ARTICLE CONTENTS INTRODUCTION I. EXPERIMENTATION AND DECENTRALIZATION II. THE EFFECTS OF POLICY LEARNING A. Deliberative and Political Information B. Beneficial and Mischievous Uses C. Incentives and Timing D. Applying the Model III. TURBULENT WATERS A. Limited Deliberative Information B. Risks of Harmful Political Information C. Conclusion IV. CLIMATE LABORATORIES A. Limited Deliberative Information B. Potential for Beneficial Political Information C. Conclusion V. CONTRASTING POLICY ENVIRONMENTS INTRODUCTION
American political culture values decentralized governance. The preference toward decentralization shows up in the federalist constitutional structure as well as in numerous national regulatory programs that preserve a significant role for the states. From a policy perspective, this preference is typically grounded in considerations of interjurisdictional diversity, political accountability, and policy experimentation. (1) In recent years, the experimentation angle in particular has enjoyed enthusiastic supporters, who argue that decentralization engenders innovation and learning that has wide-ranging benefits for democratic policymaking. (2)
The nub of the argument in this Article is that, although policy experimentation may tend to generate information, that information can be a mixed blessing that brings mischief along with insight. (3) As a consequence, policy experimentation has both costs and benefits; policy learning is not an unalloyed advantage of decentralization; and, in the decentralization calculus, the potential for policy experimentation may just as often count against decentralization as for it. Accordingly, well-designed governance regimes will decentralize in ways that promote useful experimentation, while cutting off, or at least declining to facilitate, experimentation that is more likely to cause harm.
Classically, policy experimentation has been described as a technocratic, even scientific process. In Justice Brandeis's famous terminology, states are akin to "laboratories" in which impartial researchers search for effective means to promote social ends. (4) More recently, federalism scholars have focused on "the discursive benefits of structure." (5) They describe a federalism in which decentralization makes room for a diversity of views within the national conversation and provides "democratic churn" that enlivens national politics. (6) Under the discursive conception, federalist structures facilitate democratic deliberation between a range of interests and perspectives. This process ultimately helps constitute a national polity that is more dynamic, inclusive, and resilient.
But there is also a downside of experimentation that demands its due. In an imperfect democracy, there are many kinds of lessons to be learned, and not all of them will promote social well-being. Politicians are interested in learning how to exploit the benefits of incumbency. Well-organized interest groups want to learn how to translate their collective action advantages into economic rents. Ideologically extreme activists are interested in learning how to take advantage of voter inattention to drive policy away from median preferences. All of these actors are hungry for information that confirms the validity of their policy positions or undermines their opponents. In the messy world of policymaking, information might not always be put to its highest and best use.
This Article takes as its starting place the Jekyll-and-Hyde nature of policy experimentation. Given the dual social potential of information, ceteris paribus, the goal of policy designers should be to maximize the net benefits of experimentation through efficient forms and levels of decentralization. To facilitate this inquiry, I develop a general framework that disaggregates policy information according to type of information and the ways in which that information is likely to be put to use. This framework can be applied to different contexts to anticipate the social effects of policy learning and to evaluate whether more, less, or differently structured decentralization is appropriate. Of course, this analysis does not end the calculation--there are legal and constitutional constraints to consider, as well as other policy factors to accommodate. But departing from the optimal level and form of experimentation, for whatever reason, should be acknowledged as a cost to be balanced against other factors.
With this general framework in hand, I discuss two contemporary environmental rulemakings of high political, legal, and social significance. One establishes the jurisdictional reach of the Clean Water Act; the other sets greenhouse gas emissions limits for the power sector for the first time. These two rules sit at the heart of the Obama Administration's environmental legacy and have generated aggressive legal challenges. Like many environmental policies, they also have strong implications for the balance of national, state, and local power and will influence whether, and how, policy experimentation will take place on these issues in the coming years. Applying the analytic framework developed here, I examine the consequences for policy learning of each rule and evaluate how well they capitalize on the promise--and avoid the pitfalls--of experimentation.
Any given policy experiment can be thought to generate two types of information. (8) I will call the first kind deliberative information. This type of information concerns either the means or ends of policymaking from the perspective of social welfare. (9) If an experiment generates data on the efficacy of a particular policy intervention at achieving its goals, it is deliberative information. If an experiment produces information that can serve as air input into broader democratic conversation about the value of some policy goal, that is deliberative information.
The second category is political information, which concerns ideological preferences or political incentives. A policy experiment may show, for example, whether elected officials who carry out the experiment tend to persist in office or to be voted out. That data is political information. In addition, an unfamiliar policy intervention may not have a well-established location in ideological space. It may be possible to observe early adopters of the policy to determine where in ideological space the policy is located. This communication of ideological preferences is also political information.
An example may help illustrate. Several municipalities have adopted laws in recent years banning local businesses from dispensing single-use plastic bags. (10) One of the goals of these ordinances is to reduce waste in local landfills. The early adopters of the bans essentially engaged in an experiment that generated both deliberative and political information. From the perspective of social welfare (i.e., deliberative information), it may be possible for other jurisdictions to observe ban-adopting municipalities and determine whether they are successful at reducing waste at local landfills. Perhaps the bans achieve that goal. Or perhaps commercial enterprises replace thin plastic bags with thicker plastic bags that are ostensibly reusable, but are just as likely to be thrown out. (11) If so, then bans may not be an effective waste-reduction strategy. More broadly, a plastic bag ban fiasco may prompt the local citizenry to rethink their environmental priorities, and they may end up focusing on preserving local forests, reducing storm water runoff, or installing cleaner electricity generation. Or plastic bag successes may prompt a broader rethinking about the appropriate role of local government in enhancing collective welfare. The policy experiment on bags, then, could create deliberative information about the appropriate priorities and goals of environmental policy or local governments.
The experiment can also generate political information concerning the place of bag bans within ideological space and the political incentives surrounding the measure. Assume that it is unclear to many people, at first impression, whether a bag ban is a liberal or conservative type of policy. Once a handful of municipalities have adopted the policy, it is possible to observe the political affiliations of the interest groups that favored or opposed the ban and the politicians who voted for or against the ban. If environmentalists, labor unions, single women, young people, minorities, and college professors favored the ban, and Democratic officials voted for it, an observer would have good reason to believe that bag bans were a liberal type of policy. In addition, politicians can determine whether city council members who opposed a ban faced a backlash by voters and lost their seats, and plastic bag manufacturers might observe the type of counter-messaging that was or was not successful in earlier campaigns and adjust their strategic branding accordingly. All of this information would fall into the political category.
Whether policy experimentation can be expected to lead to socially beneficial outcomes depends on the balance between deliberative information and political information and how that information is put to use. (12) This Article illustrates the costs and benefits of state policy experimentation through an analysis of two recent environmental regulations. The first case study is the Waters of the United States Rule, a determination by the Environmental Protection Agency (EPA) and Army Corps of Engineers concerning their authority under the Clean Water Act. The Waters Rule was developed in response to the Supreme Court's decision in Rapanos v. United States. (13) The rule has prompted considerable pushback from farmer and landowner groups that argue that the agencies assert authority over too many of the nation's wetlands and water bodies. The second case study is the Clean Power Plan, an EPA rule to limit greenhouse gas emissions from existing...