Study: Stronger Short-Term Goals Are Needed in Climate Change Policy Because of the Likely Pace of Policy Change
Long-term climate change policy in the US and abroad is likely to change very slowly, according to a study published by an MIT researcher in Decision Analysis, a journal of the Institute for Operations Research and the Management Sciences (INFORMS). With that conclusion, author Dr. Mort Webster calls for stronger short-term goals to reduce carbon emissions.
Webster writes that climate change policy decisions are normally made sequentially over time and under uncertainty, due to the magnitude of uncertainty in both economic and scientific processes, the decades-to-centuries time scale of the phenomenon, and the ability to reduce uncertainty and revise decisions along the way.
...the central question for near-term climate policy, both in the United States and abroad, is whether or not regulations of greenhouse gas emissions can be delayed for another decade or whether some level of mitigation effort is required now. When irreversibilities exist in the presence of uncertainty, delay is not necessarily optimal.
...there is a critical element that is missing from both the policy debate and from the formal models of climate policy: path dependency. Political scientists have long noted the tendency of political systems to exhibit path dependency, and have used this feature to explain a number of political outcomes, such as European party systems...and the comparative development of healthcare systems...The idea of path dependency is that once a particular course of action has been chosen, it becomes increasingly difficult over time to reverse that course...Policies tend to exhibit lock-in, and although a legislature might from time to time create a new bureaucratic agency, it is exceedingly difficult to eliminate one.
A large-scale international policy issue such as climate change is especially vulnerable to path dependencies.
...Does accounting for the path dependency in political systems change the first-period (today) optimal choice from a sequential decision model of climate policy? If it does, then this would argue for a more aggressive hedging strategy with greater emissions reductions for near-term climate policy. This action would allow for greater flexibility if significant reductions are required later in the century.
Although staging climate change policy decisions over time would seem to make sense, he points out that the tendency of US and international policy to change extremely slowly requires front-loading the difficult decisions.
A central question for near-term climate policy, both in the United States and abroad, is whether or not regulations of greenhouse gas emissions can be delayed, and whether some level of mitigating effort is required at once. Countering those who say the dust should settle before committing to big decisions, he points out that when a decision will be irreversible—as is likely the case in climate policy—delaying the decision is probably not the best option, according to research in decision analysis.
Climate policy optimization models typically assume that some fraction of baseline emissions can be reduced in each period, ranging from none to nearly 100%, he notes. But, he points out, the range of reductions considered in any period is independent of any choices made in previous periods.
The conclusion of this study for the climate policy modeling community is that applications of sequential decision models over very long time horizons should consider path dependencies in the political systems modeled. Otherwise, if policies at each time point can be reconsidered without regard to past decisions, we may place an unrealistic expectation on future generations and eliminate future options by not laying the groundwork with minimal policies today. Ignoring path dependencies risks giving qualitatively biased advice to policymakers as to whether it is yet time to begin mandatory emissions regulations.
Mort Webster (2008) “Incorporating Path Dependency into Decision-Analytic Methods: An Application to Global Climate-Change Policy”, Decision Analysis, doi: 10.1287/deca.1080.0114