Accounting for Renter Density
When analyzing a rental property in a city that I’m not familiar with, one of the first questions I have is whether that area is densely populated with a lot of rentals relative to the broader vicinity. It is important to study and understand at least in general terms the density of rentals in the area that your rental property is situated in. One common question that comes to mind of property investors is if there was a technique to determine if a potential area has too many rentals.
A simple “surface level” solution as recommended by many is to simply drive around the neighbourhood and look for rental apartment complexes. Then compare the number of rental buildings relative to the surrounding neighbourhoods. Well, this could be the first step in conducting an initial analysis. How can you account for any rental units sitting in a condo apartment building or condo townhouse complex? That would be difficult and cannot merely be conducted by looking online to see how many rentals are available in the neighbourhood. Although, that is a step in the right direction and would further add more data to your analysis.
There are two further approaches that we consider in our density analysis. One method is to conduct a rental property count within a 1 km radius (urban area) and then compare it to a wider vicinity such as a 2km radius. We can then extrapolate a simple percentage indicating whether there are less or more rental properties in our 1km area compared to the broader region.
Another approach is to compare the number of rental properties within a 1km radius vs. a population count within this same area. You can then arrive at a figure and use it to compare against other regions. Statistics Canada conducts its survey down to a region that is as small as a block or two with a population of at least 500 people. They refer to this as the dissemination area. We are then able to understand if the specific area is a densely populated rental area or not.
Example: District population / Rental Properties = number of rentals per population (ex. 23 rental properties per 1,000 people = 2.3% renter density).
In urban areas, we can use a small spatial region of a few blocks or a 1km radius for instance, but suburban areas will have fewer data to generate a strong enough analysis. In less urban areas there will be less rental properties, and they will be dispersed more relative to an urban area that is densely populated with properties in general.
In addition to taking a technical approach, one also has to weigh in the fundamentals of the area by looking at the market forces affecting the rental density dynamics. Research to see if there will be a job influx within your target area of study. This will put more pressure on the availability of rental properties (supply). There may be a new company setting up an office in the area and looking to hire a large number of employees.
There are several indicators to look out for here. For instance, you can see if a company is either constructing or leasing a large number of commercial or industrial space. Is there a hiring spree by that company? Factors like these will put pressure on the surrounding housing market causing demand to go up.
Now, also consider the supply chain. Is there a future supply of rental housing coming? Rental inventory can be newly built or even taken away when an old apartment building gets demolished, and a new condo apartment is built in place of it for example. In short, we are merely analyzing the supply and demand of a particular market.
Within our Real Estate Top Performers group we will be sharing data visualizations that we have developed in house that provides more insight. You will be able to configure the data visualizations and share them with your clients or other real estate professionals to better understand the renter market in your area.