Consumer Advocates...Not Sales People
 
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Key Points

Some key points about the housing stats we've put together in this section. Please see our technical comments on our real estate stats for more detail.

  • Cities Covered: Our stats cover the major communities in Boulder County, Broomfield County, and northern Jefferson County including Boulder, Gunbarrel, Louisville, Lafayette, Superior, Longmont, Erie, Arvada, Broomfield and Westminster.
  • Data Sources: Our data is drawn from two MLS systems, IRES and Metrolist, and from county real estate tax record data compiled by Metrolist. The tax record data includes sales of new homes, foreclosures and private sales that may not be included in the MLS data, while the MLS data provides other kinds of information that isn't available in the tax data. Where we've used data from both the MLS and tax records, we've used a green background in our charts. Where we've used only tax tax the charts are on a blue background and they are on a brown background where we've used MLS data only.
  • House Type and Size: Real estate sales and pricing data is most commonly reported on a community basis, providing information on the average sales price or the number of sales in Louisville or Superior for example. In contrast, we report data on houses of various sizes within the communities we cover. This allows us to compare sale prices for comparable houses in different communities, to track price increases or decreases in comparable houses within a single community over time, and to see when the sales dynamics of large, mid-sized and small houses are differing under varying market conditions.
  • Organization of the Data: We reported the same data in two ways in these sections of the web site. In the final section here, we've organized the data on a community basis, reporting data on prices, long term appreciation, sales numbers and speed of sale for large houses, mid-sized houses, small houses and condos in each community. This makes it easy to see whether condos or small houses are selling more quickly in Boulder than large houses or whether large houses or small ones have appreciated more over the long term. Elsewhere in this section, we've organized the data based on house size/type and allowing easy comparison amoung the 10 communities we cover. Here it is easy to compare the cost of a 900-1600 sqft house in Boulder to the cost of a similar house in Longmont.

A Brief Comment on Using Stats in Making Buying Decisions

You can spend a lifetime analyzing real estate statistics and still remained baffled by some of the dynamics of the real estate market. Still, it can often be very useful for home buyers to spend an hour or two looking a statistical data on the real estate market in which they are planning to buy. Stats can give you a sense of whether prices are rising or falling, what communities you can afford to buy in, and whether properties are selling quickly. They can also give you an objective basis for evaluating claims about whether you're in a buyer's market or a seller's market.

But to give fair warning, studying stats can also help you make bad decisions. For example, many buyers want to use stats on price appreciation in various communities as a basis for deciding whether they should be buying a home and where they should buy it. While you shouldn't ignore sales stats in making these decisions, you need to remember that "past performance does not guarantee future returns." Stats are historical data and shouldn't be used to try to predict the future, at least not in isolation from other information about the community and market.

Technical Comments on Our Real Estate Statistics

With those caveats covered, you should take look at the stats compiled by the Boulder Area Realtor Association (BARA), in addition to the stats on our site. You can access several years' of their monthly statistical reports by selecting "Sales Statistics" from the list in the upper right corner of their home page.

Since our stats and those provided by BARA cover many of the same communities and use the same MLS as their data source, the same general trends will be reflected in both. However, we do use different subsets of this MLS sales data, and we use it in different ways. Some important points of explanation and clarification:

  • Both set of stats are based on sales data for properties that were listed and sold through the MLS database system used by Realtors. Data from properties that were not "listed" by real estate agents, but were sold independently "by owner" will not be reflected in these data. Still, because about 90% of sales occur through the MLS system, these data do provide a good picture of the market.
  • While both sets of stats cover the Boulder County market, there are some differences in how the parts of the county are covered. On the one hand, the BARA stats cover the mountain and plains areas outside the major cities. Ours don't because we believe the numbers generated are often misleading. There are too few sales and too many factors such as location and views that dramatically affect both sales price and time on the market in a manner. This makes it difficult to produce meaningful data in these areas.
  • While the BARA stats include sales of both new homes and resale homes, we limit our coverage to resale homes only. There are good arguments for either approach, but we feel that merging the two data sets is misleading. For example, builders often list new homes for sale when they get their building permit approved. Construction may not begin for a month, and it may be 3-6 months before construction is completed. This can significantly impact "average days on market" data which is intended to indicate how long seller's have to wait before they get contracts on their properties. As a result, "days on market" data for a city like Longmont, where there is a lot of new construction, may be significantly distorted.
  • The BARA stats not only lump together new homes and resale homes, they also lump together all homes regardless of size. There are reasonable arguments for taking this approach. Consider, however:
    • If the average size of Lafayette homes has changed over the past decade -- which is has -- historical data on price increases may exaggerate the amount that the price of an average 1500 square foot home has increased.
    • If the average home sizes home in Louisville and Superior differ -- which they do -- you may get a distorted picture of comparative home prices in Louisville and Superior if you use the BARA stats
  • To deal with this, our stats focus on classes of homes and condos that are defined by square footage. Our stats for "larger homes" reflect data on resale homes between 2300-3000 square feet in size, while "medium homes are 1600-2300 square feet and "smaller homes" are 900-1600 square feet. We limit our data on condos and townhomes to those that are between 800 and 1600 square feet in size. In defining each of these home sizes, we've focused solely on "above grade" living space square footage, ignoring the square footage in basements and garages. This makes it possible to compare sale prices of 800-1600 square foot homes in Boulder vs. Louisville, or to look at the rates at which prices have appreciated in a given community since 1995. Because these data allow you to compare "apples to apples," we feel that they provide a better picture of what is happening in the market.
  • Importantly, our stats provide data on the speed at which properties sell that is not provided in the BARA stats. Both sets of stats provide data on the average number of days that homes are on the market before the seller accepts an offer. However, we feel its important for our clients to know not only how quickly the average house sells, but how quickly the best properties sell. That's why we have data on what percentage of properties go under contract in 14 days or less and what percentage go under contract in 5 days or less. As a buyer, you just have to behave differently in a market where 25% of properties are going under contract in 5 days than in a market where only 5% are.
  • The BARA stats are updated monthly. Our's are updated quarterly.