The latest FHFA House Price Index (HPI) data came out for the First Quarter of 2018 and I thought I’d spend some time on those stats. You’ll see in the chart below that the Boulder County MSA, the metro Denver MSA and the State of Colorado are all off their peaks in appreciation as our market shows some deceleration. Overall, the US is still showing increasing appreciation. It’s important to note that even though appreciation is slowing, it is still positive, with Boulder County still experiencing 8.25% appreciation over the last 12 months.
The Boulder MSA remains very strong compared to the other 245 ranked MSA’s across the Country as you can see in the chart below. As I’ve noted before, when you look at appreciation since 1991, our local MSA’s remain very strong, placing First, Second, Sixth and Thirteenth. Here’s a table showing how the different areas rank. It is interesting to note that the 10 metro County Denver MSA is showing stronger appreciation than Boulder County in the shorter timeframes. Since the Denver MSA has an overall lower price point than Boulder County, I think they continue to experience more of the frenzied appreciation we’re seeing occur on the lower end. Overall as a State, Colorado ranks second or fourth in the individual time frames.
|1 Quarter||1 Year||5 Year||Since 1991|
|Boulder||2.21% – 56th||8.25% – 68th||62.56% – 28th||390.93% – 1st|
|Denver||2.37% – 47th||10.18% – 28th||69.09% – 16th||349.19% – 2nd|
|Ft. Collins||1.84% – 82nd||7.98% – 75th||58.40% – 34th||316.16% – 6th|
|Greeley||3.50% – 15th||12.63% – 5th||70.13% – 15th||274.76% – 13th|
|Colorado||3.37% – 4th||10.63% – 4th||62.75% – 2nd||355.99% – 2nd|
Surprisingly from our local perspective of a hot market, the HPI report still shows MSA’s across the country that are experiencing depreciation. Not everyone has been having the appreciation we’ve been experiencing since 2012. Of the 345 total MSA’s across the country, 19 have had negative appreciation over the last year or last 5 years. Still some scattered parts of the country that have suffering home prices.
Two other items of note from the FHFA HPI report. The rebound in national prices has now easily surpassed the peak in 2006 before the national downturn. We also finally have every State showing positive annual appreciation, but the rates vary from 0.9% to 13.7%. I hope everyone had a great Memorial Day!
Last month we talked about what a high-end home was. After looking at the data for Boulder County for the last 16 years, I came up with the answer that the top 3% of the market was the high-end. In the raw data, there was a hitch in many years when you reached that 3% level, a jump larger than other increments that implied there was something different as you moved from the top 4% to the top 3%. After looking at all of that data, I was also left with the curiosity to see how those price levels played out across the individual cities in the County. As usual, some time with my head buried in Excel and I have some answers and some further questions. Here are the breakdowns for the individual Cities in the County for 2017 Sales using IRES only data, the chart of Single Family homes first, Attached homes second and combined third.
You can see that I’ve highlighted in yellow the sales price for each city that would have put that home into the top 3% of all 2017 sales for both single family and attached. The first thing I realized when I looked at this city by city data is that the hitch in my data at the 3% level has disappeared. When comparing prices within each city, apples to apples, there typically is just a smooth transition between the different price percentiles. An interesting result and one that throws out my assertion that there was something special about that 3% level.
Another thing that jumped out of the data is that we live in an expensive area, I know, shocking news. The Median Price for a home in the State of Colorado is $363,386 and for the nation as a whole, $213,146. The most affordable City within Boulder County is Longmont with a Median Price higher than the state median and far higher than the national median. 40% of City of Boulder sales were over $1M in 2017 and surprisingly to me, over 6% of City of Louisville sales were over $1M.
The more I contemplated this data, I also came to the realization that comparing City to City also has issues. We know of many areas where a City line is drawn, and on the other side of the City line is a subdivision composed of homes in a much different price point that gets included into a different area. Think of Portico (Suburban Plains) versus SW Longmont, Boulder Country Club versus the rest of Gunbarrel (the City of Boulder parts and the Suburban Plains parts), and White Hawk Ranch (Suburban Plains) versus the City of Lafayette. One other area of question, the Suburban Mountains. I would bet without looking that most of the high-end sales in that area were for the very close in to Boulder properties and not the homes up by Allenspark. I’m sure there are other similar areas as well scattered throughout the County. So how do you account for those differences? Should those areas be lumped in with the nearby Cities or not? This is really more of comment on the Area/Subarea structure of the MLS data. Possibly something that worked well in the past but today it may just be causing more confusion.
