Hey, it’s been a while. Since the start of the pandemic, demand for appraisal services has gone through the roof, limiting my ability to write. Thank you if you’ve sent me work. That said, I hope to write more frequently in 2022. This is the start.
Market Analysis Ground Rules
Below are market updates for Davis, Woodland, and the Northern Yolo County small acreage residential markets. My data source is Metrolist, the MLS for my region and part of the Norcal MLS Alliance. I’m very fortunate to have such great data partners.
For suburban markets like Davis and Woodland, I limit the analysis to sales of single family residences on one lot. I exclude condominiums, townhouses, halfplexes, and small income residential properties (2-4 units) because these types of transactions in general add noise to the analysis in markets I cover. For small acreage residential properties, I include one house on a lot, two houses on a lot, manufactured homes, and modular homes outside of city limits. I usually narrow the lot size range of transactions included in the analysis. For example, the analysis below is limited to sales on lots with 1-60 acres of area.
Sales volume in Davis was significantly higher year-over-year in early 2021 because of lockdowns in 2020 but over the past six months are down year-over-year because of the surge in late 2020.
My favorite way to measure sale price trends in Davis is to look at monthly year-over-year metrics because of the high degree of seasonality in the Davis market. Look at the graph below. The past six months prices are up on average 20% overall in Davis. Pre-pandemic, prices were stable to declining slightly…
Sales volume in Woodland has been distorted by Covid, too. Volume in early 2021 increased significantly over the prior year but were below 2020 over the summer of 2021 and are mixed most recently.
Woodland is a much less seasonal market than Davis so I use a sale price or sale price per square foot scatter graph model to show market trends. Prices have continued to rise in Woodland significantly over the past 12 months.
Davis and Woodland Recent Activity
Prices continue to show strong appreciation. The key issue is the lack of inventory. Normally, Davis and Woodland have 50-100 single family homes listed for sale. Lack of inventory is driving competition and prices.
Competition is frantic in Davis now with the vast majority of homes receiving multiple offers. Woodland homes are receiving multiple offers at a higher than typical rate, too, but not at Davis levels. Great time to sell, terrible time to buy.
Cash Buyers in the Market
With most listings receiving multiple offers, I’m not surprised to see a rising percentage of all-cash buyers.
These trends are telling the same story.
Northern Yolo County Small Acreage Residential Market
As noted above, I analyzed sales of properties on 1-60 acres sold in unincorporated Yolo County. I excluded Dunnigan because it is a different market from the rest of the county with 1 acre lots next to the interstate and many manufactured homes adding noise to the analysis.
With so few transactions, best way to understand the market is by sales per date scatter graph. First shows all sales from the start of 2020:
Those familiar with this market will be able to explain the price bump in 2016 and subsequent flattening. In early 2016, Yolo County changed the code to allow for medical marijuana grows on small acreage lots. This led to a rush in outside investors competing for small acreage residential properties and rapid price increases. When Yolo County put a clamp on new permits, prices stabilized and were relatively flat heading into the pandemic. The overall lack of inventory and desire for separation from neighbors led to a return of price increases.
The Elephant in the Room
The Covid pandemic surprised many of us by leading to rapid price increases driven by low inventory and historically low interest rates. Low inventory is still here but interest rates are rising rapidly:
If trends continue, at some point rising interest rates will reduce affordability enough to reduce sales activity and prices. Here’s hoping for a soft landing.
Brownie points to anyone who was not on the Yolo County Association of Realtors call last week who can tell where this is:
The FMHPI is your friend. The index reports monthly change in house prices for national, state, and metropolitan statistical areas (MSAs). The data series starts with January, 1975 and usually runs two to three months behind the current date. The data is available in Excel or text files with seasonal adjustments or non-seasonally adjusted.
As an appraiser, I use the FMHPI in several ways for current work:
Regional market trends. I use this data set if I want to show how house prices are trending in my home regions of Sacramento or Fairfield/Vallejo.
Market areas with little activity. I cover Stonyford, a small community on the eastern edge of the coastal mountains with very few sales. I trend surrounding MSAs to show regional activity and offer this as the best evidence available for market trends in Stonyford.
Market areas with significant non-conformity. I cover the Sacramento Delta area, a place with a mix of small towns and small acreage residential properties plus some high quality mansions. Market trends are often influenced by the mix of sales and frequently are not reliable so I use the Sacramento MSA instead.
