April 21, 2021

By Colleen Kaiser  & Martin Olszynski

Although it may seem counterintuitive — constraints drive creativity and innovation.

In the context of regulation, the magnitude of constraints is called ‘stringency’. In the agile regulation context, stringency refers to “the degree to which regulation requires compliance innovation” and, as a result, how much change a given policy or regulation can be expected to generate.ⁱⁱⁱ When policies are more stringent - or strict - firms have a greater incentive to devise innovative low-cost paths to reaching their regulatory objective.

Stringent regulations in and of themselves will not automatically drive efficiency increases and encourage innovation. In fact, if not well designed and implemented, strict regulations can limit options to innovate, thereby reducing incentives to move beyond current environmental or performance standards, increasing risks to firms, industries or markets and reducing competitiveness. The key is to design regulations in ways that minimize compliance costs by maximizing the incentive and potential to innovate. This is why ensuring a sufficient level of flexibility, the subject of our last blog post, is integrated into regulations.

In practice, striking this balance is not an easy task. That being said, there have been many successful efforts, both in Canada and abroad, from which to draw upon for best practices. For example, in Canada, Nova Scotia’s bold waste diversion targets have helped the province beat all others to achieve the lowest amount of annual waste generated per capita.^iv These stringent targets have also fostered the emergence of new firms like Sustane Technologies that aims to convert waste into clean-burning fuels and recyclable materials, with a demonstration plant currently under construction. As an international cleantech example, Japan’s Top Runner program targets continuous improvement in the energy efficiency of manufactured products.^v The program sets ambitious product-specific energy performance requirements through iterative target revisions in consultation with stakeholders, setting the next energy efficiency standard based on the current best-in-class performer and potential future technological advances.

Critically, setting the optimum level of stringency requires regulators that are well-informed, which itself requires internal capacity but also collaboration with industry and other relevant stakeholders. The California Air Resource Board’s development and implementation of the state’s first Low Emission Vehicle regulations throughout the 1990s exemplifies the importance of this regulatory capacity^vi; iterative, good-faith collaboration with industry around revising stringency levels and timelines allowed these pioneering regulations to be successful in practice.

Because there is often a level of uncertainty involved in predicting future advancements, an iterative approach is necessary to gauge the level of stringency over time. Environmental policies that chart a predictable path for increasing levels of stringency can significantly reduce the policy risk that chills investment in clean innovation. This characteristic, which we call ‘dynamic predictability,’ will be explored in the next in SP’s agile regulation blog series.