Affordability Maps: How to solve a problem

There’s a housing crisis, if you haven’t heard. It’s hard to miss with all of the news publications on the topic and outrage from people on social media who are, rightfully, voicing their concerns that Canadian cities are simply becoming unaffordable for the average person. But how do you solve that problem? ‘Build more houses!’, some might say, or perhaps ‘Disincentivize foreign investment!’, among a myriad other potential solutions. All of these proposed solutions have their own arguments for and against, but they miss a very obvious point: We don’t know how to measure which solution (or mixture of solutions) works best. That’s because we don’t actually have a signal for how unaffordable things are, not in a way that is meaningful to the average person.

While we have figures such as the average rent in a given city, and we have seen that number increase, that increase doesn’t accurately capture the strain that the diverse group of people that make up the residents of that city are feeling. For instance, a single mother caring for 2 children might find that living costs have doubled relative to her income while the average rent for the city only went up by 10%. On the other hand, someone that belongs to a family of 4 working adults in high-paying jobs may find that their relative living costs have halved because their capital gains have outpaced the 10% rent increase. We have to characterize the problem in a way that reflects the experiences of actual residents so that we can outline the problem and propose solutions. Then we can measure the impact of those solutions on the relevant populations and relevant regions, rather than trying blanket solutions that may work in some instances and not in others.

To quantify the problem of affordability in a way that is constructive for proposing solutions, we used StatsCan census data to create affordability maps for various family types. These maps are coloured according to how much of a given biweekly paycheque the average person in the North East Avalon spends on costs related to housing (mortgage, rent, maintenance costs, etc.). We can build different maps for different ‘family types’ in order to visualize trends specific to that economic group. As an example, the map below is for renting one-parent families (see more maps and detailed post here). The relative affordability in given regions, known as dissemination areas, gives the city and province the ability to target resources and policies that help this demographic to the areas where they’re most needed. We plan to make this map interactive in the near future by adding it to our upcoming StatsCan maps series!

By developing and promoting tools such as these affordability maps we hope to foster a culture where policies, like streets, are for people.