Where the FMHPI really shines is with retrospective work. My local MLS has data going back to 1998 for my county. That’s great for the past 23 years but what if a client wants a date of value before then? In the past two years I have had requests for appraisals dated in the 1980s and early 1990s on multiple occasions. Each time I used the FMHPI to determine market trends and calculate time adjustments.
Normally I download the data into Excel and generate the chart I want, discussed below. However, you can use the pre-built chart and table tool. This is the default chart:
FMHPI default chart
You can add multiple states or MSAs for comparison by clicking the blue button:
FMHPI with Sacramento MSA
You can also adjust the time period on the chart by sliding the time frame below:
FMHPI Date Range Adjusted
Once you have the chart you want, you can print or download it as a PNG file to stick in your report or work file:
Print or download a PNG graphics file
This tool is versatile and includes a table view showing percentage change.
However, I normally download the data into my Excel work file and create my own graphs. The FMHPI MSAs Excel workbooks are two sheets with MSAs A-L on Sheet 1 and M-Z on Sheet 2. Column A is the Month with MSAs in columns in alphabetical order like this:
Month on the far left column, MSAs in alphabetical order
Here’s my simple process to deal with the way dates are formatted.
Click the link
Download the Seasonally Adjusted MSAs Index:
Click the link
Open the file and copy the Month Column into your Excel work file plus the columns of data for any MSAs you want to analyze.
Leave a column to the immediate left of the MSAs you want to work with to fill in Excel-readable dates. I usually label it “Date Sold.”
Then fill in the Date Sold column matching the dates in the FMHPI Month Column. 1975M01 is 1/1/75, 1975M02 is 2/1/75, etc. Fortunately, once you have the pattern, you can use Excel to autofill to the bottom:
Copy the columns, leaving space for Date Sold, autofill date sold
You can now use this data in Excel to make line graphs or scatter graphs. If you don’t need all 46 years of data in your chart, graph only what you need. Here’s an example of how I would prepare the Sacramento MSA data for the past two years and past 10 years plus the graphs:
Data copied from original columns for ease of creating graphs
And here are the resulting graphs:
Line Graph Example
I hope you can see the value of this data. Let me know in the comments if you have questions or are already using this data.
Six months after the Covid-19 stay-at-home order hit Yolo County, what’s happened to residential real estate in local markets?
Sales activity in Davis was low at the start of 2020 before the pandemic hit and continued into the spring with a massive drop in May. As shown below, Davis is way behind in sales compared to last year but we may make up ground in the fall.
In contrast, Woodland started 2020 with strong year-over-year sales activity, putting on the brakes in April and May. Some of the missing activity shifted into the summer but Woodland is still behind last year’s numbers.
While demand (sales) fell over the past six months, supply fell even further in both Davis and Woodland. We have seen an increase this summer in homes listed in Davis, hopefully a sign of the traditional summer market spilling into the fall.
Woodland saw a sharp drop in new listings in April and May and is continuing to track lower.
Net effect on both Davis and Woodland is a supply imbalance leading to rising prices. Davis is showing year-over-year increases in five of the past six months.
Woodland prices are rising too as shown on the scatter graph of all sales below.
Below is a quick summary of both markets:
The standout statistic above is the incredibly low inventory in Woodland.
Winters is a much smaller market than Davis or Woodland. As the graph below shows, sales are increasing at present. Also note the lack of sales in April and May in Winters, similar to other Yolo County markets.
Takeaways for Davis and Woodland
Sales volume is down
Inventory has declined more leading to a supply imbalance
Prices are increasing
Pay Attention To
Interest rates. The historically low rates are jet fuel for the residential market. When rates go up, pay attention
The local economy. We’re still in a recession with massive job losses and a large percentage of mortgage forbearances. So far, impacts to local housing have been minimal but that may change in a hurry
Update: Well, this helps but doesn’t completely solve the problem. Tab characters still stay in the fields not converted to numbers or dates. If this doesn’t work, I’ve added a couple of steps that will work involving using a robust text editor, Notepad++.
A recent Rappatoni MLS update broke data export. It appears that a hidden tab character is placed between fields as a delimiter, changing numeric fields into character fields. This causes issues when you try to use a workbook like Don Machholz’s 1004MC because the 1004MC workbook relies on the data types to be correct. The calculator chokes whenever it finds text in a numeric field like list price (or sale price, or DOM, etc.). This only affects Rappatoni system MLSes. Metrolist was not affected (yet) because they run their own code and do not appear to have run the update that broke stuff.
