I have repeatedly asked myself, “Why did you write this paper?”
It is hard to dispute the social importance of environmental questions. As I, and others, have argued elsewhere, purely evidence-based policy is a misnomer in general, and most certainly for this particular problem. Theory and evidence have to be equal dance partners.
Quantitative storytelling is a credible way to conduct policy analysis in dynamic settings. It combines so-called “stylized modeling” with empirical evidence. We purposefully consider multiple stories, with carefully worked-out narratives that are formally captured as models, which have different ramifications for the environment and the economy. For dynamic problems such as this one, multiple “stories” are virtually impossible to dismiss on either theoretical or empirical grounds. I have little doubt that this multiplicity is germane to many policy problems. So, perhaps the answer to my own question should be obvious.
This analysis has attracted much more attention than most of my recent papers. For me, it has been both challenging and rewarding. My co-authors, Mike Barnett, William “Buz” Brock and I pushed ourselves to bring together tools from decision theory, asset valuation and control theory to confront uncertainty outside of the usual confines of risk analysis typically focused on in economics and finance.
So why did I pose the question at the outset? In part, perhaps in large part, this contribution is a “proof-in-concept” paper for informing policy in the face of uncertainty. Thus, we designed the framework to be a template for future research, including by ourselves and other researchers. But we also deliberately chose climate economics as our featured example. Because our specific analysis is both novel and novelistic, I feel it needs some explanation. While we use the social cost of carbon to explore the impact of uncertainty, our reported numbers are merely our first step for this type of analysis. These numbers are not ready to be posted on the Environmental Protection Agency (EPA) website, which is mechanically embraced by “green books” for policy analyses. We did not write this to provide soundbites for media coverage.
In our quantitative application, we show that the social cost of carbon could become very large without additional forms of mitigation, technological change, adaptation and/or policy intervention. We abstract from regional and developmental heterogeneity, which should be part of a more full accounting. Of course, these limitations should be explored and they will alter the implied social cost of carbon. We are actively engaged in revealing extensions that will allow us to confront some of these shortcomings along with more ambitious climate inputs. In summary, this paper is not meant as the answer, but as our initial step in incorporating broad notions of uncertainty in a formal policy analysis while avoiding overstated claims of our current knowledge base.
I am continually haunted by the warning in Hayek’s Nobel address:
“Even if true scientists should recognize the limits of studying human behavior, as long as the public has expectations, there will be people who pretend or believe that they can do more to meet popular demand than what is really in their power.”
While those social scientists interested in quantitative policy analysis should not just throw in the towel, they should remain cognizant of the limits to their knowledge and understanding.
Lars Peter Hansen is the Director of BFI’s Macro Finance Research Program and the David Rockefeller Distinguished Service Professor in Economics and Statistics and the Booth School of Business.
This reflection was originally posted on the Becker Friedman Institute website.