List price on a property
When it’s time to set the list price on a property, the roles are clear. Real estate professionals provide detailed data and selling strategies relevant to the specific property and market. Property owners decide on the list price. One Canadian researcher wondered what trade-off between time-on-the-market and sale price is reflected in the choice of list price.
“It is important to identify which segment of buyers you want to attract,” said Dr. Paul Anglin, currently an Associate Professor of Real Estate and Housing in the Department of Marketing and Consumer Studies in the University of Guelph’s newly-created College of Management and Economics.
“Do you set the list price high and wait for someone to come along, or does the high list price scare away buyers? There is a trade off between time and money and several parts of my research are trying to come to grips with high selling price versus quick selling time. Sometimes you just get lucky and sell for a high price in 2 or 3 days. How much is luck and how much is the listing price strategy? Distinguishing luck from good choices requires careful analysis of the data.”
When Anglin was a member of the University of Windsor’s Economics Department, he undertook research based on 3 years (1997 to early 2000) of listing information provided by the Windsor Real Estate Board. Through the Board’s cooperation, data for more than 20,000 houses, including those that did not sell, was available for statistical analysis. The resulting study, entitled “House Prices and Time-till-sale in Windsor,” attempted to quantify the trade-off between time on the market and sale price as a reflection of selected list price.
“The key step in our analysis was that we tried to compare to a benchmark,” said Anglin, who used a three-bedroom/two-bathroom bungalow as the standard for comparison. “An increase in the list price has an effect relative to a benchmark.”
- Analysis revealed that, on average over that 3-year period:Smaller houses sold faster while increased time-til-sale (TTS) was the case for properties with 5 or more bedrooms.
- Bungalows and side-splits sold at the same pace, but condominiums, ranch-style and “rental” properties took more time.
- TTS differed significantly by location while properties outside the City of Windsor consistently had longer TTS.
- Descriptive remarks on the listing form had the following effects: The words “beautiful” or “gorgeous” reduced TTS by 15 percent and “beautiful” houses sold for more. “Landscaping” reduced TTS by 20 percent and “move-in” condition did so by 12 percent. However, “must see” and “vacant” houses apparently had no statistically significant effect.
- Houses identified as “Starter” homes sold in 9 percent less time, however, “Handyman Specials” sold approximately 50 percent faster. “Rental” properties were on the market 60 percent longer. Seller intent described as “motivated” or “must sell” were associated with a 30 percent increase in the average TTS while “moving” had no statistically significant effect.
Following the research statistic “Degree of Over Pricing” (DOP), which measures the difference between the list price chosen by the seller and the average list price for that type of house, the DOP of unsold houses was roughly 4.5 per cent higher than those which sold.
Anglin believes his work is also relevant to “hot” markets and large cities like Toronto and Vancouver. According to his research, “Roughly 40 percent of listings in average markets around the world do not sell.” The impression in a hot market is that all listings sell, but Anglin stresses that may not be true. Since the only way to be sure is to analyze other real estate board data, Anglin hopes to expand his research to a large centre like Toronto.
In an email follow-up to our interview, Anglin added: “I was looking at the website of the Calgary Real Estate Board and, even with the hot market that they have, the number of new listings is about 40 percent above the number of sales for the year to date. The data for the Edmonton Real Estate Board does not report new listings; thus, I cannot tell whether the data on the number of listings represents a lot of new listings that sell quickly or a few new listings that sell slowly and I cannot distinguish between the listings which sell and those which