Here’s a quick way to know if your MLS has been affected. Take a look at the Selling Price column. If it lines up on the left, your MLS has the issue. If it lines up on the right, you’re good to go.
Here’s an example with the problem:
Here’s how it should look:
Here’s an easy workaround for the latest version of Excel.
Download your data out of MLS and save it to a csv file.
Open up an Excel workbook.
Click on the cell you want the downloaded data to appear in.
Click on the Data Tab and select From Text/CSV
Select your csv file containing the data you need and hit the Import button
Excel will open a data import wizard. This should show your data with the correct data formats and aligned correctly (numbers aligned to the right, text to the left, dates looking like dates). Click the Transform Data button and you should be good to go.
Older versions may require more work to find the data import wizard. This link shows the process using a slightly older version of Excel. Brings me back to my days as an EDI analyst….
I’m learning from others that this fix doesn’t work universally. If you see this in your Excel file, you still have problems.
Here are additional steps that you can do to fix it. The simple way is to place your cursor in the edit bar to the immediate left of the data you want to keep, hit <Backspace>, then enter. This deletes the hidden Tab character but needs to be repeated throughout the file. Another option is to simply not copy text fields into the 1004MC since they are not required to run the calculator.
If you’re interested in a better solution, download a robust text editor like Notepad++ (link). Use Notepad++ to open the csv file.
Go to View, Show Symbol, Show All Characters
Notepad++ will then show the Tab characters
Select one of the now visible tab characters and type ctl + c to copy the Tab character. In Notepad++, select Search then Replace
Click on the Find what: box and paste the Tab you selected previously. Leave the Replace with: box blank. Click on the Replace All button and then save changes.
Now you should be good to go.
(There are many ways to skin a cat. Another way would be to import your files into an Access database, delete the tabs, then output as an Excel file. If you know how to do this, you don’t need my instructions)
Good luck and contact me directly at email@example.com with questions. Hopefully Rappatoni fixes this soon.
As I type this, the 100,000th person in the US has died from the novel coronavirus 2019. The country has shut down to bend the curve. Shelter in place started in Yolo County on March 19, forcing most people to stay home. Unemployment exploded nationwide, going from 3% to nearly 20% in a month while mortgage forbearance levels jumped to 2008 levels. How has the economic crash affected residential real estate in Davis and Woodland?
Shelter in place stopped in-person interior inspections for buyers and real estate agents while the stock market crash and jump in unemployment shook consumer confidence. However, interest rates dropped into the low 3s, increasing affordability.
The graph above shows all single family residences sold in Davis by month for 2019 and 2020. Year-over-year change in January, February, and March was somewhat negative, indicative of a slowing market. April 2020 was lower still and probably represents sales that went into contract before or at the beginning of the shut down. May sales are probably the first period to reflect the post-shut down period. I was so surprised at how few sales in May to date that I ran the search multiple times to make sure I wasn’t making a mistake….
The Davis residential market ground to a halt. Current listing volume is still low but homes in contract is starting to recover (35 in contract in May 2020 to date compared to 41 in 2019). Prices have held up surprisingly well on a year-over-year, price per square foot basis as shown below.
After a period of decline in the fall, prices shifted to stable to slightly increasing. Early days and less reliable than typical because of the sales volume decline.
Woodland, in contrast, was poised for a strong 2020 before the pandemic. Sales volume was up 38% in January and 25% in February from 2019. March sales this year slowed to the 2019 rate and declined steeply in April and May to date.
Sales volume declined sooner in Woodland but not as steeply as Davis. Once again, prices in Woodland have been relatively stable overall. Homes currently in contract are low and point to continued sales volume decline in at least the short run.
We’ve seen a significant slowdown in activity that has yet to affect prices significantly. Inventory is slightly higher but not yet affecting prices. Historically low interest rates have certainly helped prop up the market. Buyers and agents have adjusted their protocols to stay healthy while shopping for homes.
I’m concerned at the trickle of sales in Davis. Davis is a really hard place to value properties because of differences in location and the high degree of seasonality from the university. Reduce sales volume significantly and sales comparison is going to be difficult. Here’s hoping my Davis Realtor friends have a busy quarter…..
It was my pleasure to speak at the Sacramento chapter of the Real Estate Appraisers Association last night at the Story of Value class with my good friend Ryan Lundquist. I discussed ways to explain markets in residential real estate appraisals and focused on using graphs and was surprised to see that maybe half of the crowd didn’t include graphs in their reports. This post is the first to offer advice and instructions on how to create meaningful graphs for residential appraisers.
