I’ve been very fortunate to take classes from George Dell over the years and occasionally volunteer as an assistant in his Stats, Graphs, and Data Sciences classes. His teachings have changed my approach to appraising moving me down the path from practitioner to professional. And appraising has become much more interesting to me as a result. George invited me to write about it on his blog which you can read here.
I recently completed my first stint as an appraisal expert witness in federal court for a personal bankruptcy. It was an interesting experience for me and was a lot less intimidating than I expected. My client was the lender for a second mortgage. The question was whether there was enough equity in the home for my client to receive any proceeds in the bankruptcy plan.
Here are some takeaways from my first experience:
Dress professionally. I wore a suit and tie. My lawyer was pleased to be able to call me again. The appraiser on the other side wore jeans with no tie.
Don’t use lending forms for non-lender work. The other appraiser used a 1004 URAR form plus included the 1004MC in his bankruptcy appraisal. Not a match for the assignment and possibly an issue for our licensing board.
That said, neither of the lawyers nor the judge cared that his report was on a lending form.
Chose your comps with care. Pay attention to neighborhood boundaries, school district boundaries, and flood zones. There are no good reasons to use a radius search today given the robust search tools available with most MLS systems. The subject was near a neighborhood boundary and the other appraiser crossed that boundary for two comparables. Both were in an inferior market and really were poor comparables.
Verify your comparables. One of the two comps from the opposing appraiser had $40,000 in foundation damage reported in the prior listing. The opposing appraiser missed this.
If you’re going to be an expert witness, have some game. Be able to run a trendline and be able to report market conditions. And be able to explain your appraisal model. I teach a class on this.
Our side lost despite the issues with the other side’s appraisal. Variance between my value and the other side’s value was about 10%-I was on the high side. To forgo payments, value had to be within 2% of my value. The judge thanked me for my professionalism and split the difference, eliminating the debt owed from the debtor’s bankruptcy plan.
However, I won. My side’s lawyer was very pleased with my work and plans to hire me again. He explained that in bankruptcies, it is very common for outcomes to favor the debtor.
I just completed an appraisal of a home for a refinance where the subject had sold eight months prior to date of value. I included the prior sale of the subject as Comp#4 and had two very recent, reasonably similar comparable sales that I included in the sales comparison grid. The subject is located in a suburban neighborhood built out in the 1960s-1970s on a ridge with some homes featuring city light views. Many recent sales feature remodeling or recent updating while others are relatively original.
In most suburban neighborhoods, using sale price per square foot (PSF) is the best way to track market trends because using PSF reduces the impact of changes in floor area in your sales comparable data. Generally speaking, the sale price model is subject to variations in floor area in this case and is not the best model. So, following my normal practice, I used the PSF linear regression model to determine time adjustments to comparables.
The PSF linear regression formula is:
Slope of the Trendline * Subject’s GLA = Daily Time Adjustment
PSF Linear Regression Model
So, in this case:
0.0992 * 1794 sf = $178/day
PSF Model Time Adjustments
Once I applied these time adjustments, my range of value was from $447,000 to $466,000 with an indicated value of $460,000. However, the most recent sale indicated $450,000 at most as did homes in contract competitive with the subject. Something wasn’t right.
So I tried a sale price linear regression model instead.
Sale Price Linear Regression Model:
Slope of the Trendline = Daily Time Adjustment
Sale Price Linear Regression Model
In this case, indicated daily time adjustment is $117/day or
Sale Price Model Time Adjustments
Indicated range of value for the subject ranged from $443,000 to $451,000, in line with the most recent sale and competitive homes in contract.
In this case, the Sale Price Linear Regression Model explained my data better than the PSF model.
I’ll have posts explaining more about time and real estate in the near future and will be teaching a class this July in Sacramento. Or you can learn straight from the national expert, George Dell. Sign up for his website and classes here. Thanks George for sharing with the rest of us.
Why do you think the linear model worked better in this case?
Time is your friend when valuing homes, especially when analyzing unusual properties. Sometimes when appraising a property, you find six model match sales within three months of date of value in a very narrow range, the value of the subject is obvious, and you’re done. Next please.
Other times, the subject is located on a busy street, is larger than any sale in town in the past 12 months, and has a moat. How do you deal with this nightmare? This is when time is your friend.
Expand your search parameters back in timeuntil you find a competitive sale that brackets or equals the subject’s unusual feature. That sale from three years ago that was bigger than the subject is a comparable you can use to value it today. Or better yet, use the prior sale of the subject from five years ago so you have a sense of the value impact of that moat. Sometimes the best comp is the prior sale of the subject.
If you have time adjustments in your tool box, you’ll have access to a wider range of comparables than someone who doesn’t.
I’m developing a time adjustments class for REAA Sacramento that I plan to teach in July. I’ll talk about time adjustments more on this blog but will leave you with a couple of ways to determine time adjustments, especially when you want to bring forward in time a dated sale to use as a comparable.
Gary Christensen has a video here that discusses how to do a linear time adjustment in Excel. This works well when you have a set of comparable sales that you can analyze and the market has been relatively consistent. I’ll discuss this in detail in the near future.
Another simple way that works well for comparables from 2+ years ago is to look at the percent change in average (median/mean) sale price or price per square foot for the subject’s market area compared to the date of value. That percent difference-that’s your time adjustment. Apply the percentage to the comparable’s sale price and your old sale is ready to use as a comp. Most MLS systems have market analysis tools that will let you look up an average price in the past. In the worst case, the Freddie Mac House Price Index on the MSA level can help. Or you can use pivot tables to track changes in market areas (more to come soon about pivot tables).
I recently appraised a home in a small project where the most recent sale occurred nine years prior to date of value. I used the Freddie Mac House Price Index to determine a 29% negative time adjustment for this sale, subtracted the dollar amount, and the dated sale was ready for comparison.
Freddie Mac Home Price Index Calculation
Freddie Mac Index Value
What is the most time between a date of value and a date of sale for a comparable in one of your valuations?
I regularly appraise in Dixon, California, a city of approximately 20,000 located in Northeast Solano County. Dixon is an interesting market because it is on the outer fringes of the San Francisco Bay Area but crosses over into the Sacramento region. Prices fell through the floor during the downturn, hitting bottom in late 2011, but have increased significantly since. The past several months trends have been hidden somewhat by seasonality and a lump of somewhat below average homes selling in the winter. Here’s what I saw this week:
Sale Price Trendline for all homes sold in Dixon, CA since 1/1/16
With a little more data to work with, looks like Dixon is increasing. With about two weeks of inventory at present, expect more increases in the short term.
Taking inspiration from Ryan Lundquist at the Sacramento Appraisal Blog I’ve started this blog to have a conversation about residential real estate in the markets I cover, primarily Yolo, Solano, and Colusa Counties in Northern California. Additionally, I will discuss general topics of interest to appraisers and other real estate professionals here.