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Economists making spectacularly bad forecasts, 1961 edition.

Summary:
Back in the 1960s, the Ontario government's Department of Economics dutifully cranked out annual population forecasts. What is remarkable about these forecasts is how far wrong they were. The economists completely failed to predict the demographic changes that were about to hit Ontario. Here are the 1961 projections side by side with the actual 1976 population numbers for Ontario, downloaded from Statistics Canada's CANSIM table 051-0001. (An image taken from the Ontario Economic Survey can be found at the end of the post): The Ontario Department of Economics projections were most spectacularly wrong for children under 10. The economists failed to anticipate the end of the baby boom. They also, it seems, underestimated the improvements in life expectancy that would be enjoyed by older Canadians, and the amount of migration into Ontario. Now one could argue that the early 1960s collapse in birth rates was triggered by something completely outside the economists' demographic models - a unforeseen and unforeseeable technological change.  Yet the fall in birth rates was predictable, even in 1961. With the brief exception of the 1950s, Canadian birth rates had been falling for most of the previous century - see the picture below borrowed from here: Indeed, by 1961 the number of births in Canada had already declined from its 1959 peak.

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Back in the 1960s, the Ontario government's Department of Economics dutifully cranked out annual population forecasts. What is remarkable about these forecasts is how far wrong they were. The economists completely failed to predict the demographic changes that were about to hit Ontario.

Here are the 1961 projections side by side with the actual 1976 population numbers for Ontario, downloaded from Statistics Canada's CANSIM table 051-0001. (An image taken from the Ontario Economic Survey can be found at the end of the post):

Screen Shot 2017-02-20 at 7.37.16 PM

The Ontario Department of Economics projections were most spectacularly wrong for children under 10. The economists failed to anticipate the end of the baby boom. They also, it seems, underestimated the improvements in life expectancy that would be enjoyed by older Canadians, and the amount of migration into Ontario.

Now one could argue that the early 1960s collapse in birth rates was triggered by something completely outside the economists' demographic models - a unforeseen and unforeseeable technological change. 

Yet the fall in birth rates was predictable, even in 1961. With the brief exception of the 1950s, Canadian birth rates had been falling for most of the previous century - see the picture below borrowed from here:

Canadian Fertility 1871-1996

Indeed, by 1961 the number of births in Canada had already declined from its 1959 peak. The birth control pill had been in the market since 1957 - although not marketed as such - and had already been approved for contraceptive use in the US. Second-wave feminism was beginning. For example, US President John F Kennedy signed an Executive Order calling for a Presidential Commission on the Status of Women in 1961.

If the forecasters in the Department of Economics had talked to historians, medical researchers, or even their wives, they might have come across some information that would have caused them to question their forecast of continuing high birth rates.

Now one might say - so what? Why does it matter that the Ontario Department of Economics got the demographic forecasts spectacularly wrong?

It matters because governments, firms, and other economic actors rely on demographic forecasts to make investment decisions. If the demographic forecasts are wrong, schools get built unnecessarily. Medical students train as obstetricians, when they would be better off becoming orthopaedic surgeons. Real estate developers build homes for large families, not small ones. Inaccurate demographic forecasts are unlikely to be good economic ones.

This historical incident matters because it says something about why long-term economic forecasting is hard and how forecasts could be improved. What I take from this story is that sometimes questioning the parameters of a model, and bringing in additional information from novel sources, may be of greater value than refining and tweaking a business-as-usual model.

For those who are interested, here is an image showing the 1961 Ontario population forecasts: 20170220_170711

Frances Woolley
I am a Professor of Economics at Carleton University, where I have taught since 1990. My research centres on families and public policy. My most-cited work is on modelling family-decision making, measuring inequality within the household, feminist economics, and tax-benefit policy towards families. I hold a BA from Simon Fraser University, an MA from Queen’s, and completed my doctorate at the London School of Economics, under the supervision of Tony Atkinson.

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