We all like to show off to the world that we can grasp basic mathematical concepts such as percentages. But oftentimes it’s far more relevant to look at the absolute dollar amounts since this better correlates to people’s purchasing power.
For example, it sounds great when I say I’ve doubled my income from one year to the next, until I tell you I make $2 an hour this year compared to $1 an hour last. And if living expenses also increase 100 per cent, a house that cost $500,000 now costs $1 million. It becomes obvious how my wage, when not expressed in a percentage, indicates my purchasing power has dropped precipitously.
Saanich council recently misused percentages to justify increasing development cost charges (DCC), fees collected from land developers to fund growth-related infrastructure. Fees that Mayor Fred Haynes acknowledges will affect people’s purchasing power because developers pass these costs onto consumers.
A memorandum to the municipality concluded that since the 2005 DCC rates were 1.3 per cent of the cost of a house in 2005, it’s reasonable that 2018 DCCs also be similar (1.6 per cent). Saanich News threw this math dagger back at council by pointing out this equated to a 180 per cent jump per average residential single family dwelling. Here are the actual numbers used: $13,498 (2018) minus $4,809 (2005) = $8,689 (180 per cent).
The municipality has allowed DCC to stagnate for the past decade despite annually increasing homeowners’ taxes on a representative house by 72 per cent ($2,266) since 2005. Thus, council believes this rate hike is a justifiable catch-up.
However, Saanich council’s focus on percentages, rather on the far more relevant actual infrastructure costs, is a mistake. Just because housing costs are high in Saanich, does not mean infrastructure costs are. Houses are much cheaper in Sooke and Duncan, for example. Do sewage and water systems cost so much more to build in Saanich than nearby? I would expect not.
Council must consider absolute costs of items when deciding on issues that affect constituents, because easily calculated percentages using cherry-picked inputs rarely provide the right information upon which to make informed decisions.