From the Fraser Institute

By Jake Fuss and Grady Munro

Premier Doug Ford, who will trigger an election this week, recently said he plans to “spend billions of dollars” to stimulate Ontario’s economy if President Donald Trump makes good on his threat to slap a 25 per cent tariff on Canadian exports into the United States.

But rather than piling on even more spending, the next Ontario government—whoever that may be—should enact policies that finally get provincial finances back in order and make Ontario an attractive place to work and invest.

Relief can’t come soon enough. The Ford government has woefully mismanaged provincial finances. When first elected in 2018, Premier Ford promised to balance the budget and reduce government debt—something Ford’s former finance minister Vic Fedeli described as a “moral” imperative. Yet since then, the government has run deficits in five of six years and its net debt burden has increased by an estimated $70.3 billion.

As a result, in 2023 Ontario had the second-highest debt burden of any province (only Newfoundland and Labrador had a larger burden) when measured on a per-person basis.

Based on the Ford government’s latest fiscal update, the reckless mismanagement has continued into this fiscal year (2024/25). Despite enjoying lower-than-expected debt interest costs and higher-than-expected revenues—which combined could have nearly eliminated the budget deficit—the Ford government instead chose to again increase spending and keep running deficits.

Why should Ontarians care?

Because the Ford government’s penchant for spending and borrowing is hurting Ontario’s economy. When the government runs a deficit and accumulates more debt, it competes with individuals, households and businesses for borrowing. This drives up interest rates (i.e. the cost of borrowing) for everyone, which can reduce the level of investment in the economy. Moreover, because rising debt and higher interest rates equal higher interest payments, the government faces pressure to raise taxes. And the brunt of the new tax burden will fall on younger generations of Ontarians.

Also this week, Premier Ford said President Trump “wants to attract businesses from Ontario to come down to the United States,” which will eliminate jobs in the province.

And Ford’s right. When policymakers create the conditions to attract people and investment, their economies grow and people prosper.

If the Ontario government wants to beat Trump at his own game, it should lower personal income taxes and make the province a more attractive destination for high-skilled workers such as engineers and entrepreneurs who contribute greatly to the economy and create jobs. Lower taxes also improve the incentive for individuals to engage in productive activities such as working, saving and investing. In 2023, Ontario had the third-highest top combined (provincial and federal) personal income tax rate in Canada and the U.S.

The government should also lower business taxes to make Ontario more competitive with the U.S. in attracting businesses and investment—the pillars of job-creation and prosperity.

Regardless of who wins the election, the next Ontario government should finally restore some semblance of fiscal responsibility and balance the budget. And it should lower taxes for workers and businesses to help create prosperity across the province. That’s a much more sensible and sustainable way to counter threats from Trump (or anyone else) than spending billions of dollars borrowed on the backs of Ontarians.

Jake Fuss

Director, Fiscal Studies, Fraser Institute

Grady Munro

Policy Analyst, Fraser Institute

From The Deep View

$600 billion collapse

Volatility is kind of a given when it comes to Wall Street’s tech sector. It doesn’t take much to send things soaring; it likewise doesn’t take much to set off a downward spiral.

After months of soaring, Monday marked the possible beginning of a spiral, and a Chinese company seems to be at the center of it.

Alright, what’s going on: A week ago, Chinese tech firm DeepSeek launched R1, a so-called reasoning model, that, according to DeepSeek, has reached technical parity with OpenAI’s o1 across a few benchmarks. But, unlike its American competition, DeepSeek open-sourced R1 under an MIT license, making it significantly cheaper and more accessible than any of the closed models coming from U.S. tech giants.

But the real punchline here doesn’t have to do with R1 at all, but with a previous language model — called V3 — that DeepSeek released in December. DeepSeek was reportedly able to train V3 using a small collection of older Nvidia chips (about 2,000 H800s) at a cost of about $5.6 million. Still, training is only one cost of many tied to AI development/deployment; while the costs associated with researching, developing, training and operating both R1 and V3 remain either unknown or unconfirmed, DeepSeek’s apparent ability to reach technical parity at a far reduced cost, without state-of-the-art GPU chips or massive GPU clusters, has a lot of implications for America’s now tenuous position in AI leadership. (Though DeepSeek says it is open-sourced, the company did not release its training data).

