Use In Policy Analysis Research Articles

Personal computer simulations of two New England trawl fisheries

This paper outlines the basic components of two personal-computer-based bioeconomic simulators for New England otter trawlers and presents selective results illustrating their use for policy analysis. It has proved difficult to monitor the economic status of commercial fisheries because of technical, bureaucratic and cost considerations associated with survey procedures, and the difficulty of timely acquisition of biological and harvest data. The author has developed an alternative approach which combines information from various data bases, including periodic surveys, and integrates them in a budgeting or “economic engineering” approach. The result of these adaptations is a tool useful for extension education as well as for research policy evaluation.

The Seven Deadly Sins of Policy Analysis

The practice and use of policy analysis has expanded throughout the United States. Yet, as part of our political system, policy analysis has been influenced by a set of recurring problems, problems of the policy process that involve both analysts and their clients. These problems are identified as "sins." Sinful policy analysis is channeled, distant, late, superficial, topical, capricious, and apolitical.

The Fate of Policy Analysis in Congressional Decision Making: Three Types of Use in Committees

TW A TITHIN the past two decades, Congress has dramatically enhanced its analytic capability, increasing the number and responsibilities of its professional staff (Malbin 1979; Salisbury and Shepsle 1981) and the quantity and quality of its analytic information (Commission on the Operation of the Senate 1976; Frantzich 1982). Two new congressional support agencies have been created, the Office of Technology Assessment and Congressional Budget Office, and the policy analysis components of the other two, the Congressional Research Service and General Accounting Office, have been significantly upgraded. The fate of policy analysis in congressional decision making, however, remains unclear. Research on the use of analytic information has focused almost exclusively on the executive branch, perhaps in response to suggestions that the potential for using policy analysis in Congress appeared to be quite limited (Davidson 1976; Jones 1976; Dreyfus 1977). In addition, research on congressional decision making has yet to produce models which explicitly connect floor voting choices, which are not likely to be directly influenced by policy analysis, with the activities which precede and structure those choices, activities in which the influence of analytic information is likely to be much stronger. This article is an attempt to provide some theoretical context and empirical underpinning to discussions of both the use of policy analysis in Congress and the implications of that use for congressional decision making. Such an endeavor contributes in two more general ways to greater understanding of the role of analysis in public decision making. First, it extends the scope of research, which has been largely restricted to administrative organizations. Investigating the use of policy analysis in legislative environment forces explicit attention to the political factors which affect use, something often ignored. Second, the legislative setting presents, in stark terms, the basic difficulty of combining expert advice with democratic political institutions, which MacRae contends is a major problem of contemporary democratic societies (1976: 169). Congress, the institution once envisioned to be tied most closely to the common sense of the common man, is now being confronted with increasingly complex problems that appear to require considerable specialized knowledge. An

Reaffirming the Importance of Strategic Use

Focusing exclusively on the substantive use of policy analysis results in a limited assessment of the role of analysis in policymaking, particularly in a congressional setting. This article develops a two-dimensional perspective on use, incorporating a substantive-strategic dimension as well as a concrete-conceptual dimension. The importance of this perspective is demonstrated through an analysis of congressional use of two projects produced by the congressional Office of Technology Assessment, one on coal slurry pipelines and the other on residential energy conservation. Results indicate both the existence of substantive use and the importance of more strategic uses.

Patterns of Policy Analysis Use for State Governments: A Contingency and Demand Perspective

A question yet to be suitably answered by public administrators is how well public programs and organizations work. The approaches to answering this question have ranged from laissez-faire economic explanations to the recent emphasis on analytical approaches such as those classified as policy analysis. Some observers have been skeptical about the possible benefits of analysis in that a first step in analysis is the definition of objectives; since objectives of public programs may be difficult to define, the results of analysis may be dubious. Others have proposed that rationality should be increased in government and administration and that analysis is an important contributor to increased rationality.' Any study of policy analysis at the state level must recognize that state governments are simultaneously similar and dissimilar. On the one hand, they are similar from the standpoint of the types of services which they provide. On the other hand, they vary markedly in their regional, political, social, and economic characteristics.' A major area of variation is how they manage themselves, and, particularly, whether they use policy analysis in decision making. The objectives of this study are to seek a general model which can explain the use of policy analysis in the states, to determine whether there are consistent influences on the use of policy analysis in the different branches of state government, and to consider what may be the future status of policy analysis in the states.

