Representative photo: Chris Liverani/Unsplash
- As COP27 approaches, the spotlight once again turns to building a compelling national narrative around climate change – based on what India can do and what India needs.
- There are many independent estimates of India’s needs, ranging from $1 trillion to be invested over the next decade, to $10 trillion required to reach net-zero by 2070.
- How are targets and estimates like these determined and what do they mean for the country?
- Quantified targets can usually be traced back to scenario studies that are generated by powerful analytical tools called energy-economy models.
- They follow a seemingly elegant process – but if you look closer, you might notice questions about the finality of their results and the extent to which they can inform policy.
As COP27 approaches, the spotlight once again turns towards building a compelling national narrative around climate change – based on what India can credibly do and what India realistically needs. Five-hundred gigawatt of renewables capacity to be installed by 2030; 50% installed capacity to come from non-fossil sources by 2030; net-zero emissions to be reached by 2070 – there are many national targets setting the stage for such a narrative.
Equally, there are many independent estimates of India’s needs, ranging from $1 trillion to be invested over the next decade, to $10 trillion required to reach net-zero by 2070. How are targets and estimates such as these determined, and what do they mean for the country?
Quantified targets can usually be traced back to scenario studies that are generated by powerful analytical tools called energy-economy models. While such studies can take different forms, the essential premise is the same: a modeller makes certain assumptions about the economy, technology, and climate policies, and feeds these assumptions into the model in the form of scenarios. The model then runs computations and generates results for each scenario; these usually relate to a country’s projected emissions, costs of those policies, and the energy demand and supply mixes.
This sounds like a very elegant process – but how conclusive are the results, and what more do we need to know about these models to design policies?
Unclear, deterministic processes: There is a rich diversity of models that have been developed for use towards climate policymaking. Each modeller may use a certain model, based on varied sets of assumptions about the country’s socioeconomic future possibilities and needs – for instance, whether India is likely to grow at an annualised 5.5% or 6%, or whether the cost of solar power will fall by 45% or 50%, over the next decade – and each model may then treat these assumptions differently based on its structure.
As a result of these varied processes, different models may say very different things about how India’s climate and development goals can be attained. While this diversity of assumptions and outcomes can help capture a wider range of the uncertainties in India’s future pathways, a challenge lies in how credibly the assumptions are framed, how clearly the approaches are communicated, and how circumspect the studies are about these uncertainties. Often, the uncertainties may not be highlighted and the results of modelling studies may be deterministically treated as a fait accompli.
Insufficient focus on challenges and implications: Compounding this, most models focus on the technological solutions to mitigating emissions – offering recommendations on renewables, hydrogen, carbon capture, demand management, and so on. They are ill-equipped to comment on the political or behavioural aspects of implementing these solutions – the distributional impacts of phasing out coal on employment, for instance, or managing just transitions, dealing with resource constraints, or indeed exploring whether alternate trends of urbanisation or economic growth are possible.
Through this narrow scope, adopting modelled results can risk locking India into one techno-economic pathway and turn scenarios into self-fulfilling prophecies, where results that are projected to be economically feasible – without looking at socio-political constraints – are adopted in national target-setting.
These confounding factors present a problem for policymakers, who look to models for realistic outputs and are faced with conflicting bottom-line messages on what might be needed and what might be possible – under the highly specific conditions in which these models operate – and proceed to design policies based on limited information in the face of an uncertain future. Further, with this approach, it is very difficult to consider what the implications of these outputs might be for India’s development futures. It is no surprise then that this approach carries the risk of policies that have only limited success in implementation.
We need a deeper and more considered approach to modelling. Policymakers need to be able to better understand what these modelling studies are qualified to say, whether their statements are defensible, and the conditions within which they issue their statements and what information they aren’t able to capture.
There is a potential two-step approach to doing this. First, modelling studies should be carefully assessed for their structure (how well they are put together) and then for their implications (how lessons are interpreted from them). The first step involves asking whether the choice of model is appropriate, whether the inputs are credible, how robustly the scenarios are constructed, how the study considers uncertainties, and whether study outputs are validated.
In the second step, studies should be evaluated carefully for what they say – or imply – for what socioeconomic development patterns are being locked in, how the energy transition will be managed, what emissions are projected, what the investment needs are, how the study thinks about social equity and natural resource impacts, and what it will imply for India’s energy security.
A better understanding of these two things – the structure and implications of modelling studies – can help policymakers have more information about how to use these modelling studies in a nuanced manner, and what additional information to bring in, when they’re designing policies. This can lead to better policy design, and build in the wiggle room needed to deal with the many uncertainties present in India’s development futures while implementing policies.
Such an approach can also serve as a checklist of factors that should be considered when designing future modelling studies and can thereby encourage greater transparency and rigour in how studies are set up, so that they are clearer about what they are saying, as well as about recognising what they are unable to say.
The British statistician George Box famously said, “All models are wrong, but some are useful.” Given the importance of well-designed climate policies and the central role of models in designing them, it is critical to build and interpret future modelling studies better, to improve their usefulness and application.
The authors are grateful to Navroz Dubash and Sonali Verma for inputs to this article, and additionally to Eri Ikeda and Mandakini Chandra for their ongoing contributions to this project.
Aman Srivastava is fellow at the Centre for Policy Research, New Delhi. Kaveri Iychettira is assistant professor at IIT Delhi.