I’ve had a couple of weeks of thinking I’d answered something about the high-end, but further reflection tells me my definition doesn’t work. I’ll have to keep contemplating this question.
This month I want to chat about an issue that has been bugging me for some time. What is a high-end property? You’ll frequently see statistics, articles and analysis of the over One Million Dollar market, but with the average sales price of a single family home in the City of Boulder at $1.09M in 2017, does talking about the One Million Dollar market as something special or different make sense? After all in the City of Boulder today, a million dollar home sale just means that sale is average, not something special. I already had all of the data for Boulder County sales going back to 2002 that were reported to IRES, so after some spreadsheet formulas I was able to start zeroing in on what a high-end property means today.
Back in 2002, a million dollar home sale meant that home was one of the top 1.29% of the sales across all of Boulder County. As of the end of 2017, a million dollar home sale means that home was one of the top 10.26% of the sales in the County, not nearly the same cachet. To be in the top 1.29% of the sales in 2017, a home would have had to sell for $2.1M. I didn’t take the time to break this data down into smaller market segments like individual cities, but looking at the overall County data, it felt to me like the top 3% of homes sales deserved the label of the high-end.
Some interesting things appear when I charted this data. The high-end reacts to market forces differently than the median and average price points, which makes sense. For most people, a home is a necessity, something that is purchased and held onto through good and bad market cycles. For high-end homes, we see the market downturns have a bigger effect as these homes usually aren’t a necessity but a luxury.
Another interesting item in the data, the high end homes were up by 114% since 2002 while the average home was up 81% and the median home was up 89%. Some of this discrepancy may be due to Affordable Housing program homes that remain in the data, but this better appreciation rate for the high end of the market was a surprise. Another possible explanation is that the high-end of the market is a smaller market segment, in 2017, the top 3% of all sales was only 147 sales. One or two exceptionally high high-end sales could be skewing those numbers and in 2017, there was one sale for $13.1M, a 23 unit income property in downtown Boulder.
As with any statistics debate, these numbers are County averages and may differ for your area. Obviously a high-end sale in the City of Boulder means something very different than a high-end sale in Longmont. I may dig back into the data and try to pull out what the top 3% of sales are for the different cities for a future article. Hope everyone has a wonderful spring!
Another article this month looking back at how 2017 played out compared to previous years. This month I want to take a look at sales price to list price ratios. This year, as in previous years, I’ve removed seller concessions from the sales prices, hopefully making these sales price to list price ratios as accurate as possible using IRES only data for Boulder County.
I first looked at the percent of the market that is selling for over asking price and how that metric is trending over time. In 2017, the percentage of both Single Family and Attached Homes selling for over asking price moderated and dropped from the 2016 levels. Just under 50% of Single Family Homes sold for over asking while Attached Homes saw just under 65% sell for over asking. This was a decline of 7-8 percentage points from the levels we saw in 2016. More importantly, this is the second year we’ve seen this metric decline for Attached Homes and both metrics are now declining likely indicating that we’re entering a new downward trend pattern.
The second stat I wanted to revisit again was the sales price to asking price ratios and how those ratios change depending on how quickly the home goes under contract. As you would expect, the more quickly the home gets snatched up, the more likely the sales price was to be at or over the asking price, but we saw that trend moderating some in 2017. For Single Family Homes that went under contract during their first week on the market, just under 70% sold for at or over their asking price. This was a decline of about 6 percentage points from the levels we saw in 2016. We also saw about 6% fewer homes sell during their first week on the market and increases in the numbers of homes selling during the third week and on, another indicator of softening in these stats. The one quirk to this IRES data that I haven’t been able to eliminate is the possible inclusion of properties that were withdrawn and then re-entered with a new MLS # and possible new asking price that then sell quickly even though they have a lengthy combined days on market.
