Bounded institutions.

• Author: Listokin, Yair
• Position: Introduction into III. Bounded Versus Unbounded Structures in Action, p. 336-365

ESSAY CONTENTS INTRODUCTION I. BOUNDED AND UNBOUNDED INSTITUTIONS A. Defining Bounded and Unbounded Institutions 1. Principals, Agents, and Bounded Institutions 2. Simplifying Assumptions a. Two-Tiered Institutions b. Sharing of Relative Quality Perceptions c. No Strategic Behavior d. Random Assignment of Subjects to Agents e. Optimal Agent Response to Bounds f. Principal Knows the Distribution of Subject Quality B. The Scope of Bounded and Unbounded Institutional Structures 1. Bounded Institutional Structures and Rules and Standards 2. Does the Typical Institution Have a Bounded or Unbounded Structure? II. BOUNDED VERSUS UNBOUNDED INSTITUTIONAL STRUCTURES A. Unbiased Agents B. Biased Agents 1. Benefits and Costs of Bounded and Unbounded Institutional Structures a. Theory b. Application to the National Science Foundation 2. Factors Favoring the Choice of a Bounded Institutional Structure a. Theory b. Application to the National Science Foundation 3. Perfect Outcomes with Imperfect Principals and Agents a. Theory b. Application to the National Science Foundation C. Error-Prone Agents Without Bias 1. Theory 2. Application to the National Science Foundation D. Principals with Imperfect Population Information and Agents with Different Preferences E. Rules Versus Bounds III. BOUNDED VERSUS UNBOUNDED STRUCTURES IN ACTION A. Traditional Regulatory Oversight Versus Regulatory Budgeting 1. EPA Regulations: The Case for Bounded Institutions 2. EPA Regulations: The Case Against Bounded Institutions a. Quantifiability b. Knowledge of the Distributional Parameters B. Mandatory Versus Discretionary Spending C. Minority Set-Asides and Croson D. Judicial and Quasi-Judicial Decision Making E. Timing CONCLUSION APPENDIX A. Model Setup B. Unbiased Agents C. Biased Agents 1. Bounds Remove Bias 2. Solving for the Agent's Policy Allocation 3. Comparing Bounds with No Bounds 4. Conditions Favoring Bounds 5. Ideal Outcomes with Uninformed Principals, Biased Agents, and Many Subjects D. Error-Prone Agent Without Bias E. Rules Versus Bounds INTRODUCTION

To bound or not to bound? While the question is not usually framed this way, policymakers face the choice of whether to "bound" in many legal contexts. Should Congress give government programs a bounded budget (as in discretionary spending) or allow the program budget to be unbounded and spent as needed (as in entitlement spending)? Should Congress bound the Environmental Protection Agency (EPA) by subjecting its regulations to a "regulatory budget," or should it allow the EPA to enact any regulations that meet a specified standard or rule? Should judges be bound in the total lengths of the sentences they can give, or should criminal sentences be left to judicial discretion? Should governments be required to award a bounded percentage of contracts to minority-owned businesses, or should the government consider minority ownership as a factor in awarding contracts without being bound to any target? Should the National Science Foundation (NSF) have a bounded budget and then award grants to the best projects that conform to the budget, or should the NSF choose a quality threshold and award grants to all projects that meet it--even if there are more or fewer projects meeting the threshold than expected? Should a law school instruct its professors to grade on a bounded curve, or should grading be left to the instructor's discretion?

In a bounded institutional structure, a policymaking body (the principal) places a binding numerical restriction on one or more dimensions of a subordinate body's (the agent's) decision process. The existence of the bound compels the agent to compare subjects who may or may not benefit from a program instituted by the principal but administered by the agent. Budgets, quotas, and curves are prominent examples of bounded institutional structures. In an unbounded structure, by contrast, the agent is not compelled to compare subjects but rather makes separate determinations about each subject.

This Essay has two purposes. The first is descriptive: boundedness is recurrent in law and policy, and there is particular value in naming the phenomenon and applying formal economic tools to explain when and why bounded structures are more (or less) attractive. The second is normative: numerical bounds have many underappreciated practical and theoretical attractions, and they might be used more extensively than they are now.

