In March, forecasters expected 25,000 new jobs in Canada. Instead, we lost 2,200
Analysts use a combination of statistical models, academic theory and personal judgment to churn out numbers and predictions for their clients to consume.Kevin Yin is a contributing columnist for The Globe and Mail and an economics doctoral student at the University of California, Berkeley.
Before that, in March, forecasters had expected 25,000 new jobs in Canada in February. Instead we lost 2,200. And a month earlier, the number of jobs created in January came in at more than double what was predicted. A particularly comical case was October, 2022, where Canada created 10 times more jobs than analysts expected.
In defence of these forecasters, part of the issue is just that the problem is very hard. There are simply too many unknown unknowns in the economy and political environment to make reliable sense of it all. Often analysts get the mechanism right but the magnitude wrong. And sometimes new aspects of the problem become relevant without anyone having the courtesy of letting them know beforehand.
Thus, the discretion that analysts keep to adjust their forecasts, which was meant to allow them to account for confounding factors, also gives them the freedom to conform and play it safe. Your time series analysis, theoretical model or line of reasoning might lead you to a very different conclusion from your peers, but overstate these differences and it’s your neck on the line.
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