Valuing property for tax purposes often involves comparing the property you are valuing to similar properties that sold. A common issue that arises is that the comparable sales do not sell on the day you are looking for. For instance, the Assessment Act requires that property be valued at what it likely would have sold for on January 1, 2016 for the 2017 through 2022 tax years. It appears that the January 1, 2016 valuation date will also be used to calculate taxes for the 2023 tax year – see statement from MPAC here.
Similar properties will have sold some distance in time from that valuation day. It is well accepted that the value of property changes over time. As a result, it is a common appraisal strategy to adjust the sale price to what it likely would have been on January 1, 2016. This is known as a time adjustment study and is a form of time travel. There are a few ways to go about adjusting for time, and some are more reliable than others.
One of the most intuitive ways to determine a time adjustment factor is an analysis of “paired sales”.
Those are sales of the same property at different points in time. By looking at how the value of those properties over time changed a monthly average change in value can be calculated. A paired sales analysis was accepted by the Board in 622294 Ontario Limited v Municipal Property Assessment Corporation, Region 03, 2020 CanLII 48631 (ON ARB). The Board held that the paired sales study, consisting of 12 pairs of sales, had “its limitations, specifically the relatively small number of properties in the data set, and sale dates that fall well outside the 2015 and 2017 shoulder years.” But the Board ultimately accepted it as the best evidence of the change in value over time.
The number of properties that sold twice in the relevant time period is usually the limiting factor in creating a compelling paired sales study. A robust conclusion can only be drawn if there are enough sales to come to a reliable conclusion, and that data isn’t always available.
The physical and locational aspects of the paired sales must also be considered. If a property has significantly changed between the two sale dates, that must be accounted for prior to considering whether there should be an adjustment for time.
The geographic area of the study can also be a concern. If you have to canvas a wide area to get enough paired sales, the conclusion may be less compelling. This is because each area may change at its own rate. Some areas of a city may have significant infill, which can increase value faster than areas without that development pressure. The more localized a study is, the more compelling it will likely be.
Another approach is to look at the average sale price in an area through the Multiple Listing Service. MLS produces a House Price Index, which shows the average change over time in a city. The Board is occasionally presented with this type of time adjustment, as in Li v Municipal Property Assessment Corporation, Region 14, 2018 CanLII 14270 (ON ARB).
There are risks with using average values to create trends. As outlined in this time adjustment article, the distribution of each sample that you pull matters. If the sales in your starting period are skewed in a particular direction (that is, the mean and median differ) then the study will not be accurate unless the other data sets skew the exact same way.
The statistical nature of a time adjustment study makes it susceptible to errors such as that. As noted in the time adjustment article: “real estate markets are so imperfect that we cannot extricate such fine detail about time despite all that is read in the local newspaper about the rising average house prices in different markets.”
The MLS House Price Index is also too wide geographically to generally be of much assistance. As noted above, different communities are likely to rise at different rates.
The time adjustment article points out the risks of averages and suggests that a linear regression analysis may be a more reliable way to tease out the variable of time in a changing market. Regression is a statistical tool to determine how strongly a given variable impacts another variable. In appraisal, the variable we are interested in is the sale price and how factors such as size, age, and time influence the sale price.
Regression is a common appraisal technique. Like other time adjustment methods, it requires a large data set to be reliable and works best if all of the sales are in the same geographic area.
If you have the right data set, regression can be a powerful tool to see how various factors contribute to value. It is not foolproof. As noted here: “regression analysis is not a substitute for traditional appraisal practices as much as it is a complement to your experience and judgment. It will help you identify the most salient features for estimating the value for a given property, possibly including some you might not have thought were important but which turn out to be.”
Regression requires an expert with the right tools to conduct the analysis and also requires the right data.
Other Methods Possible
There may be other methods for adjusting for time such as a quality point analysis when using a direct comparison approach. The time adjustment article also provides details on this method. Importantly, when using a quality point analysis, all traditional adjustments such as physical and locational aspects must first be made before determining whether time should also be adjusted for.
Regardless of the method used, what is most critical is the quality of the data used and a logical analysis of that data. Otherwise, a time adjustment may result in a less reliable current value.
An adjudicative tribunal such as the Board is tasked with determining whether a particular time adjustment study is reliable in adjusting sale prices. In some cases, adjudicative tribunals refuse to used a time adjustment study because it is found to be unreliable. That was the case in Omega Developments Inc as represented by Avison Young Real Estate Alberta Inc. v The City of Edmonton, 2020 ABECARB 2101 (CanLII), a decision by the Edmonton Composite Assessment Review Board. In Alberta, municipalities are the assessors and the complainant in Omega Developments challenged the gross income multiplier used by the City for assessing its multi-residential high rise property on an income approach to value. Specifically, the Complainant argued that the time adjustment study the City relied upon in their analysis was based entirely on sales of low-rise multi-residential properties. The Board found that it was inappropriate to use a time trend from one property type (low-rises) and apply it to another (a downtown high-rise) due to a lack of data.
In Ontario, the Board similarly refuses to use time adjustment studies when evidence is presented that is not reliable. In Moorey v Municipal Property Assessment Corporation, Region 32, 2019 CanLII 96148 (ON ARB), the taxpayer challenged MPAC’s time adjustment study and the Board accepted those arguments, holding that based on “the physical distance from Terrace Bay and time distances of the sales from the valuation day… the resulting [time adjustment factors] are likely unreliable when determining the current value for this property.” The Board then relied on the actual sale values of the comparable properties in its analysis.
Finally, as noted in the time adjustment article, time adjustments may not be called for in every instance: “When we extract out 4-6 sales in order to complete a [Direct Comparison Approach], this author is not convinced that every house sale is subject to a Time Adjustment.” A careful appraiser will consider a proper method for time adjustment and determine whether a time adjustment is required under the circumstances.
Time adjustment is not an exact science and requires enough data to be compelling. But it is a common appraisal adjustment and relied on by the Assessment Review Board in most cases that compare properties.
NextGenLaw LLP works with experts in the valuation industry that can help us build the best case for you, including a proper time adjustment study. Contact us today to see how we can help lower your tax burden.