Budgeting Strategy: Cross-Sectional versus Longitudinal Models

ment not only on its own practices but also on those of other executive agencies and the legislature. Also, no attempt was made to verify the responses; the research team did not try to validate the extent to which any given state was truly conducting policy analyses. This data has had broad exposure to practitioners and researchers, however, and has been widely reported upon for other purposes. See Mushkin, op. cit.; Robert D. Lee, Jr. and Raymond J. Staffeldt, Executive and Legislature Use of Policy Analysis in the State Budgetary Process: Survey Results, Policy Analysis, 3 (Summer, 1977), pp. 395-504; and Robert D. Lee, Jr. and Raymond J. Staffeldt, Educational Characteristics of State Budget Officers, Public Administration Review, 36 (July/August, 1976), pp. 424-428. Given the structure of the questions, the numerous cross-validating uses reported in the literature, and a lack of reason to challenge the reliability of state budget officers, the authors assume that substantial validity and reliability can be attributed to the data. 22. Because of the nature of the dependent variables, different statistical analyses were required. The variables pertaining to executive decision making allowed for interval level analysis such as multiple regression. The categorical data for the legislative and agency dependent variables required a more robust multivariate method, such as discriminant analysis which allows for the examination of nominal and interval level independent variables. This method also corresponds to regression for the executive analysis. For a more detailed description of the uses and advantages of discriminant analysis over bivariate analysis, see Norman H. Nie, et al., SPSS: Statistical Package for the Social Sciences, 2nd ed. (New York: McGraw-Hill, 1975), pp. 435-444.

Econometric Studies of Labor-Labor Substitution and Their Implications for Policy

A critical synthesis of the rapidly growing literature on substitution among labor force aggregates is presented. Despite the large number of studies now available, the only firm conclusions are: (1) Physical and human capital are complements and are jointly substitutable with raw labor. This has implications for policies that subsidize the wage costs of low-wage workers. (2) Young workers' own-wage elasticity of demand exceeds unity, but the degree to which they are substitutes for older workers is unclear. The paper suggests that future research should concentrate on substitution among workers disaggregated by age, education, or sex rather than by the blue-collar-white-collar distinction used in most work and that has little use in policy analysis.

Evaluation of Policy Simulation Models by Robert E. Pugh (review)

BOOK REVIEWS Evaluation of Policy Simulation Models. By Robert E. Pugh. Washington, D.C.: Information Resources Press, 1977. P. xv+320. $30.50. The use of mathematical models for policymaking in biomedical research programs and medical administration has had its ups and downs over die past decade. On the face of it, mathematical models (particularly in a computerized form) would seem to offer a viable alternative to die usual "brownie-point" decision making that goes on in most professional areas. It is attractive, in principle , to substitute a coldly objective mechanism for reaching an optimal decision for the inherently political process of finding a compromise that wiU satisfy a committee of professionals by exchange of brownie points. A mathematical model can be constructed to reflect the benefit-to-cost balance for the patients involved or for the public (rather than the benefit-to-cost situation for the decision makers). However, in actual medical and scientific decision making the use of mathematical models is relatively rare at present. The uses tend to be limited to unimportant or hypothetical planning situations. Is the reluctance to use mathematical models in policymaking decisions in the medical and scientific areas due to the inadequacies of the models, of die decision makers, or of the medical and scientific communities? Is it simply that the idea is too new to have won acceptance in the inherently conservative professional areas? Is it simply lack of availability of useable models when decisions are to be made? Is it due to overselling or underselling of this approach to policymaking? The idea is not really new. In my 1953 book, Designfor Decision [1], the concepts of statistical decision making developed in the 1940s were presented in a simplified procedures for drawing conclusions from data. Some of these procedures—controlled clinical trials, for example—have become generally accepted and are widely used in the medical area. Policymaking procedures have not. However, in 1953 clinical trials were almost as new and unfamiliar as the policymaking procedures. Since the conceptual bases of drawing medical conclusions and of making medical policies are not very different, one might wonder : Why did one set of ideas "catch on"? Why did another and similar set fail to make much progress in a quarter of a century? In one sense die book under review helps to provide an answer to this question . However, it is the book itself, radier than what is said in the book, that is informative. What is being considered in this work is a special kind ofmodel that is common in operations research, systems analysis, and other areas with a focus on policymaking—a "simulation model." The particular model that is being inPermission to reprint a book review printed in this section may be obtained only from the author. Perspectives in Biology and Medicine ¦ Summer 1978 \ 629 vestigated is an "urban dynamics" model. It is a more modest cousin of the "Umits ofgrowth" model which made headlines because ofdie end-of-the-world forecasts it produced. The author tries hard to make an even-handed neutral evaluation of the urban dynamics model. This effort to avoid prejudgment of the model means that the author takes 179 pages of text (in die 192 pp. of the main text) to get to the point: "Although the evaluation reasonably concludes that urban dynamics is inadequate for policy analysis use, the evaluation is far less satisfying in pinpointing a concise reason why the model is unsatisfactory. Basically, this is because the model is inadequate for a very broad reason: It floats free of the real world." This statement brings into sharp focus the basic difference between a genuine scientific model, mathematical or otherwise, and the kinds of models that are commonly devised by pure mathematicians, by computer-oriented systems analysts, or by economists. The prime directive of modern science, the Galilean rule, applies to any dieory: A theory must fit the facts. It makes no difference whedier a theory is expressed in an algebraic language or in some verbal technicaljargon , it must be firmly anchored to reality. In genuine science, thefirst step (not the last step) in the evaluation of a mathematical model (which is simply a theoretic construct...

