Essay by Eric Worrall
Professor Andy Pitman wants central banks to hire climate scientists to help them build high-resolution risk models to properly assess climate risk in the region. But the Aussie RBA disagrees that its role is to assess climate risk.
Trillions of dollars at risk because central banks’ climate models don’t fit
Climate studies show that the model used cannot predict severe weather locally, leading to poor risk estimates
Peter Hannam
Wednesday, August 10, 2022 03:30 AEST…
Professor Andy Pitman, director of the Australian Research Council Center of Excellence for Climate ExtremesHowever, managers say they are relying on models that predict how the average climate will change as the planet warms, but are less likely to be used to predict how extreme weather will affect the planet. affect individual localities such as cities.
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“Without a doubt, we are overestimating the cost of climate change in some areas and underestimating it in others.” Pittman said. “We need to take this issue seriously – not just access information flying around and think we can package it up to do the proper economic assessments.”
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Pitman’s article, and a separate one that he co-authored for Natural Climate Change in 2021, looked at models used by groups such as Greening the financial system. NGFS advises around 100 central banks and other regulators globally, including the Reserve Bank and Apra of Australia.
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Without climate scientists of their own, the RBA and Apra rely on scenarios generated by the NGFS to understand how a warming planet will affect economic and financial stability.
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“We do not conduct risk assessments on behalf of the organizations we regulate,” the spokesperson said.
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Professor Andy Pitman’s research is available here.
Of course, to meaningfully model climate change in the region, national reserve banks and central banks will need climate models that yield useful results.
Professor Andy Pitman himself let the cat out of his pocket in 2019, of climate modeling utility, when he revealed that climate scientists can’t even tell us whether global warming whether it will increase or decrease rainfall – a metric that is quite important for determining climate impacts, especially in an arid country like Australia.
There is also a moral hazard associated with central banks being too strict in their assessment of risk. If central banks require regulated entities to use specific models, then those central banks will be morally liable if they suffer financial loss, due to deficiencies in the system. defect in the central bank’s risk model.
To bet any imposed model will fail is a very safe assumption, because All non-trivial financial models contain flaws and limitations.
For example, many financial models prior to the 2007-10 global financial crisis omitted liquidity risk, assuming that there will always be buyers of financial instruments. Assumption of infinite market liquidity spectacularly broken in the 2007-10 subprime crashwhen bankers playing it safe, who stuck with their financial model recommendations, stuck with catastrophic losses making subprime mortgage investments, they couldn’t offload in time to save his own skin.
One of the great survivors of the GFC, Greg Lippmann of Deutsche Bankfamously made huge profits during the subprime crash by modifying his computer model proposals and betting everything on the impending total market crash.
What about climate models? I suspect bankers will enjoy finding ways to create better risk models and would be happy to further integrate climate risk models into their financial risk projections, if the integration thus providing value. But are climate risk models ready to incorporate?
Former responsible banker of HSBC Stuart Kirk recently complained that he is being pressured to add unrealistic assumptions to climate finance models. to make them interesting. “Even with a carbon tax, even with growth, they can’t make climate risk move with the needle, so they have to take their smart winks into the back room to deliver a shock. huge interest on their models to get attention.”
Of course, some scientists make predictions that are far more interesting than those of mild financial losses, like predictions of impending catastrophic tipping points or even impending extinction. But how do you combine a wild series of scenarios, from near-normal business to an impending extinction event, into a financial risk model and still produce meaningful yields? means? Especially since even climate scientists make more pedestrian forecasts sometimes admit that their model is running “horribly hot”?
For example, how do Australian banks model future rainfall changes into their regional farm mortgage credit score models, when Professor Andy Pitman himself recently admitted that no one can tell whether global warming will cause precipitation on a continental scale to increase or decrease?
At least bankers experimenting with market liquidity models have something tangible to work with – they can forecast their models based on high-quality historical price and liquidity data, to see if their pattern generates the right buy/sell signals. But as Anthony Watts has demonstratedHistorical global climate data has serious quality problems.
Until climate scientists produce climate models that produce a range of useful predictions, models that add quantifiable value to risk calculations, they can continue to expect expect less enthusiastic reception outside of their immediate fan base, as they try to push bankers to make more use of their product.
I have no problem with Professor Andy Pitman approaching bankers and asking for funding. I was impressed with Professor Pitman’s creativity, as he acknowledged the model’s uncertainty in 2019, even if then he seems to step back and qualify his original statement. I think Professor Pitman will find the idea receptive to bankers to help fund the development of better risk models. But it seems a great strain for Professor Pitman to stress that climate models in their current form are ready for banking risk, that the models are mature enough for bankers to begin with. hire climate scientists to help integrate climate models into their risk projections.
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