This week, Alberta released its Carbon Competitiveness Incentive policy, which lays out the mechanics of its output-based pricing (OBP) system. We’ve talked a lot of about output-based pricing (also known as “output-based allocations” or OBAs) here at Ecofiscal as a sensible way to maintain incentives to reduce emissions, while also addressing concerns around leakage and competitiveness. And governments seem to agree: Manitoba’s new carbon pricing policy plans to include OBAs. So will the federal backstop policy. The free allocations in Ontario and Quebec’s cap-and-trade systems behave very similarly. And new, emerging policies in other provinces are considering the same tools.

Still, as for any complex policy, the details matter, especially when it comes to implementation.

To shine some light on those details, we asked Dave Sawyer and Seton Stiebert at EnviroEconomics—who’ve worked with multiple governments on this issue—for some help. They wrote this paper, laying out what they’ve learned about designing OBAs in the real world. You should check out the full paper, but here are a few of the highlights that stand out for me, considered in the context of Alberta’s announcement.

Wait, what exactly is output-based pricing, again?

First, let me pause for a quick refresher on output-based pricing or allocations (see here for a longer explanation). Basically: the system defines a sector-level benchmark for emissions intensity (a starting point for Alberta was top-quartile performance within a sector, though it has made adjustments in some cases). Based on that benchmark and a given firms’ output, the firm is allowed to produce some number of emissions for free. If the firm has more actual emissions than free “allocations”, it can buy additional credits (which it needs in order to have those emissions). On the other hand, if it has fewer emissions, the firm receives credits, which it can sell to other emitters who need them.

The upshot: emitters have incentives to reduce emissions by improving performance, not by shifting production, investment, and emissions to jurisdictions with weaker policy.

OK that’s the theory. Now back to Dave and Seton’s paper and applying these ideas in practice. Let me pull out three key insights.

Insight #1: Detailed data is scarce, making OBAs harder in practice than in theory

One of the key challenges in designing OBAs is choosing those sector-level benchmarks. What’s the right benchmark for a threshold? Too generous, and you’re letting emitters off the hook (and forgoing revenue that could have been otherwise used for useful things such as tax cuts). Too stingy, and you might not be sufficiently addressing the leakage problem.

Similarly, which sectors really need OBAs? As we’ve noted before, it’s really only the sectors that are both emissions-intensive (i.e., produce lots of GHGs per unit output) and trade-exposed (i.e., compete in global markets, where competitors face less stringent carbon pricing) that are really vulnerable. Nationally, that’s around 5% of Canadian GDP, but around 18% of Alberta and Saskatchewan’s economies.

Yet detailed, sector-level data for each province with respect to production, trade, and emissions isn’t publicly available. That creates challenges for identifying vulnerable sectors but also for defining those sector benchmarks.

A word of warning from Dave and Seton:

The administrative effort required to set the OBP rate within a solid policy package should not be underestimated. Setting the OBP rate can be a challenge, especially if industrial facilities are complex, unique or if there is a wide divergence in emissions performance between facilities or types of products produced. In the end, setting the OBP can be complex even when good baseline emission and production data is available, requiring a high level of knowledge about the regulated entities.

Insight #2: Output-based pricing shifts industry-government discussions

A prescriptive regulation might try to identify specific ways to reduce emissions, or specific outcomes that policy should achieve. Industry tends to have an information advantage when they discuss these regulations with governments, because they tend to know more about their own processes, costs, and opportunities to reduce GHG emissions.

Carbon pricing, on the other hand doesn’t require industry-specific information. It establishes a price on carbon, and lets firms, not governments, identify the opportunities for reducing GHG emissions that cost the least. That’s a key advantage.

Output-based pricing re-introduces some complexity. Because data is scarce, governments rely on conversations with industry and the information that industry can bring to the table in defining sector emissions-intensity benchmarks. That can create room for strategic behaviour on the part of firms. As Dave and Seton note, firms can and do make fierce arguments about why they should receive more output-based allocations rather than fewer and thus why a sector benchmark should be more generous.

Despite the challenges, output-based pricing shifts the debate away from whether emitters should be covered by policy. Instead, it allows policy to default toward including more emitters under the policy, and negotiate over the sector benchmarks and OBAs provided rather than the stringency of a regulation or the coverage of policy. That has implications for revenue generation rather than emissions reductions. Even then, those revenue implications matter most in the shorter term, since output-based pricing is a transitional measure and should be phased out over time, as higher carbon prices in other jurisdictions come into place.

Alberta’s new policy is a clear illustration. The policy released errs toward more OBAs rather than fewer, especially where there is limited information about specific sectors or new market entrants. Alberta’s plan also creates a three-year phase-in period, with sector benchmarks initially set to the average sector intensity, thus providing even more OBAs to firms in the short term.

But here’s the thing: that’s still a better approach than simply exempting some emitters from the price, because it ensures that more emitters face the incentive to reduce GHG emissions. And the Alberta sector benchmarks continue to decline over time after the phase-in period, though perhaps not as quickly as they could.

Insight #3: Adjusting and improving over time is critical

Both of the insights above lead to a third: dynamics over time matter.

Given the challenges of data and complexity of setting benchmarks, there’s a good chance that governments won’t set OBA thresholds perfectly. That means adjusting and improving the policies over time should be a priority. As the system gets up and running, new data will begin to be collected, and the success of output-based pricing can be evaluated and adjusted.

As Dave and Seton suggest:

Set it, test it and take stock. With the risks identified above, regulators may want to initially err on the side of caution when setting the OBP rate, especially if there are concerns over information availability or quality. Aligning an information collection program will therefore be needed from the outset of the OBP development. Then in future periods, the OBP can be updated as new information on outcomes and impacts becomes clearer.

Again, the Alberta proposal takes this advice, with assessment and updates scheduled in 2020 and then every five years moving forward. That will give policy-makers an opportunity to reassess sector benchmarks based on real data from the performance of sectors over time.

Output-based pricing in theory and practice

These real-world complications for OBA design are important, but they don’t undermine the case for carbon pricing and output-based allocations. That combination still creates incentives for cost-effective emission reductions, while managing concerns around leakage, exactly as Alberta’s system is designed to do. Alberta’s approach acknowledges the challenges of OBA design in the real world. But it also illustrates a practical solution: evaluating and adjusting output-based pricing can help improve the policy as more data becomes available.

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