geeky

Wealth vs income

Wealth and income are not the same thing. And it matters. Especially in BC.

Nathan Lauster Jens von Bergmann

5 minute read

(Joint with Nathan Lauster and cross-posted at HomeFreeSociology) Wealth and income are different things. Wealth is measured in terms of assets minus debts at any given point in time. It can accumulate or deplete over a lifetime and across generations. By contrast, income represents some variation of how much money one makes over a given time period (usually a year). Most people get this on some level. But since both income and wealth deal with people and their money, the terms are also often used interchangeably.

Property tax snacks

A short post munching through some property tax musings.

Jens von Bergmann Nathan Lauster

5 minute read

(Joint with Nathan Lauster and cross-posted at HomeFreeSociology) Property Tax Snacks Residential Property Taxes have been rising in Vancouver. As always, we’re seeing a lot of sturm and drang about the rise. But we think it’s ultimately a good thing. Why? Here’s three perspectives. From a fiscal perspective, property taxes pool our resources to enable our government to pursue projects and provide for the common good. They’re a big component of how we take care of each other and set priorities.

Elections fun

Playing with Canadian 2019 federal elections data.

Jens von Bergmann

4 minute read

Canada is a large country, with some reasonably densely populated regions, and large areas that are sparsely populated. That makes it hard to map things. CensusMapper, our project to flexibly map Canadian census data, struggles with that. The choropleth maps can be quite misleading. The same problem comes up when mapping Canadian election data. This map makes it virtually impossible to get a good reading of the distribution of votes. There are a couple of ways around this.

Spatial autocorrelation & co

Common (and commonly ignored) problems in spatial analysis.

Jens von Bergmann

12 minute read

These days I run a fair bit of spatial analysis. And there are three problems that regularly come up: Getting data on compatible geographies Ecological fallacy Spatial autocorrelation None of these problems is insurmountable, but they are all annoying to various degrees. Often I might ignore them on my first analysis run, but these problems need to be dealt with sooner or later. Which can eat up significant amounts of time.

Low income vs new dwellings

Does adding homes decrease the low income population? A look at the Canadian data.

Jens von Bergmann

13 minute read

Canada’s metropolitan areas are growing, which means we need to add housing. But adding housing often faces stiff oppositions. There are many reasons people don’t like to add housing, this post is trying to look at one particular one. That adding housing causes displacement of the low-income population. Adding new housing to a neighbourhood has two opposing effects. The gentrification effect starts from the observation that new housing is more expensive than old housing (all else being equal).