Learning through Policy Variation

Article excerpt

ARTICLE CONTENTS

INTRODUCTION

  I. THEORIES OF PUBLIC POLICYMAKING

 II. CHOOSING POLICIES FROM AN OPTIMAL SEARCH PERSPECTIVE: THEORY
     AND APPLICATIONS
     A. The Theory of Optimal Search
     B. Factors Influencing the Optimal Degree of Policy Variance
     C. The Optimal Search Approach: Applications
        1. Choosing Between Reversible Regulations
        2. The Optimal Search Approach and Penalty Default Rules in
           Contract Law
        3. Increasing Shareholder Democracy in Corporate Law
        4. Federalism and the Optimal Search Approach

III. THE OPTIMAL SEARCH APPROACH: OBJECTIONS, RESPONSES, AND
     MODIFICATIONS
     A. Burkean Objections
     B. The Costs of Changing Policies
     C. Irreversibility, Real Options, and the Optimal Search Approach
        1. The Real Options Approach to Policymaking
        2. Burkeanism, the Precautionary Principle, and the Real Options
           Approach
        3. Sticky but Reversible Policies
     D. Optimal Variance in Different Policymaking Contexts
     E. Reversibility and Institutional Design
        1. Sunset Clauses and Legislative Entrenchment
        2. Separation of Powers
        3. Stare Decisis

 IV. PUBLIC POLICYMAKING INCENTIVES AND THE OPTIMAL SEARCH
     APPROACH
     A. High-Variance Policies and Reelection/Reappointment Incentives
     B. High-Variance Policies and Incentives for Political Advancement
     C. Federalism and Incentives To Innovate

  V. IRREVERSIBILITY AND POLITICAL INCENTIVES: APPLICATIONS AND
     RECOMMENDATIONS
     A. Reversible Regulations
     B. Contract Default Rules and Increased Judicial Policymaking
     C. Shareholder Power
     D. Federalism and Preemption
     E. Other Sources of Variation: Direct Experimentation

CONCLUSION

INTRODUCTION

How should policymakers choose laws and regulations when outcomes are uncertain? The answer initially seems simple: they should choose the best policies--the ones with the highest average payoffs along some metric. Burkeans have a different view. They are skeptical of human ability to divine the best policies. Instead of encouraging policymakers to choose the policies that seem best, Burkeans urge policymakers to choose policies that change the status quo incrementally rather than drastically. When policymakers can learn from the results of their laws and make changes, however, both the common sense position--choose the best policy--and the Burkean position--choose new policies cautiously and incrementally--are often wrong.

When learning is possible, (1) innovative high-risk policies with lower average outcomes but the potential for greater outcomes become preferable. (2) If a high-risk policy proves a failure, then the policy can be changed, and the policy with the highest average payoff can be pursued. If the policy succeeds, then policymakers will have achieved an ideal outcome and will no longer need to search for alternatives. Learning allows policymakers to limit the downside of a high-risk policy but still enjoy the upside, making a high-risk policy with a lower average payoff a better initial choice in many cases than a low-risk policy with a higher average payoff.

In other words, policies serve two functions. Their primary function is to achieve some outcome in the current period. But the information provided by observing a policy's outcome also assists the search for better policies for the future. And the best policy from a search perspective often differs from the best policy for the current period. The "optimal search" for a policy seeks an excellent policy that will enable policymakers to end the policy search. Thus, optimal search theory favors high-variance policies, because variance increases the probability of finding excellent policies. The average outcome of a policy matters less from an optimal search perspective than the upside of a policy because it is unlikely that a reasonable but suboptimal outcome will end the search for a good policy. …