Category Archives: Teaching

Add Histograms to Your Appraisal Tool Kit

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.

Gross Living Area Histogram

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.

Sale Price Histogram

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:

Year Built Histogram

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:

Table or Histogram, which is better?

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!

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%.

First Not Ugly Histogram

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.

Default Bin Width

Excel defaulted to a bin width of 370 sf. Below is what the histogram looks like with bin width equal to 100 sf:

100 sf Bin Width

Here’s bin width equal to 500:

500 sf Bin Width

Here’s bin width equal to 200:

200 sf Bin Width

Which one appears most useful to you?

Context

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.

The Subject’s Position in a Market Area

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.

The Subject is one of the bigger homes….

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.

Charge big bucks if you get this subject

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.

Support for your market value conclusion

“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.

Teaching in Washington State in March

Time is your friend

Edit: Just found out the Washington class is sold out. Thanks Dave.

I can now confirm that I’m going to teach two classes in Marysville, Washington on Friday, March 30. The first is a two hour Introduction to Excel for Appraisers, a brief review of Excel basics (Excel structure, navigation, simple commands). The second is my four hour Time Adjustments for Residential Appraisers class. This class focuses on sale price and PSF trendline analysis for determining market direction and comparable time adjustments. We also discuss trending for neighborhood markets plus what to do with few sales/scarce data. Both classes are through Dave Towne’s Appraiser Education Service.

If you’re in Northern California, I’m teaching the Time Adjustments for Appraisers class for REAA North Bay on May 17 and June 18 for REAA East Bay.

Time is Your Friend When Valuing Homes

Time is your friend

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 time until 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

Sacramento MSA
Date Freddie Mac Index Value
Dec-05 215.10
Jul-14 152.57
Difference 29%

Time Adjustment

Sale Price 363,000
Time Adjustment -105,500
Net 257,500

What is the most time between a date of value and a date of sale for a comparable in one of your valuations?