|Single Family||Week 1||Week 2||Week 3||Week 4||Week 5||Week 6+|
|% of all 3,391 Sales||38.78%||14.13%||8.61%||5.81%||5.37%||27.31%|
|Asking or better||69.96%||38.41%||23.29%||24.87%||19.23%||17.82%|
|<80% – 95%||2.66%||4.80%||7.88%||13.71%||14.84%||22.79%|
|95% – 97%||3.04%||10.44%||16.44%||18.78%||16.48%||16.74%|
|97% – 99%||11.41%||29.65%||37.67%||29.95%||37.36%||31.75%|
|99% – 100%||12.93%||16.70%||14.73%||12.69%||12.09%||10.91%|
|100% – 102%||36.50%||26.51%||17.47%||18.78%||15.38%||15.23%|
|102% – 105%||19.32%||7.10%||4.11%||4.57%||2.20%||1.51%|
In this graph, I’ve plotted, in separate colors, the Single Family home sales per the week they went under contract. The expected strength in the properties that went under contract in the first week is displayed in blue. As we saw in 2015 & 2016, those “under contract in the first week” properties had numerous sales that were at asking price through sales that were up to 10% over asking price. It’s not until homes have been for sale into the third week that you start to see the peaks in the chart at something less than asking price. One other quirk in the data that I didn’t attempt to adjust for was properties that went under contract, had a buyer back out and then re-entered the market.
If we look at these same stats for Attached Homes, you’ll see that this market segment is also softening compared to last year but remains stronger than Single Family. Attached Homes that went under contract within the first week on the market sold for asking price or better 76.01% of the time, more than 10 percentage points lower than 2016. During 2016 more than half of the Attached homes went under contract in the first week and last year that number dropped about 5 percentage points to just under 47%. As we saw in 2016, there is far more strength for close to or at asking price sales in Attached Homes past the first week on the market than we see for Single Family Homes. For some reason about half of all Attached Homes sell for asking price or better after the first week except for those homes that go under contract in week 4. Hard to tease a reason for this out of the data, could be overall lower prices for Attached homes, odd price reduction effects, or more demand for that entry-level, affordable price point.
|Attached Homes||Week 1||Week 2||Week 3||Week 4||Week 5||Week 6+|
|% of all 1,315 Sales||46.92%||14.22%||7.07%||5.32%||5.25%||21.22%|
|Asking or better||76.01%||45.45%||48.39%||28.57%||46.38%||40.14%|
|<80% – 95%||1.62%||4.28%||5.38%||7.14%||5.80%||6.45%|
|95% – 97%||1.46%||8.02%||7.53%||7.14%||7.25%||16.49%|
|97% – 99%||8.91%||25.13%||30.11%||44.29%||33.33%||26.88%|
|99% – 100%||11.99%||17.11%||8.60%||12.86%||7.25%||10.04%|
|100% – 102%||44.73%||34.76%||38.71%||25.71%||46.38%||35.48%|
|102% – 105%||19.29%||6.42%||6.45%||1.43%||0.00%||2.15%|
In the chart below, we take the same Attached Home data and display that date per the week in which the property went under contract. As in the Single Family graph, you see great strength in the properties that go under contract in the first week. Oddly, for Attached Homes, only in properties that go under contract in week 4 do we see the numbers peak at less than asking price.
Interestingly, all of these 2017 metrics show softening since 2016 and yet the subjective feel of the market so far in 2018 is a strengthening market with many properties that lagged on the 2017 market suddenly getting snatched up. Hard to tell which signal to trust as we move further into the year. Could be that the strength we’re feeling is due to very small numbers of available homes and I can see that lack of available inventory continuing throughout the year. Could be that the softening may accelerate if mortgage rates continue to creep upwards. Only time will tell.
A new year and a new bunch of stats to sift through for meaning. It definitely seems as if the market is shifting, but some strong performance at the end of the year and a strong start in 2018 has me debating where we’re headed. This year is also the first year without data share between IRES and REColorado and I’m sure that affected our numbers, but how and to what extent is very hard to tease out without massive data consolidation efforts. To keep that variable to a minimum and to match all previous years these stats are all IRES data only.
It has been a great time to be a seller since mid-year 2012 and 2017 was no exception. While we did see a shift in the market, sellers still remained in control for most price points. The higher the price point the less seller control we saw. Entry level markets saw sellers choosing amongst many, multiple, strong offers. At the highest price points, sellers were not as fortunate and were much more likely to experience a balanced market. We continue to see wobbles in our stats with different metrics telling different stories. What is confusing is that not only are the different metrics telling different stories but that the metrics themselves are flip-flopping back and forth in their indications. This is very different than what we saw during 2013-2015 when all arrows were pointed straight up.
