People often berate Statistics Canada when it comes to producing data on education in Canada. And not entirely without reason: there are some statistics that Canadians seem to be especially bad at producing. But it’s also worth noting that there are other kinds of data that Statscan is extraordinarily good at capturing – data that researchers in other countries would kill to have.
When it comes to research, there are broadly two types of data. The first is factual, aggregate data, which usually comes from administrative sources and is usually analyzed by means of a time series. We use this approach to measure things like aggregate enrolments, tuition fees, number of professors, university and college finances, etc. Call this Type I data.
Statistics Canada’s record in obtaining Type I data is disappointing. We seem to have a ludicrously difficult time in this country collecting data on part-time academics, college students, or the number of new students entering into higher education in a given year. Consistent ancillary fee data is also a challenge. There are a number of reasons why this is so, not all of which are Statistics Canada’s fault. But at the end of the day, the Type I data products Statistics Canada puts out are pretty disappointing.
But Type II data is a totally different story. Type II is based on surveys, not administrative data, and at its best is longitudinal. This is the stuff that helps researchers draw empirical conclusions about the relationship between inputs and outputs. When it comes to Type II data, Statscan is the envy of the world. The data in the Access and Support to Education and Training Survey does a good job of covering key topics in education across the life cycle, even if the public use file is a bit on the irritatingly useless side. And the Youth in Transition Survey, a magnificent 12-year longitudinal effort linked to the PISA test, is quite simply the best data source for the transition from high school to adulthood anywhere in the world.
So is Statscan doing a good job or a bad job with educational statistics? Well, if what you’re worried about is the ability to compare Canada to other OECD countries every year in Education at a Glance, then it’s doing a bad job, because that’s all Type I data. But if you’re interested in understanding the dynamics of access and outcomes in education, then it’s doing an exceptionally good job.
One small problem though: Statscan’s core funding is devoted entirely to Type I data; the funding for Type II comes entirely from HRSDC, whose commitment to supporting these surveys is best described as “soft.”
Cause for concern.