If you analyze Statistics Canada data these days, you will come across many “X”s.
In the place of where numbers should be, X’s indicate that the data have been suppressed due to confidentiality or reliability issues. In other words, instead of having a neat table displaying, for example, mining supervisors in Newfoundland since 1999, you will have a few numbers and a whole bunch of cells with “X” filled in–especially after the mid-2000s. More often than not, you won’t have any numbers at all and the data table will be marked with the gloomy word “terminated.”
These Xs have become a big problem for policy makers in Canada. In 2010, StatsCan’s Chief Statistician Munir Sheikh resigned in protest over the Harper government’s decision to replace the mandatory long-form census with a much-abridged voluntary survey, the results of which would render much of the data unusable and leave many populations off the grid. Comprehensive, reliable survey data is becoming increasingly hard to come by, leaving less information to inform public policy and more data gaps.
Public support for StatsCan’s mandate has recently become clear– first with the tabling of Bill C-626, which proposes to reinstate the long-form census and expand the authority of the Chief Statistician, and secondly with the buzz in public discourse and over 6000 signatures Evidence for Democracy has received from concerned citizens petitioning for their MPs to support bringing back the long-form census. It’s a start, but, as data monkeys like me know, this is a small feat in the much larger bid to restore Canada’s data collection capacity.
I am a policy analyst at a small think tank in Toronto that researches economic and public policy issues. Because of funding and staff restrictions, my organization mainly relies on publicly available data from agencies like Statistics Canada, among others. There are many organizations out there like mine and many researchers, analysts, academics and general policy wonks who need access to good data on important areas of the economy and society.
My job, like those of thousands of researchers across the country, has become increasingly difficult in this era of cuts. Over the past two years, StatsCan has lost 18.5 percent of their staff and more than 7 percent of their core budget. As a result, StatsCan cannot update many surveys and relies increasingly on funding from other departments and custom orders.
What do these cuts mean for Canadians?
Well, we don’t really know—and that’s exactly the point.
From the perspective of many Canadians, the business of governing seems to be ticking along just fine. Schools are still running; electricity is still flowing. Yet, all of us can agree there are social problems that need solving. And without good data, we have no way of understanding them, much less tackling them.
Let’s take a deeper look at something the Harper Government has championed itself on: job growth.
Last year, the Conservative government’s job vacancy figures pointed to severe labour shortages across the country, using them as justification to expand the controversial temporary foreign worker program. Later, it was discovered that the data significantly overestimated job vacancy rates by relying on job postings from Kijiji and similar websites that often posted the same job more than once. The official job vacancy rate was later revised from 4 percent down to 1.5 percent–a drop of more than half.
It’s become clear that current tracking tools are so ineffective that StatsCan is now in the process of developing a new job vacancy survey. The current one doesn’t even collect data for many industries: if you want to know, for example, whether construction, IT or natural resource sectors are hiring, you’re out of luck.
This isn’t all that is missing. Given the cutbacks, economists and researchers are increasingly having to rely on two main sources of StatsCan’s labour data: the Labour Force Survey and the Survey of Employment, Payroll and Hours. While these provide detailed insights into hours worked, wages and unemployment, they are seriously limited. For the most part, they only provide provincial data, leaving regional differences to guesswork. Secondly, they collect little to no information on things like employment benefits or non-standard work.
We don’t know how many people have dental or extended medical insurance coverage from their workplace (data collected by the Workplace and Employee Survey, which was terminated in 2009). We don’t know how many people work an irregular schedule or how many are employed through a temporary help agency (data collected by the Survey of Labour and Income Dynamics, which was terminated in 2011). We no longer have longitudinal datasets, that track the same workers and their employment conditions over the long term, giving powerful insights into economic conditions.
These data gaps make it very concerning that the Ontario government and others are enacting policies on pensions and so-called “precarious” forms of employment. When there’s so little information, we cannot know how many people will be affected and in what areas of the economy.
Even more troubling is the blow to public accountability. StatsCan used to provide annualized data on government revenue and expenditures, including how much tax each province collected and how they spent it (education, healthcare, etc.). This robust dataset, started in 1989, provided transparency and easy comparability of government finances, and gave real insight as to where governments were falling short. It was cut in 2009. The hard-to-access data that remains are much more difficult to compare due to accounting differences.
These are but a few casualties resulting from the federal government’s cuts to Statistics Canada.
Expanding the capacity of Statistics Canada is not a very glamorous proposal, hence why not many politicians aren’t entertaining it. It’s evident, though, that Canadians need to be informed of the consequences of not having good data, and the serious problems this can cause. Without good data, money and time will continue to be wasted on uninformed policies that don’t solve problems for which they are intended.
Let’s hope that after the next election we will be talking about what the data says, and not asking whether we have any.