Annual sales numbers saw modest growth, up 6.47% from 2016. Single family homes saw a slightly greater increase at 7.15% while attached homes were up 4.70%. This is one of our unusual metrics, as typically in a strong market like we’ve been experiencing, annual sales numbers increase strongly. This held true during the last strong market we had in the late 90’s as you can see partially above. During this current strong market, our annual sales numbers have been bouncing up and down each year but holding generally in the area of 4,500 home sales.
Here is our current level of single family inventory, with 2018 levels setting a new all-time low. That is one of the interesting things about our market, strong price appreciation that isn’t causing more sellers to put their homes on the market. I think this is due to two factors, one the aging of the Boulder County populace and two the lack of new home construction activity we have. According to the State demographer, Boulder County will see a 77% increase in the number of people 65+ in Boulder County between 2015 and 2030 and as a general rule, as people age, they move less. We are also almost done with large scale new home developments in Boulder County unless we dramatically change our land use policies. Without new homes being built in large quantities and with our growing population, you get a musical chairs situation. People don’t want to put their home on the market for fear the music will stop and they won’t be able to find their next home in the County. We’ll be watching this chart this year to see if we again see larger inventory numbers mid-summer like we saw last year. I am becoming more convinced every year that the light red area in the chart above is the new-normal range for our inventory levels due to the two factors we discussed above. With lower inventory levels likely to be a somewhat permanent issue, I don’t see home values dropping dramatically for the foreseeable future. High demand and low supply are always good for prices.
The next chart is one of the charts showing that the market is shifting. Overall percentages of properties under contract has been dropping since our peak in the summer of 2016. To me, this shows that the market is returning to a more balanced level but is still strong. The current downward trend doesn’t concern me as an indicator of poor market, just a slowing market. Many of my fellow stats nerds feel that we see price appreciation for any market that is at least 25-30% under contract. If our current downward trend continues to the point that our under contract percentage is approaching that 25-30% level, then this would be concerning.
Another possible source of friction that could slow our market is rising interest rates. It seems like we’ve been expecting rising interest rates every year since we escaped the Great Recession and so far we’ve mostly called that wrong. As you can see in this next chart looking at 30 year mortgage interest rates over the last 5 years we’re starting to see some upward movement. What we can’t predict though is if this current upward movement will be permanent or another buildup in rates that slowly deflates again like we saw in July 2013, early 2015 and again in early 2017.
This is my one chart pulled from REColorado data showing the number of Boulder County sales recorded in REColorado over the last five years. The large jump in 2017 is indicative to me of the many IRES-only brokers forced to join and entering their Boulder County listings and sales into REColorado. I’m sure this has affected our stats as I’m sure there are also REColorado-only brokers who felt they had to join IRES to get their Boulder County listings in front of Boulder County brokers. My few attempts at downloading from both systems and trying to reconcile the two data sets has shown me that I don’t have the time, energy or statistical chops to create charts incorporating every Boulder County sale. You also have other off-MLS sales adding to the complicated mix. Hopefully someday, we’ll have a merged Front Range MLS system that includes historical data from IRES and REColorado, but until then, we’ll keep plugging along with the data we have. Have an amazing 2018!
The latest FHFA Q3 data is out for Boulder County and it tells the story of a changing, cooling market. For the first time since the second quarter of 2012, the Boulder County MSA saw negative appreciation from one quarter to the next logging a negative .58% appreciation rate from the second quarter to the third quarter of 2017. This leaves Boulder as one of only 26 MSA’s across the country to see negative appreciation when compared to the previous quarter.
Now, before everyone gets too concerned, do realize that the FHFA HPI data is constantly being revised and what shows up as a negative quarter today may well be adjusted back into positive territory with the next Q4 data release at the end of February 2018. While Boulder has fallen towards the bottom of the 253 MSA’s when it comes to quarter to quarter appreciation, we still remain 57th for annual appreciation and number one for appreciation since 1991. This negatively appreciating quarterly number does show though that the market is changing. Here’s the chart for annual appreciation rates.
