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Turning back to the modelling, there is a practical and even more intimate link that is imposed by what the optimisation algorithms can solve (to be clear, these are optimising the system, not for individuals) – which generally means things have to be (log) linear. As far as I’m aware, this also means you need to assume implicitly a social planner to manage the system. It can handle internalising externalities through a basic pricing mechanisms but is limited on possibilities for more realistic treatments of technology and market structures.

This is fine if the question you are asking is how to design a system at least cost, given the assumptions and constraints. But less appropriate for scenario analysis, where the assumptions become proxy for real-world behaviour. Incidentally, I’m speculating a bit now, but to model the structure you are suggesting (individual optimisation with system-level constraints) I think you would need to resort to an agent-based framework. I came across a non-climate example recently, will try to dig out.

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Well if you mean benefits to society, anyone making this argument “If reducing greenhouse emissions had economic benefits then we would do it anyway without new policy” is obviously nonsense because the whole point of externalities, public goods is that beneficial things won’t happen without intervention.

I don’t really understand this ” if you account for these externalities in the optimisation function then you could still get better outcomes in a low-carbon case”

in a model with externalities, optimising by self-interested private agents won’t give you the best outcomes, but optimising by a social planner with tools such as taxes and regulations at their disposal.can.If the “low carbon case” is the best outcome that will not be obtained by laissez-faire, then taxes and regulations etc. could achieve it.

“I am arguing that GDP in its narrow definition can increase in a scenario with lower emissions, even ignoring any feedbacks from climate (see next paragraph). This seems to be the main point we disagree on.”

I did not write anything about whether GDP can increase with lower emissions. Whether it can or not will depend on technology and productivity and efficiency of resource allocation and utilization.

I agree that if the truth is that there are lower emissions technologies that firms could profitably adopt but which they don’t know about, your model will be over optimistic about them being adopted without some policy intervention. I didn’t think the problem with Nordaus at al. was being over optimistic about firms adopting green tech, whereas in reality they won’t because they don’t know about it.

yes you need to do something that deviates from perfect market assumptions to end up with a model that has persistent capacity underutilization. If the models you don’t like don’t incorporate market failures that are both present in reality and are relevant in this context, then there’s your problem – optimisation, rationality etc. are not the culprits.

I don’t think I am really starting from any position, I am just pointing out that mainstream economics does not support the proposition that if something is economically beneficial, we’d be doing it already, or that regulations etc. are necessarily costly

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I am talking in macro terms, so do mean economic benefits to society and not individual firms. I fully agree that one of the reasons we have not seen stronger climate policy is the lobbying of the firms that will lose out.

This comes to the point on externalities and the logical mainstream policy response of a carbon tax. Similarly on innovation, where there are positive externalities, the logical response is subsidies. If I have interpreted correctly, you are saying that if you account for these externalities in the optimisation function then you could still get better outcomes in a low-carbon case – and it is reporting GDP rather than a more aggregate welfare function that is the issue. So the issue is not the models per se, but how they are applied/reported.

I am arguing that GDP in its narrow definition can increase in a scenario with lower emissions, even ignoring any feedbacks from climate (see next paragraph). This seems to be the main point we disagree on.

I view the main issue as fundamental uncertainty, which I think is even more relevant to this topic than most others – e.g. we don’t know what the climate damages will be and therefore how to set a carbon tax rate. On a more basic level, we see many examples of firms that could improve energy efficiency to their own advantage but don’t, e.g. either because they are not aware of the options or simply are focused on other concerns. In neoclassical terms you could call this another market failure (knowledge gaps), which active policy could correct. Similarly, we see that it can take some time for new/better technologies to be adopted because firms don’t want to take risks on new equipment.

Regarding spare capacity, I can only see two ways you would get it under the conditions you set – either you put a value on not using something (as in theories of ‘voluntary’ unemployment) or relax the assumption of perfectly flexible markets with prices adjusting to equilibrium – otherwise all resources will be used. Again you could regard markets not adjusting as a market failure and put in policy to correct. In contrast, Keynes saw it more as a natural outcome even in perfect markets, again related to uncertainty and firms wanting to hold cash in case of emergency.

To summarise, I think we are coming at the same issue from two different directions. You are suggesting starting from the standard theory and then making allowances for where the assumptions don’t hold, i.e. the market failures. I am suggesting that the market failures are too numerous and we start from a position where we don’t use these assumptions – in part because it would be difficult to identify all the places that we would need to step in (likely the case in the results in the chart).

The European Commission reflects this in its modelling of energy policy – two models are used, one is a modified CGE model that is based on rational behaviour but constrainted to reflect many real-world constraints, the other is the Cambridge Econometrics post-Keyesian model referenced in the post. Happy to send some links comparing the results from the models if you are interested.

Hope that helps, and thanks again.

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As you no doubt know, one of the most fundamental ideas in context of climate change is negative externalities. So when you write:

“If reducing greenhouse emissions had economic benefits then we would do it anyway without new policy”

Do you mean “economic benefits” as in benefits to society as a whole, or benefits in the sense of private financial returns? If reducing greenhouse emissions is the most profitable thing to do from a private returns perspective, then yes maybe people would “do it anyway”. Otherwise no, firms will tend not do things that benefit society but which lose them money, that’s the whole point of externalities. So no (sensible) mainstream economist is going to argue against the introduction of policies to reduce greenhouse gas emissions because the costs must outweigh the benefits otherwise we’d be doing it anyway. That’s sheer nonsense and i am quite sure Nordaus would make no arguments like that. .

That means that regulations etc. are not necessarily costly from society’s point of view – it depends if they are counteracting market failures such as externalities. So if your model is telling you regulation etc. can only be bad, it’s not because of optimising, rationality etc. it’s because you don’t have externalities etc. in the model. There are lots of lots of mainstream models with optimization and all the assumptions you blame, that recommend interventions. Here’s one:

The example you give of German subsidies getting the solar market moving is pretty much a text-book case of why government intervention might be needed because private actors won’t do it by themselves – see e.g. box 1-1 here:

if you want to argue that investments to go green will have benefits because innovation is demand-led and the economy is operating below capacity so could use some stimulus, well fine your model needs to incorporate that idea but you can do that with rational optimising agents with perfect knowledge.

So whilst mainstream climate models may or may not be rubbish, it looks to me like you have misdiagnosed the cause.

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