Weathering the weather, whether we like it or not

One of the main hypotheses peddled by the “future risk” people is that the financial and economic effects of climate change are likely to be nonlinear.  The statement is technically wrong because nonlinearity is actually a theoretical certainty – there are no straight lines in nature; everything is nonlinear if you apply a high enough resolution.  

Of course, these people are not really interested in the technical nuances of modeling.  Saying that climate risk is nonlinear is really just a clever way to tell banks and investors that they should be very scared of global warming, even if the evidence points in the opposite direction.   Rich investors, banks, and corporations are quite capable of managing the risks and opportunities of climate change – which is likely why many lobby against government action to address it.

Now to be fair, if the end result of climate change is the cessation of all life on earth it’s likely that the data will start indicating negative consequences for even the mega-wealthy at some point.  If this happens, the nonlinearity hypothesis will be confirmed and the future-riskarians will finally be vindicated.  Obviously, they will have a very short time in which to revel in their victory before being wiped out like the rest of us.

But practically speaking, we have no idea whether the hypothesized nonlinearities will emerge at 10°C, 5°C, or 2°C above pre-industrial temperatures.   Because of this, we should behave as if climate risk causes and effects progress linearly. 

Even evidencing this is tricky.  At our current level of empirical understanding, we have a fair bit of difficulty finding robust linear associations between rising temperatures and economic outcomes.  It therefore seems premature to be talking about reliably identifying nonlinearities – both in terms of the timing of the inflection points that spark them and the behavior of the data after they’re passed.