Both Denver and Boulder show decelerating, yet still positive, annual appreciation rates in the chart. Interesting that Denver is decelerating less sharply than Boulder which is likely due to better affordability in the Denver MSA. Hope everyone has a wonderful holiday season.
The shift in the market seems to be coming clearer as we move into the fall. Homes are taking longer to go under contract and inventory is building faster than sales. The shift is still patchy however in that certain areas and price points are still very active. I’ve even seen this patchiness within neighborhoods as some homes get scooped up quickly while others can linger on the market. Buyers are once again caring about finishes, upgrades and location when comparing homes. Homes with negative issues are starting to again be penalized by the market, just being for sale is no longer all it takes to move a home.
One of the metrics that is displaying a marked shift that caught my eye recently is the percent of homes under contract across all of Boulder County. This summer, this metric didn’t rise above 50% under contract like the last two summers. It is also now displaying an under contract percentage that is below what we saw during any point in all of 2015 and 2016. A definite shift in the market.
To try and display data that backs up what I’m feeling in the market, I also plotted the number of homes available for sale that aren’t under contract and the number of homes that are under contract for the same time period going back over the last 5 years. In the chart below you can see that the inventory of homes available for sale had been dropping for the previous four periods but this year has sharply reversed trend. The number of home under contract meanwhile has stayed fairly constant throughout. Homes Available increased almost 18% compared to last year while the number under contract grew only 3% during the same time period.
So, inventory is growing strongly while sales have only increased mildly. A big question though is this change in trend a seasonal pattern or indicative of a market shift. Since we’re comparing these numbers for the same date going back over the last 5 years, I don’t think we’re seeing a seasonal pattern, but I’m not sure we’ll be able to answer that until we see how spring of 2018 plays out. Enjoy the changing seasons!
The latest FHFA House Price Index data came out for the Second Quarter of 2017 and I thought I’d spend some time on those stats. You’ll see in the chart below that Boulder County MSA, the metro Denver MSA and the State of Colorado are all off their peaks in appreciation as our current cycle shows some weakness. Overall, the US is still showing increasing appreciation.
The Boulder MSA remains very strong compared to the other 354 MSA’s across the Country. Boulder ranks 1st for appreciation since 1991. Interestingly, Denver is 2nd and Ft. Collins is 6th. When looking at 5 year appreciation, Boulder ranks 31st, Denver is 22nd and Ft. Collins is 36th. For one year appreciation, Boulder ranks 20th, Denver is 17th and Ft. Collins is 10th. One quarter appreciation, has Boulder ranking 85th, Denver is 48th and Ft. Collins is 67th. The Denver Metro MSA is comprised of the City & County of Denver, the City & County of Broomfield, Jefferson County, Gilpin County, Clear Creek County, Park County, Douglas County, Elbert County, Arapahoe County and Adams County. In many of these rankings the Denver metro MSA is out stripping the Boulder County MSA and I think this is due to the generally lower price points in the Denver Metro MSA. They have more room for the frenzied appreciation we’re seeing occur on the lower end. Below is a chart from the FHFA website showing those appreciation numbers for the three MSA’s.
Sometimes I have a great idea for a new statistical chart after a conversation with a colleague. After a conversation with John Hampshire at my office, I decided to see if I could chart the Sales Price to List Price ratio for real estate sales in Boulder County over the last 6 years. The expectation is that during the spring when the market is most frenzied, that this ratio would show a much higher percentage that would gradually decrease throughout the year to the slowest time in the late Fall. This chart could then be used to show sellers the best time to get the highest price and buyers the best time to get the best deal.
Like many great ideas, this idea didn’t survive first contact with reality. I was able to pull the data without too much effort but that was the last easy step. A quick look showed SP/LP ratios that ranged from 19.79% to 559%, not what I expected. A quick look at some of the outliers to figure out my next action. The 19.79% sale was for a single family home that went under contract pre 2013 flood but closed as a piece of vacant land post 2013 flood. Many of the other very low ratio sales were for small mountain acreages that took multiple years to sell. First massage of the data, take out all of the Vacant Land sales.