Before going further, it is important to avoid two possible sources of misunderstanding. First, bounded does not mean "rigid" in the sense of "constrained." An agent subject to a bound may feel much less constrained than an unbounded agent who must apply precise rules articulated by the principal. Instead of implying rigidity, boundedness refers to the existence of some aggregate numerical requirement that requires direct comparisons of one subject to another. Second, in a world of finite resources, all institutions are bounded to some degree. Entitlement spending, for example, cannot be infinite--even if that is what the programs ostensibly require. But in a bounded institution, the numerical restriction compels comparison among subjects relatively quickly, while in an unbounded structure, the tradeoffs among subjects may become apparent only much later (if they become apparent at all). As a result, I believe the bounded-unbounded distinction will prove fruitful even if it is not absolute.

Bounded and unbounded structures add a new dimension to the voluminous literature on legislative delegation to administrative agencies and other branches. This literature has focused on why legislatures delegate. (1) A smaller literature asks to whom legislatures should delegate--agencies, courts, or some other actor. (2) Yet another well-developed literature focuses on one aspect of how legislatures should delegate: should the principals provide agents with rules or standards in constraining the agents' delegated authority? (3)

The focus on bounded versus unbounded institutional structures introduces a new theme to the literature on how legislatures should delegate to courts and agencies. Bounded institutional structures impose aggregate numerical restrictions on agents and compel agents to make relative determinations among subjects. (4) Bounds can coexist with rules, standards, or complete discretion on other dimensions of the agent's decision-making process. For example, a grading curve specifies the number of each type of grade that the professor can award and compels the professor to compare students to each other. The curve is a bounded institution. But other dimensions of the grading decision may be subject to anything from a strict rule to complete discretion. One educational institution that uses a curve may provide professors with exam questions and grading rules, while another institution that relies on a curve may tell the professors nothing about how to assign grades.

Unbounded institutional structures entail no aggregate numerical cap on the agent's decision; they allow for anything from strict rules to unspecified discretion regarding that decision. For example, some entitlement spending programs, such as Medicare, obligate the government to "make payments .. . to any person who ... meets the legal criteria for eligibility." (5) Moreover, the government is not allowed to become involved in medical decision making. (6) By contrast, other entitlement programs, such as Social Security, use rules to determine which beneficiaries receive funding and how much each beneficiary receives. Focusing on bounded and unbounded institutional structures allows us to see that, contrary to standard analyses, the question of rules versus standards does not exhaust the question of how principals can (or should) delegate authority to agents.

When principals must delegate and agents are potentially biased, my discussion and model, which build upon the optimal delegation literature in economics, (7) offer several recommendations relating to the use of bounded institutions. Bounded institutional structures work well relative to unbounded structures when (1) there is relatively little variation in quality among subjects evaluated by the agent (for example, the quality of scientific grant applications to the NSF does not vary all that much across different applications); (2) agents evaluate a large number of subjects; (3) agents are likely to be biased relative to the principal; and (4) a rule that constrains the agent's behavior is impractical (for example, scientific quality is difficult to specify by rule, and a rule that attempted to do so would lead to poor funding choices).

Unbounded institutions, by contrast, outperform bounded institutions when subject populations are small and inconsistent. Bounded budgets for government departments subject to idiosyncratic needs--such as the Federal Emergency Management Administration (FEMA)--are a bad idea. Instead, FEMA and similar departments are better off with more flexible unbounded budgets that can respond to unexpected needs (such as those created by a catastrophic hurricane). In addition, unbounded institutions perform better when agents share preferences with the principal. For example, if the NSF demonstrates expertise in evaluating grant applications and shares Congress's preferences over how many projects to fund, then it should be trusted with an unbounded budget. The unbounded budget would allow the NSF to respond when the number of worthwhile applications is unusually high or low.

In some circumstances, the optimal delegation literature demonstrates that bounded institutional structures can approximate ideal outcomes even though neither the principal nor the agent is fully informed or free of bias. (8) Suppose, for example, that Congress is incapable of evaluating specific scientific proposals but has a general sense of how many scientific research projects are worth pursuing each year. (9) Further...