Since the release of R1, DeepSeek has become the top free app in Apple’s App Store, bumping ChatGPT to the number two slot. In the midst of its spiking popularity, DeepSeek restricted new sign-ups due to large-scale cyberattacks against its servers. And, as Salesforce Chief Marc Benioff noted, “no Nvidia supercomputers or $100M needed,” a point that the market heard loud and clear.

What happened: Led by Nvidia, a series of tech and chip stocks, in addition to the three major stock indices, fell hard in pre-market trading early Monday morning. All told, $1.1 trillion of U.S. market cap was erased within a half hour of the opening bell.

Performance didn’t get better throughout the day. Nvidia closed Monday down 17%, erasing some $600 billion in market capitalization, a Wall Street record. TSMC was down 14%, Arm was down 11%, Broadcom was down 17%, Google was down 4% and Microsoft was down 2%. The S&P fell 1.4% and the Nasdaq fell 3.3%. An Nvidia spokesperson called R1 an “excellent AI advancement.” This is all going into a week of Big Tech earnings, where Microsoft and Meta will be held to account for the billions of dollars ($80 billion and $65 billion, respectively) they plan to spend on AI infrastructure in 2025, a cost that Wall Street no longer seems to feel quite so good about.

It’s hard to miss the political tensions underlying all of this. The tail end of former President Joe Biden’s time in office was marked in part by an increasingly tense trade war with China, wherein both countries issued bans on the export of materials needed to build advanced AI chips. And with President Trump hell-bent on maintaining American leadership in AI, and despite the chip restrictions that are in place, Chinese companies seem to be turning hardware challenges into a motivation for innovation that challenges the American lead, something they seem keen to drive home.

R1, for instance, was announced at around the same time as OpenAI’s $500 billion Project Stargate, two impactfully divergent approaches.

What’s happening here is that the market has finally come around to the idea that maybe the cost of AI development (hundreds of billions of dollars annually) is too high, a recognition “that the winners in AI will be the most innovative companies, not just those with the most GPUs,” according to Writer CTA Waseem Alshikh. “Brute-forcing AI with GPUs is no longer a viable strategy.”

Wedbush analyst Dan Ives, however, thinks this is just a good time to buy into Nvidia — Nvidia and the rest are building infrastructure that, he argues, China will not be able to compete with in the long run. “Launching a competitive LLM model for consumer use cases is one thing,” Ives wrote. “Launching broader AI infrastructure is a whole other ballgame.”

“I view cost reduction as a good thing. I’m of the belief that if you’re freeing up compute capacity, it likely gets absorbed — we’re going to need innovations like this,” Bernstein semiconductor analyst Stacy Rasgon told Yahoo Finance. “I understand why all the panic is going on. I don’t think DeepSeek is doomsday for AI infrastructure.”

Somewhat relatedly, Perplexity has already added DeepSeek’s R1 model to its AI search engine. And DeepSeek on Monday launched another model, one capable of competitive image generation.

Last week, I said that R1 should be enough to make OpenAI a little nervous. This anxiety spread way quicker than I anticipated; DeepSeek spent Monday dominating headlines at every publication I came across, setting off a debate and panic that has spread far beyond the tech and AI community.

Some are concerned about the national security implications of China’s AI capabilities. Some are concerned about the AI trade. Granted, there are more unknowns here than knowns; we do not know the details of DeepSeek’s costs or technical setup (and the costs are likely way higher than they seem). But this does read like a turning point in the AI race.

In January, we talked about reversion to the mean. Right now, it’s too early to tell how long-term the market impacts of DeepSeek will be. But, if Nvidia and the rest fall hard and stay down — or drop lower — through earnings season, one might argue that the bubble has begun to burst. As a part of this, watch model pricing closely; OpenAI may well be forced to bring down the costs of its models to remain competitive.

At the very least, DeepSeek appears to be evidence that scaling is one, not a law, and two, not the only (or best) way to develop more advanced AI models, something that rains heavily on OpenAI and co.’s parade since it runs contrary to everything OpenAI’s been saying for months. Funnily, it actually seems like good news for the science of AI, possibly lighting a path toward systems that are less resource-intensive (which is much needed!)

It’s yet another example of the science and the business of AI not being on the same page.