| Summary: | Many Albertans are feeling short-changed given how much they contribute to the rest of Canada compared to how little help they get back when their economy is in serious trouble, as it has been lately. As a result, commentators and politicians in the province tend to focus their grievances on the unfairness of the federal equalization program. While it is true that the equalization program needs reform, that program was never meant to help a province such as Alberta, where GDP per capita and household incomes are above the national average, even in times when its economy shrinks. What Albertans should really complain about is the fiscal stabilization program, which is meant to be a form of insurance for provinces whose economies experience economic shocks. In reality, it is an insurance policy that has been designed so that it barely pays anything to Alberta. That much was starkly evident in 2015–16, when the province’s revenues contracted by a staggering $8.8 billion and this so-called insurance policy paid out Alberta a grand total of $248 million. Alberta suffered an revenue reduction of $2,114 per capita, but the fiscal stabilization program caps payouts at a meagre $60 per head. Worse, the current formula does not count drops in resource revenue as meaningfully as it counts drops in other forms of revenue, which distinctly disadvantages Alberta and other resource-dependent provinces, especially Saskatchewan and Newfoundland and Labrador. The fiscal stabilization program should be reformed to ensure that it actually provides adequate levels of insurance to the resource-dependent provinces. That is, after all, the stated purpose of the program. A new formula should be developed that will provide meaningful assistance to provinces when they need it. A fair formula for a fiscal stabilization program should meet the same criteria as any good insurance policy. It should cover only significant losses, which in this case should be a meaningful reduction in all of a province’s own-source revenues — including ...
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