The economic costs of carbon pricing in Canada—both for the overall economy and households—have been a focus of intense political debate. Much of this debate, however, fails to distinguish between the consumer carbon price or fuel charge, which is paid by everyday Canadians, and industrial carbon pricing—also known as output-based carbon pricing or large-emitter trading systems (LETS)—that target emissions-intensive and trade-exposed large emitters.  

Unfortunately, the Parliamentary Budget Officer (PBO), whose office is tasked with providing independent economic and financial analysis to Parliament, has in the past conflated the consumer and industrial carbon prices. And even more unfortunately, they’ve done so in ways that have overstated the cost. 

For the past two years, the PBO has published analyses of carbon pricing that found it taking a significant toll on the economy and households. But in April 2024, the PBO admitted that it had been combining the impacts of both retail and industrial carbon pricing in its analysis, when commenting on the effect of the consumer carbon price alone. The PBO committed to updating its analysis in a Fall 2024 report.

But how well is the PBO equipped to accurately assess the impacts of industrial carbon pricing? After years of analyzing Canada’s carbon pricing systems, we are skeptical of the PBO’s estimates—not just due to their admitted error of conflating consumer and industrial pricing impacts, but because their modelling finds much larger negative impacts to key industries than other Canadian studies examining the same research questions.

Additionally, we understand that the PBO’s model lacks regional differentiation and therefore does not have the ability to examine how each province has implemented its carbon pricing system. Finally, we understand that their model fails to account for key technologies, including carbon capture, which are critical for reducing emissions and avoiding costly emissions reductions through reduced output. 

In this blog, we explore evidence on the economic impacts of carbon pricing. First, we compare the PBO’s 2023 projections with modelled results from Environment and Climate Change Canada (ECCC), as well as with the Climate Institute’s analysis with Navius Research (CCI/Navius). All models assess the combined impact of the consumer fuel charge and industrial carbon pricing, comparing them to a scenario without carbon pricing through 2030. While differences are expected, the PBO’s conflated projections consistently predict much higher costs. We suggest potential reasons for these discrepancies. 

Finally, since neither the PBO nor ECCC separated the consumer fuel charge from industrial pricing, we present our own estimates, showing that LETS, in addition to providing the lion’s share of emissions reductions, have minimal effects on households.

Exploring the discrepancies 

All three analyses find that carbon pricing slows economic growth compared to a no-policy scenario—though growth remains positive. The magnitude of those impacts, however, varies significantly. The PBO projects GDP in 2030 to be 1.3 per cent lower than it would otherwise have been. In contrast, ECCC and CCI/Navius estimate more moderate GDP impacts of 0.9 per cent and 0.5 per cent, respectively. Again, economic growth remains positive, but slightly slower than a scenario with no price on emissions.

Widely differing results in two key sectors help explain the higher GDP impacts in the PBO analysis: 

• The PBO estimates that the transportation sector will shrink by 22.3 per cent with carbon pricing, while ECCC and CCI/Navius estimate a decline of 5.9 and 1.0 per cent, respectively, by 2030. In our view, the PBO’s impact is implausibly large for a domestic sector with relatively limited trade exposure.
• In the oil and gas sector, the PBO projects a significant slowdown due to carbon pricing, estimating the sector will be 21.5 per cent smaller by 2030 compared to a scenario without carbon pricing. In contrast, both ECCC and CCI/Navius predict much smaller impacts, with reductions of 4.3 per cent and 4.0 per cent. We expect the projected contraction in the PBO model affects households through lower returns on investment, reduced labour income, and overall macroeconomic slowdown. Once again, the difference in estimated impacts is, in our view, an implausibly large output reduction from the industry in response to a policy imposing a net compliance cost equivalent to a few dollars per barrel of oil before tax and royalty payment deductions.

The PBO’s more severe GDP impacts translate directly to higher estimated household impacts, as slower economic growth in key sectors like oil and gas and transportation work their way through the economy. 

The differences between PBO and other projections are particularly telling when examining household impacts. Two metrics shine some light on impacts for households: 

• The PBO projects a 2.3 per cent decline in labour income, while ECCC projects a 1.5 decline, relative to no consumer and industrial carbon pricing. Lower labour income means reduced compensation for workers, leading to a greater impact on household spending. 
• ECCC forecasts a 0.7 per cent decline in household consumption (i.e., how much households spend), while CCI/Navius estimates a smaller, 0.2-0.4 per cent reduction, presenting a more optimistic view. The PBO’s consumption estimates are not publicly available, and were not made available to CCI.

Explaining the discrepancies

We expect that major differences in the PBO’s modelling assumptions contribute to a likely overestimation of industrial and household costs. The discrepancies in the PBO’s analysis follow from several factors:

• Insufficient characterization of policy details: By including the large-emitter trading systems in the backstop jurisdictions, the PBO has more than doubled the covered emissions attributed to the fuel charge in the report: emissions from covered fuels are roughly 230 megatonnes and LETS are about 285 megatonnes, or a 142 per cent increase in priced fuel charge emissions. This aggregation of the consumer and industrial systems will surely be resolved in their next report.  
• Overlooking regional differences: The design of LETS varies significantly between jurisdictions. We understand that the PBO is using a single national macroeconomic model without regional specificity, which could introduce biases that overlook the diverse regional economic structures and unique LETS systems. It is unclear to us how the PBO shoe-horned the different provincial LETS systems into a single national model.
• Under-representing key technologies: Macroeconomic models tailored to predict energy and emission outcomes—models like the one used by PBO—tend to lack explicit representation of technologies. Given high impacts discussed above, especially in transportation and oil and gas, we strongly suspect the PBO’s modelling does not integrate carbon capture and storage, electric vehicles, and biofuels, which are all essential for realistic cost estimates of complying with climate policy. Failing to explicitly account for technology or using simple approximations, which implicitly limit the ability of firms to reduce emissions by means other than shuttering production, would lead to overestimated economic costs.

