High-value homes frequently make the news in Vancouver, most recently in the wake of the extra school tax for homes valued over $3M. The province will have looked at the data before introducing the legislation, but none of this seems to have filtered out to the general public. So maybe there is a need to take a closer look using Census data. The census is a couple of years old now, and things have changed a bit since then.
(Cross-posted at HomeFreeSociology) Condominium apartments are fascinating! At their heart lies a relatively recent legal innovation enabling individual ownership of units in multi-unit developments. Since their arrival, condominium apartments have become places to build homes, sources of rental income, sites of speculative real estate investment, and experiments in private democratic government. They’re also in the middle of many on-going debates about housing and the future of cities in Canada and around the world.
Aaron Licker asked a good question about this very interesting dataset. twitter-verse where is the data that forms this amazing table from @CMHC_ca: cc @vb_jens @LausterNa @rwittstock pic.twitter.com/iRD65KQdz3 — Aaron Licker (@LGeospatial) November 28, 2018 Unfortunately it is not obvious where to get the raw data, but Keith Stewart at the Vancouver CMHC office was kind enough the share the dataset. So read on to follow my quick look at the data, or just download it if you want to tinker yourself.
Today the new CMHC Rental Market Survey data came out, which is a good opportunity to refine my musings on the rental vacancy rate and rent increases. I view this as the renter version of the relationship between months of inventory and changes in resale prices in the for sale market. CMHC surveys purpose-built (market) rental apartments every October and reports on a variety of metrics, including statistics about the total stock, median and average rents, vacancy rates, and fixed-sample average rent change among others.
When trying to understand the income makeup of regions in Canada we need to take the income distribution and simplify in a way that is accessible. This is no easy task. Simplification is an essential part of this, but we need to take care not to over-simplify but instead still retain the essential parts. How to measure income? To start we have to select an income measure. Partially this is constrained by data availability, but there are choices.