looked in the range of I-84 to SE Division and the river to about 50th. Now as we look around our price range is once again about the median price but now the homes are a little bit further out, and many are refurbished: floors, surfaces, new electrical and plumbing. Thats a big difference that I see compared to 1998ish.

    Another thing I am noticing…a lot of these homes now are vacant or have renters.

    So even though I dont have concrete stats I feel that you get a better quality home for the median price.

    Just a little observation from one potential buyer.

  27. JP-

    Glad we now agree on the math regarding “lack of small fish” being able to raise the average and not affect the median. I was beginning to think my brain was on the fritz.

    So, back to my idealized example. Using that, its easy to see averages going up and medians going down. It also confirms my general impression that prices for homes are indeed going down, and that the market data is not a good measure of appreciation in this market.

    Say you have that same neighborhood, $100k sale, 2 $200k sales, and one $300k sale for 2006. Then in 2007, remove the $100k sale, and drop everyone’s price by 5%, so you have 2 $190k sales and one $285k sale and you get a drop on median and an increase in average price.


  28. george-

    But you are using a data set that is so different from the given market. Your model and example might be true, if it actually represented the market conditions of today.

    Again, the problem is that the median price is falling, and there is not enough space at the bottom for your claim to be true.

    Also we must consider this in the light of the subprime lending mess–the bottom has been affected much more than the top end.

    I suppose we could assume that the above median homes did not change in value, and then figure out just how much those below-median homes would need to go up in value to affect the average, but this is problematic in a market that is pushing the median price lower.

    Could there be small amount of increase from what you are suggesting? Of course.

    The homes on the top end, however, are several times the median price. In other words the average price is sensitive to the top end, not the bottom end as you suggest.

    If I had the time, I would perform a sensitivity analysis on the distribution of home sales.

  29. george-

    One more thing: Our final conclusion about the market is the same, but our reasoning is slightly different.


    1. We both agree that by itself the “textbook appreciation” number might not be a good measure of underlying market conditions.
    2. We agree that there is a shift in the distribution of homes being sold, but we disagree as to whether it is top or bottom end, but we both agree that it could be a combination of the two. Recognizing that, I suggest further, however, that there isn’t enough room at the bottom end for the bottom to be much of an issue.

    Ultimately I think we agree on our final conclusion, even if we give a slightly different justification.

    Over the next couple of weeks I will be thinking about that sensitivity analysis as well as recurrence relationships.

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