Four appraisers out of 50 in the room reported using histograms. The histogram is a great tool for analyzing residential real estate markets that all appraisers should use.
What is a histogram?
For our needs, a histogram is a graph that shows the distribution of one continuous variable. The histogram splits the variable into equal-sized bins and counts the number of occurrences. It works well for important residential real estate variables like gross living area, lot size, age, and sale price.
Bin size is key to creating a useful histogram. Bins too wide loses meaning as your data is clumped together. Bins too narrow spreads the histogram out too much.
The graph above shows the sales of homes in a market area with homes of certain sizes. There is one sale less than 1000 sf and one more than 3500 sf. The most frequent size of home sold recently is around 2000 sf with the bulk of the homes in the 1400 sf to 2000 sf range.
Every report prepared for a lender asks the question “Is the subject conforming?” At a glance, any home sold in this neighborhood with between 1300 sf and 2600 sf is reasonably conforming in size. There are no sales in the 4000 sf to 5000 sf range so any homes in the neighborhood of that size are likely non-conforming. The two extreme sales, at 800 sf and 5000 sf, are unusual and likely non-conforming.
This next histogram examines the frequency of sale price in the market area. The most frequent sale price is in the $240,000 to $280,000 range with $360,000 to $400,000 the second most frequent range. A home in contract at $375,000 is fairly typical. A contract price of $700,000 is very unusual and is indicative of a non-conforming home.
The first two graphs were generated using ggplot2 in RStudio. Here’s an example from Excel 365 showing the year built for homes of sales in a market:
Most homes sold in this market area (Placerville, CA small residential acreage) were built in 1970s and 1980s. A couple of homes were built in the 1800s and there are a couple of newly built homes.
The lender forms used by appraisers ask for similar information in a table format:
Which describes the market better, the two histograms or the table?
Make A Histogram in Excel
Here’s how to use the latest version of Excel to make a histogram. This page has instructions for the latest version and older versions.
Start with your data in an Excel workbook with the top row field names and rows below sales data.
Starting with the field name, select the data to generate the histogram (ctl + shift + down arrow will select all consecutive data down)
Press F11 to insert a graph. Then chose Change Chart Type
Select Histogram then press Ok
You’ve made your first histogram!
However, it’s really ugly. Standard formatting for histograms is to have no space between the bins (columns). To fix that, double left click on one of the bins to activate the Data Series editor. Select the bars to active Series Option
Change the Gap Width to 0%. Notice how the columns come together. If you like having gaps between the columns, set the Gap Width to 6%.
To change the bin width, double left click on the x-axis labels (GLA in this case). Using the Format Axis Axis options, select the Bin Width control and type in what you want. Play with it until you’re happy with the shape of your histogram.
Excel defaulted to a bin width of 370 sf. Below is what the histogram looks like with bin width equal to 100 sf:
Here’s bin width equal to 500:
Here’s bin width equal to 200:
Which one appears most useful to you?
I use histograms to understand some aspect of a market. How big are the homes? When were the homes built? How big are the lots in the neighborhood? What do homes sell for in the market area?
Then consider where the subject fits in the market. Is it bigger than typical? If so, you have support for concluding market value is higher than typical. Is it smaller? Well, now you can show a reason why the price is lower.
Let’s consider the histogram above. The subject is one of the larger homes in the neighborhood but still relatively common in size. I would expect, without knowing anything else, that the subject’s market value is on the higher side for the neighborhood but with a reasonable number of homes larger than the subject. Take a look at the graph below.
What if the subject was one of the largest homes in the neighborhood? The subject’s market value is likely on the upper end of the neighborhood range. Also, there are fewer directly competitive sales, implying market value may be less reliable in this market area than for a smaller home. Now let’s look at an extreme case.
I pity the appraiser asked to appraise a 6500 sf house in this market. However, you do have sales either smaller or larger. Here’s the time to really open your eyes to what is a competitive sale. Throw this graph in your report and your client will immediately see your data difficulty.
After you arrive at market value and as part of your reconciliation, consider using a histogram to support your market value.
“The subject is newer than typical, above average quality custom home on a larger than typical lot. As shown above, the subject’s market value is on the higher side for the greater market area, as expected based on its superior characteristics.”
I hope you agree that histograms can be a powerful tool for appraisers.