Policy Analysis for the Congress

Congress and the Executive Branch are the nation's most important consumers of policy analysis. In recent years the Congress has created a number of innovative policy analysis institutions and expanded others. As a result, and to the surprise of some observers, the rate of legislative use of policy analysis is beginning to approach that of the Executive Office of the President. The information and analysis capabilities available to the Congress are a development of fundamental importance to the conduct of the nation's business. Not only have they strengthened the analytical phases of oversight, investigations, and appropriations some major phases of congressional decision making but they also have enlarged the opportunities for public participation in decision making. The purposes of this presentation are to: 1. Examine the main policy analysis institutions available to the Congress; 2. Identify factors that affect the use of policy analysis by the Congress; and 3. Describe some current reform proposals aimed at strengthening the policy analysis capability of the Congress.

Energy systems: Modeling and policy planning

An overview of modeling in the energy field and its role in the formulation of national energy policy is presented. The nature of the modeling task and the various steps that it encompasses are described. The methodological alternatives available to the energy system planner in the conceptualization, development, and use of models are presented. Alternative policy instruments in the various supply and demand sectors are examined and their use in policy analysis is discussed. Finally, recent experience in the modeling field is drawn upon to exemplify the interactive nature of model building and point out some areas of immediate challenge that hold promise for the future.

A Model of the U. S. Apple Industry: A Quadratic Interregional Intertemporal Activity Analysis Formulation

AbstractAn in‐depth analysis of the U. S. apple industry and its problems requires simultaneous consideration of its multiple dimensions of space, time, resources, commodities, production activities, and marketing levels. An empirical model incorporating these dimensions is constructed and its use for policy analysis is demonstrated by measuring the impact of alternative size reductions in regional apple marketings on f.o.b. level industry and regional net returns. The model could also be used in determining the ramifications of changes in consumer demand, transportation costs, and marketing margins on such factors as production, prices, and interregional flows.

Policy Analysis and Policy Development

This paper addresses three questions: (a) What is policy analysis? (b) How has policy analysis affected policy in a few cases? and (c) What tentative prescriptions can be made to improve the usefulness of policy analysis? Policy decisions with respect to the enactment of Medicare/Medicaid, the adoption of the all volunteer armed force, and the development of the Family Assistance Plan are reviewed to assess the role, if any, played by policy analysis. The role of analysis in incremental program change is also discussed. Some general conclusions are drawn from comparative analysis of these cases.

Cross-impact matrices: An illustration of their use for policy analysis

The cross-impact matrix method of forecasting, under development at the Institute for the Future, is being used by IFF in a study of alternative future environments for education. This is being performed for the Educational Policy Research Center, of the Syracuse University Research Corporation, USA.