Next, moving to the opposite end of the spectrum, how did something sell for five and a half times the asking price? Some more research determined this was a vacant land parcel that was sold in conjunction with the $2M+ dollar home next door and the combined price was reported for both the home and the vacant land. Where do you stop though? I can’t comb through 27,949 sales in my dataset and make corrections to each one. Also, some New Construction Homes really do sell for almost 200% over asking once you add in options, lot premiums, appliance packages, etc. A couple more massages to the data to correct the most egregious outliers but most get left in.
Next dilemma, what timescale do I use? Charting the sales by actual date seems like it would give too much movement. Charting by month seems like too little movement. I finally ended on Week #’s of the year, weeks 1 through 52. Still some issues with this approach too. Week 1 of 2016 didn’t contain a single business day, so no sales possible that week but still seemed to be the best approach.
Next dilemma, do I use the Sold date or the date the property went Under Contract. Contract date would more accurately reflect the market strength or weakness at the time the contract was negotiated, let’s go with that. “Shoot” (or something unprintable) Contract date isn’t a data field I can download out of IRES, Sold date it is. Sold date however is probably offset 30-60 days from contract date and the market conditions that existed then. I decided not to try and chase down that source of noise in the data.
So, after all of that, below is what my efforts came to, a metric that doesn’t really tell you anything. There isn’t a clear pattern to the SP/LP ratio throughout a year. Too many spikes and drops from outlier data. No clear trends in the shapes of each year. Only clear trend I can see is that the most recent years have had a higher SP/LP ratio than the years closer to the Great Recession. A shocking new insight to everyone I’m sure. I guess the lack of a clear pattern is an insight in some ways. There isn’t a consistent pattern to our market where a certain time will always produce a better or worse SP/LP ratio than another time. There will always be some sellers and some buyers more flexible than others.
Luckily not all was lost. For those of you who have ever downloaded large numbers of sales out of IRES, you know that there is a maximum cap of 2,000 records that can be exported at any one time. Since every year 2011-2016 has had more sales than this limit, I had to break my exports out into less than 2,000 sale chunks. The easiest way I have found to do this is by sales price. First chunk 0-250K sales, second chunk 250K-550K sales, etc. What became apparent as I made these downloads was that these chunks were changing dramatically over the years. This isn’t a dramatic insight, we all know our prices have been appreciating, but I was really struck by how we have lost the entry level of our market.
This insight was much easier to translate into a chart (next page). Each year on a 3D graph showing the sub-400K market in Boulder County for both attached and detached sales. You can clearly see the market shifting to the right towards higher sales prices. 2011 at the back of the chart to 2016 at the front of the chart. A stark visual reminder of how our market is evaporating for entry level buyers.
Hope everyone has a great August!
Many of the brokers that I chat with about stats are commenting on how they feel a change taking place in the market. This change isn’t uniform across Boulder County yet, but I suspect by the end of this year, we’ll all agree the days of instant offers and annual appreciation in the teens will have ended.
So aside from gut feel, what stats are starting to show a change? One of the ones I keep an eye on is the percent of single family homes in each area that is under contract. You can see in the chart below that we have rounded over the top in this metric. While there was a small drop from 2013 to 2014 that ended up not signaling a change, the drop so far from 2016 to 2017 seems significant enough to signal a change. We’ll eventually have further data to confirm this change and then get an idea for the slope of the change. Once we have a confirmed shape to the new direction, we can call when we break out of the new trend at some point in the future.
I maintain these same stats for each sub-area in the County. That chart is more interesting in that you can watch the individual cities move up and down as compared to the other cities in the County. I have been tracking these stats since 2004 and a very interesting change has occurred since then. Back then, the City of Boulder was always a top performer in this chart, frequently having the highest percentage of homes under contract in the County. Since the Great Recession however, the City of Boulder has been towards the bottom of the chart and lately has been tracking below the County average. Longmont and Erie back then were usually at the bottom of the chart but recently they’ve been trending much higher. I think this change is a reflection of affordability. As prices within the City of Boulder have climbed dramatically, the relatively lower prices further out in the County have driven demand outside of the City. One other observation, the Suburban Plains have been a perennial underperformer compared to the other areas within the County.
We’ll be keeping an eye on this chart as the market potentially shifts. Dramatic changes in the positioning of the competing subareas will give us some insight to what’s happening and how big a factor affordability is playing.
Hope everyone had a wonderful Fourth of July!