Ways to use histograms:
Exploratory analysis to understand characteristics of a market area
Assist in determining reasonable search criteria for sales comparison
Visual representation of the subject’s position in a market area
Support for market value conclusions
I learned about histograms from George Dell. Thanks George. Get smart by taking his Stats, Graphs, and Data Science classes or at the very least, sign up for his blog. More info on George’s website.
Postscript: I am working towards moving away from Excel to using R, the data analysis package. I’ll link to the R code used for the two graphs as a separate post/update soon.
Two recent posts from my friend Jamie Owen at the Cleveland Appraisal Blog plus a planned realtor office visit inspired me to write this. Jamie did a great job blowing up the myth that comparable sales need to be within one mile of the subject in this post. He also tackled geographical competency, or the need to have boots on the ground knowledge about a market in order to credibly value properties in a second post.
Both posts touch on the subject of what is a comparable sale and why should anyone in real estate, or even the general public, care? The quick answer is that “comps” are the basis for how we, both those in the real estate industry and the man on the street, value residential real estate.
Per the Dictionary of Real Estate Appraisal, 3rd Edition, comparables are:
“…similar property sales, rentals, or operating expenses used for comparison in the valuation process; also called comps.“
Comps are used in the Sales Comparison Approach to Value, especially in residential real estate appraisal. All of us, appraisers, real estate agents, and folks considering buying a home, use the theory of substitution to determine the value of a home. What would the typical buyer shopping in that neighborhood buy instead of the subject?
A comparable sale is a sale of a home that the typical buyer of the subject would buy instead of the subject.
Subconsciously, everyone who owns a home compares it to homes in their neighborhood. We learn about a recent sale on our block and place a price on ours based on whether we think it’s better than ours, relatively similar, or inferior. The formal version of this is the sales comparison approach used by appraisers.
We appraisers find the most similar sales, adjust the comparables for differences from the subject, leaving each adjusted comparable sale an indicator of value for the subject. The vast majority of single family residential appraisals in the US rely upon this methodology.
In the context of the sales comparison approach to value, the key is to identify the comps for the subject.
The easiest way to get the value of a single family residence wrong is to get the comps wrong!
Residential real estate, such as a house, a condominium, a home on a small acre lot outside of town, etc., have characteristics (“dimensions”) that serve as descriptions of a specific sale for a specific property. The more similarities between a sale and the subject under consideration, the better a comp. We can go into a deep dive, like George does in his classes; instead, I want to talk about what I do specifically for simple single family residential work in conforming neighborhoods.
Some examples of dimensions and characteristics important to valuing homes include transaction terms (financing, credits, etc.), motivations, location, views, quality, design, condition/age, floor area, and amenities.
Some dimensions/characteristics are more important than others and can vary dramatically in importance depending upon the location. For example, pools are valuable in the Sacramento region but have less value in the Pacific Northwest where the weather is cooler. Basements are common in the Midwest and East Coast but not so here. In the Whisper Creek Subdivision in Arbuckle, CA, a tract of large homes on half acre lots, RV parking is a significant factor unlike other nearby markets. This is why the geographical competency that Jamie discusses is so important. Appraisers with geographical competency understand what characteristics define a true comparable and get the subject’s value right.
Time usually matters except when it doesn’t. If a market is rapidly changing, using the most recent sales can reduce the impact of market change. When a market is relatively stable, time is less important and so using older comparables is reasonable. I downplay time frequently because time is usually the easiest and most reliable adjustment to make.
For a typical tract home in my area, the most important factors are motivations for the purchase or sale, time, location/proximity, and size/floor area. I start with a map search using my neighborhood boundaries and go back 12 months prior to the date of value for closed sales. I exclude from consideration REO sales, short sales, and other transactions where motivations likely had an impact on sale price.
I search for homes a little smaller than the subject because most buyers can make do with a slightly smaller home. Because the typical buyer can accept a larger home than the subject, I set the upper boundary on my floor area range wider than the lower bound. For example, if the subject has 2300 sf of living space, I will search for comparables with 2000 sf to 2800 sf of living space (300 sf smaller to 500 sf larger).
After I set my criteria in the MLS search, I run the search and review the results.
I mentally draw a box around the subject’s important characteristics so I can place it in the competitive market. This is known as bracketing. Reasonably, would the typical buyer consider the sales found suitable substitutes for the subject? Are the sales similar in quality and design? Are there differences in lot size or age? Do I have larger and smaller homes? Do I have homes in similar condition, or inferior and superior? I try to account for every significant characteristic of the subject so I can show, by comparison, the value of the subject by using these comparables.