In our modelling, accurately capturing the key design elements of carbon pricing policies is crucial for making reliable predictions about their economic impacts. Without attention to the following factors, models can easily overestimate costs and misrepresent the actual burden on industries and households:

• Keep revenue within large emitters: Compliance payments from large emitters are typically funnelled into technology funds and reinvested back into the sector, reducing the average cost of emissions reductions. This approach protects industry balance sheets and output while keeping economy-wide costs down. If these funds are diverted elsewhere in the model, such as to households or government, macroeconomic impacts are likely to be overestimated.
• Represent complex policy design and varied costs: LETS design is more complex than the fuel charge and requires detailed, nuanced modelling. Incorrectly representing these markets can significantly overestimate costs. Sectors and facilities have unique performance standards, which vary by provincial LETS program and type of emissions, leading to a wide variation in compliance costs—ranging from actual benefits for cleaner firms (which can sell credits) to modest costs for less-clean firms.
• Account for credit trading: Incorporating a functioning market for tradable credits is essential for accurately modelling the economic impacts of LETS. Credit trading allows firms to buy and sell credits, minimizing compliance costs across jurisdictions. This market mechanism significantly reduces costs for businesses, preventing inflated projections of carbon pricing impacts.
• Include budgeted technology subsidies: Accurately modelling complementary policies, such as technology subsidies, is crucial to understanding the economic effects. These subsidies help industries lower costs and mitigate profit impacts, reducing the overall burden of carbon pricing. Failing to account for these interactions can result in inflated cost estimates, underestimating the positive effects of policy support on industry performance and the broader economy.

Understanding the impact of LETS

Our modelling shows that LETS have a relatively neutral effect on households—it’s worth unpacking why that is prior to the PBO publishing its own estimates for LETS impacts later this year. This limited impact is particularly clear when looking at the limited changes in household consumption across provinces (Figure 1 below).

Under LETS, large emitters on net pay only a fraction of the full consumer carbon price, typically around $10 per tonne compared to $80, which limits the costs that are passed onto households and minimizes competitiveness impacts. Firms also have several compliance options, such as banking credits, investing in abatement technologies, using offsets, and making fund payments, all of which help reduce costs. Combined with technology subsidies and revenue recycling back to industry, average firm cost impacts are kept low, which we find avoids significant income reductions. Our analysis shows that LETS actually result in a 0.1 per cent benefit to household consumption in 2030, compared to a 0.31 per cent reduction from the fuel charge. Across jurisdictions, we estimate the average impact of the Canadian carbon pricing policy on household consumption to be just -0.21 per cent by 2030. If fewer complementary policies are included in the model, the impact of carbon pricing is closer to 0.4 per cent. 

In provinces such as Alberta, LETS mechanisms that pass savings to consumers through the electricity market can even increase household consumption. Alberta’s electricity sector, for example, yields saleable credits from non-emitting sources of generation, which lowers overall electricity prices for consumers and increases investment, resulting in a modest increase in real household consumption (i.e., how much households are spending).

Table 1: Modelled change in household consumption with carbon pricing

Federal backstop jurisdiction	ECCC combined	Navius/CCI
		Combined	Fuel charge	LETS
Alberta	-1.15%	0.35%*	-0.36%	0.71%*
Saskatchewan	-1.29%	-0.26%	-0.02%	-0.24%
Manitoba	-0.11%	-0.61%	-0.57%	-0.04%
Ontario	-0.56%	-0.32%	-0.26%	-0.06%
Prince Edward Island	-0.31%	-0.63%	-1.08%	0.46%*
Nova Scotia	-0.47%	-1.00%	-0.57%	-0.43%
Newfoundland and Labrador	-0.53%	-0.81%	-0.85%	0.03%
Average	-0.53%	-0.21%	-0.31%	0.10%

Informing reality

Our modelling has found that the LETS policy, as currently designed, should have far less impact on household costs. We look forward to seeing updated PBO estimates that more accurately distinguish between industrial and consumer carbon pricing systems. We remain concerned, however, that modelling assumptions in the PBO’s approach may overestimate the impacts of carbon pricing, and that the high costs in their previous publications were not due to the inclusion of the LETS, but to the model itself. 

Ultimately, credible economic analysis matters. Credible modelling assessing policy impacts can help inform the debate over costs and benefits, avoiding the amplification of unreasonable expectations about economic impacts—either too high or too low—and their potential political fallout. With transparent and nuanced modelling, Canada can make informed policy choices to reduce greenhouse gas emissions while balancing household affordability and competitiveness.