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A SIMPLE TYPOLOGY IS PRESENTED TO DESCRIBE THE VARIOUS WAYS THAT INFORMATION, FUNDING, AND TECHNICAL ASSISTANCE CAN BE COMBINED IN FEDERAL PROGRAMS TO ENCOURAGE INNOVATION IN LOCAL PUBLIC AGENCIES. IT IS ARGUED THAT, IN CHOOSING AMONG FEDERAL INTERVENTION STRATEGIES, IT IS IMPORTANT TO CONSIDER THE ORGANIZATIONAL INCENTIVES EACH CREATES.

Policy scientists have long been concerned with understanding the basic tools, or instruments, that governments can use to accomplish their goals. The initial interest in inductively developing comprehensive lists of generic instruments for policy analysis soon gave way to efforts to discover more parsimonious, but still useful, specifications of the elementary components out of which instruments can be assembled. Moving from a generic instrument to a fully specified policy alternative, however, requires the designer to go much beyond the elementary components. Rather than directly specifying some of these details, the designer may instead set the rules by which they will be specified. The creation of these specifications and rules can be thought of as institutional design. This book helps scholars and policy analysts formulate more effective policy alternatives by a better understanding of institutional design. The feasibility and effectiveness of policies depend on the political, economic, and social contexts in which they are embedded. These contexts provide an environment of existing institutions that offer opportunities and barriers to institutional design. A fundamental understanding of institutional design requires theories of institutions and institutional change. With a resurgence of interest in institutions in recent years, there are many possible sources of theory. The contributors to this volume draw from the variety of sources to identify implications for understanding institutional design

Abstract
Cost‐benefit analysis, as a tool of general use in policy analysis or as a mandated analytical process in some rulemaking, provides protocols for assessing the relative efficiency of policy alternatives. However, inconsistent and apparently irrational decisions by consumers in some situations call into question the validity of inferring the values that consumers place on outcomes from their observed choices. It also opens the door for "nudges" that change the architecture of choice to promote more "rational" consumer choice. Differences between decision utility and experience utility and the willingness of consumers to pay for reductions in temptation provide conceptual bases for thinking about the efficiency of nudges. However, assessment of nudges and their role in behavioral public administration should also recognize that heterogeneous preferences can result in increases in utility for some and decreases for others. Therefore, nudges require systematic assessment like other policy instruments.

Intellectual and practical endeavors almost always demand theory to help make sense of the complex world. Descriptive theories seek to predict what will happen, or at least understand what has happened, in particular circumstances. Normative theories seek to inform agents about what they should want or do in particular circumstances. As professionals seeking to promote good governance, public administrators must be able to predict consequences. To do so, they can make use of any relevant descriptive theory without concern for disciplinary boundaries. I argue that this catholic approach largely, though not completely, obviates the value of unique descriptive theories specific to public administration. In contrast, public administrators require normative theories that speak to the choices they must make as members of a profession that seeks to promote the good society. Thus, although as public administration scholars we face the same pressure as our disciplinary colleagues to create descriptive theories, our most important theoretical contributions are likely to be normative.

Cuatro demandas han impulsado el desarrollo del análisis de políticas en Estados Unidos. Primero, los reformadores han buscado evidencia para sustentar sus esfuerzos. Comenzando con las oficinas municipales de la Era Progresista, los grupos que apoyan han buscado análisis de políticas de apoyo, lo que conduce a la proliferación de grupos de reflexión diferenciados. En segundo lugar, los políticos requieren de profesionales especializados para atender problemas perentorios. En tercer lugar, el enfoque mayor y la complejidad del gobierno, en niveles federales y estatales, demandan información para apoyar los procesos de toma de decisiones. En cuarto lugar, los políticos intentan sancionar sus acciones futuras (y las de otros) al disponer que se realicen análisis rutinarios a los variados tipos de decisiones.

Policy analysis often demands quantitative prediction—especially cost‐benefit analysis, which requires the comprehensive quantification and monetization of all valued impacts. Using parameter estimates and their precisions, analysts can apply Monte Carlo simulation to create distributions of net benefits that convey the levels of certainty about the fundamental question of interest: Will net benefits be positive if the policy is adopted? An inappropriate focus on hypothesis testing of parameters rather than prediction sometimes leads analysts to treat statistically insignificant coefficients as if they, and their standard errors, are zero. One alternative method is to use all estimates and their standard errors whether or not the estimates are statistically significant. Another alternative is to use all estimates but to shrink them toward zero and adjust their standard errors in an effort to guard against regression to the mean. Comparing the three methods (only use statistically significant estimates and their standard errors, use all estimates and their standard errors, use shrunk estimates and adjusted standard errors) in Monte Carlo simulation suggests that treating statistically insignificant coefficients as zero rarely minimizes the mean squared error of prediction. Using shrunk estimates appears to provide a more robust minimization of the mean squared error of prediction. The simulations presented here suggest that routinely shrinking estimates is a robust approach if one believes that there is a substantial probability that the true value of the parameter is near zero.

Like public administration before it, public policy has an uneasy place in the discipline of political science. The stress is most obvious in the distinction between theories that attempt to explain the policy process and theories that are useful to those who seek to operate within the policy process. Accommodating this stress within the disciplinary boundaries of political science poses a difficult challenge.