If I’m comfortable with the sales found, I can start my adjustments analysis. If not, I revise my search criteria and run the search again until I am happy that the sales found reasonably describe the subject.
Once I have my initial candidate comparable sales identified, I dig in and look for most representative comparables of the subject and decide on which sales to research further (view the exterior, contact agents involved in the transaction, etc.). I review outliers, sales outside the normal range, and try to determine why the sales deviate from the norm. I either adjust for the issue or remove the outlier from consideration. The remaining comps, after adjustment, are my indicators of value for the subject.
Comps are usually easy to find in conforming neighborhoods as long as the subject is similar to the rest of the neighborhood. When the subject is unusual, or when there are few sales available and they are all different (“non-conforming”), comparable selection is difficult. The appraisal becomes complex and beyond the scope of this article. I do have tips in my article about appraising complex residential properties.
How do you search for comparables? What are some tips for a real estate agent or new appraiser you can share?
Today I was asked to comment on the issue of reporting private sales to my local multiple listing service (MLS) by a friend who works for Metrolist, the MLS for the Sacramento region. Today, Metrolist and most other local MLS systems do not allow for sales not sold through the listing service to be included in the sale databases maintained by these organizations. There’s a push within the residential real estate community to include this data. Here’s my response for why, from an appraiser’s point of view, I think it’s a bad idea:
As appraisers, data is our lives. We want available as much data as possible to help us value properties. By rule, we’re required to consider all competitive sales when valuing a property. The vast majority of assignments are for some version of market value. Here’s FNMA’s definition of market value:
“Market value is the most probable price that a property should bring in a competitive and open market under all conditions requisite to a fair sale, the buyer and seller, each acting prudently, knowledgeably and assuming the price is not affected by undue stimulus. Implicit in this definition is the consummation of a sale as of a specified date and the passing of title from seller to buyer under conditions whereby:
buyer and seller are typically motivated;
both parties are well informed or well advised, and each acting in what he or she considers his/her own best interest;
a reasonable time is allowed for exposure in the open market;
payment is made in terms of cash in U.S. dollars or in terms of financial arrangements comparable thereto; and
the price represents the normal consideration for the property sold unaffected by special or creative financing or sales concessions granted by anyone associated with the sale.” (FNMA Selling Guide, Section B4-1.1-01)
This definition requires us appraisers to confirm some information regarding every sale used as a comparable in our reports. We must analyze each comparable we use in the sales comparison approach, the primary method for determining the market value of single family residential homes in the US. We must understand that both buyers and sellers do not have unusual motivations and that the comparable sale was properly exposed to the market so that all interested parties could bid on the comparable sale. The most widely used marketplaces in most of California are the various multiple listing services. Exposure on the local multiple listing service gives the widest viewing to potential buyers and allows for market mechanisms to arrive at the market value for any given home. Without this exposure, there is significant uncertainty whether the agreed-to price is market value or something else.
In addition to the value of having a central marketplace with mechanisms to arrive at a market value, the multiple listing services serve as a central repository of data. Most of the time, we can look at one central database and see all relevant property characteristics and data. Additionally, we have record of listing agents and buyer representatives who we are required to contact as part of due diligence. Some of the markets we cover have a significant percentage of sales not reported to the local multiple listing service. In general, we do not use these transactions in our appraisals because of the uncertainty of whether they sold at market value or not. For example, the for sale by owner that puts a sign up on his lawn may attract offers from people driving by but most likely he missed all potential buyers and may have sold his home too low. The “pocket listing” of one agent only marketed to agents in his office misses a huge pool of potential buyers. As appraisers, we can’t rely on these sales as primary data-we just don’t know if the sale price was market-derived.
I have worked extensively in Solano County over the past 15+ years. BAREIS, the multiple listing service for this area, has accepted sales data not sold through the MLS and reported it as “Sold Off MLS.” In the handful of years since this data has been offered, I have used it once in approximately 300 appraisals in Solano County. The sale used was included as secondary evidence for a very difficult assignment because this sale was not clearly a market value transaction. In more than 95% of assignments, I do not bother to check the “Sold Off MLS” sales. Even when similar sales are very difficult to find, the “Sold Off MLS” sales are not very helpful.
Does your local MLS system allow for agents to enter non-MLS sales into the database? Is this good or bad in your opinion? Why or why not?