PREDICTING THE PREDICTORS
We use predictive mathematical models constantly for all kinds of systems, behaviors, processes, and devices. We use them to try to predict future events. In some of these situations the models work well. In other situations, the models are lacking. And in some models, we simply haven’t had enough of the future yet to validate them.
That might be the case with something called the Social Cost of Carbon (SCC). From the Environmental Protection Agency’s Web site :
“ [the social cost of carbon] is meant to be a comprehensive estimate of climate change damages and includes changes in net agricultural productivity, human health, property damages from increased flood risk, and changes in energy system costs, such as reduced costs for heating and increased costs for air conditioning. However, given current modeling and data limitations, it does not include all important damages. ”
Although the SCC many believe arises from noble concerns for our future on the planet, perhaps the model behind it is a bit of a stretch. David Kreutzer, a senior research fellow in energy and climate change expresses some skepticism at a recent energy summit (Matthew Phillips, Mark Drajem, and Jennifer A. Dlouhy. “How Climate Rules Might Fade Away” Bloomberg Businessweek . 12/19/16–12/25/16, pp. 6–7):
“ Believe it or not, these models look out to the year 2300. That’s like effectively asking, ‘If you turn your light switch on today, how much damage will that do in 2300?’ That’s way beyond when any macroeconomic model can be trusted. ” (p. 7)
Predictive models can be great tools, but every tool is useless beyond its limits.
