On assumptions, models and praying mantises

After nearly a years’ worth of gentle prompting I am – at last –  sitting down to write my first blog post for EDP. It is on the recently-ended Developing Scenarios for Economic Pathways project led by the Presidential Climate Committee (PCC). This was my first project I got involved with in my new job as the Energy & Climate programme lead at the EDP. It was also my first time focusing on South Africa after many years collaborating and partnering with colleagues in the global South more broadly. And it was the first time in a decade that I was again working alongside energy and economic models. It is fitting then I guess, that when I set down to reflect, I keep thinking about the assumptions I had when I started the project, and those I hold now that the project has drawn to an end.

The first set of assumptions I encountered in the project are relatively obvious to those that have worked in the energy and climate modelling space. These are the exogenous (externally supplied) assumptions that human modellers feed into energy and economic models to process. For example, the price of oil, the rate at which renewable energy generation capacity is fed into the grid, population growth, uptake of electric vehicles. These are not objective, uncontested facts. They reflect human judgements about plausible futures. And what comes in directly impacts what comes out (Junk in – Junk out).

Another set of assumptions that became apparent during the project process were the assumptions that a whole lot of people have about models. That models can predict the future and predict it in a whole range of nuanced and useful ways: tell us how the income in women-headed households will be affected by the closing down of coal-fired power stations. Reveal to us how the integration of electric vehicles into public transport will lower our carbon emissions. Demonstrate the efficacy of having skills training on unemployment in the country. Not so. Models can give us a reasonable indication of what might happen in some aspects of the future, but when you start factoring in the realities of life in South Africa, a country with one of the highest Gini coefficients in the world, models are just not able to deal with the nuance nor the complexity.

Do you know about the experiment with the carnivorous female praying mantis? For years it was accepted as fact that females ate their mates after mating. Except that the original observations were made in laboratory conditions, with stressed and hungry females under bright lights in confined spaces. When researchers changed those conditions, the cannibalism largely disappeared. The point? Real life does not operate in a vacuum.

Then there were the usual set of assumptions one makes at project design phase: about budgets, about results, about a consistent stakeholder engagement cohort allowing us to iteratively build on previous engagements – nope. People’s time and resources are limited. Things come up. Priorities shifted. Jobs changed. At each stage of the project, we were dealing with changes, with discoveries and with learnings, pivoting to ensure the process remained heading in the right direction despite a few detours.

And then, there were all those assumptions that we had absolutely no idea were even there. The assumptions that become so embedded in the way this particular community of practice thinks (and hopes) that they become fact. For instance, the assumption that good climate strategy and good governance go hand in hand. That things will go according to (government) plan. Or the assumption that there is no greed or corruption or crime to derail climate response plans. Aspirations are easily assumed as fact. It was revealing and rewarding working with those from outside the climate space to take us out of our Matrix – red pill or blue pill anyone?

What stood out the most to me though are the assumptions that I kept bumping into outside of the PES project. One of the biggest of these assumptions is that there is no place for civil society, or community-based organisations in the work of energy and economic modelling and planning because it is too technical. The ‘logic’ underpinning this assumption is that CSOs and CBOs only deal with the contextual and that they don’t have the knowledge, the capacity nor the desire to be part of national climate solutions and planning.

This was not what we found to be true during the course of the PES project. We found that in bringing together a cross-section of society, of sectors, and spheres of government to provide inputs into quantitative modelling. And to combine these models with qualitative inputs, we were exposed to realities we – as project implementers – didn’t know we didn’t know. Hurdles to Just low-carbon transitions were brought to the fore that we had not made the connections with. Challenges we know of but that weren’t top of mind were brought to the fore; challenges that make a big impact on how we plan for the future. Most of all that as a society we are all capable of providing knowledge and expertise to national planning processes. That co-creation can be done. Is it messy? Yes. Is it challenging? Absolutely. Is it worth it? Without a doubt. Kudos to all of those involved and a sincere thank you to the Presidential Climate Commission for having us along for the journey.

Editing: Natalie Tannous

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