The Use Of Computer Simulation Models For Policy Analysis

The purpose of this book is to place computer simulation studies within the paradigm of intervention research that is concerned with comparing the outcomes of health care delivered under different policies. This book presents computer simulation as a tool for testing various policy alternatives that have been developed by decision-makers within health care systems. This approach differs from the use of computer simulation in operations research, where simulation helps determine the configurations of a system that will allow it to function optimally. Although simulation of health care processes is not new, few health care systems have used simulations as a basis for re-engineering the delivery of health services. There is growing appreciation that the complexity of health care processes exceeds the capacity of individual disciplines–health services research, health economics, or operations research–to guide health care reform. In this book, the authors focus on bringing the methodological rigor of evaluative research to the design and analysis of such simulation studies. The book is intended as a reference for health services researchers. It offers a comprehensive description of the methodology of conducting simulation studies in evaluation of service alternatives in surgical care using discrete-event models, including the steps for identifying the clinical and managerial activities of the perioperative process, determining the model requirements, implementing simulation models, designing simulation experiments and analyzing the experimental data, and interpreting and reporting results. The book also offers examples of specific aspects of conducting simulation experiments: how to determine the number of runs needed to estimate the effect of implementing a health care policy; how to allocate the number of runs to study groups in simulation experiments aiming to evaluate policy or management alternatives; and how to use statistical analysis to estimate, interpret, and report effect sizes.

Public policy and management problems have been described as poorly defined, messy, squishy, unstructured, intractable, and wicked. In a word, they are complex. This book illustrates the development and use of simulation models designed to capture some of the complexity inherent in the formulation, management, and implementation of policies aimed at addressing such problems. Simulation models have long existed at the fringes of policy inquiry but are not yet considered an essential component of the policy analyst’s toolkit. However, this situation is likely to change because with improvements in computational power and software, simulation is now easier to include in the standard repertoire of research tools available for discovery and decision support. This volume provides both a conceptual rationale for using simulations to inform public policy and a practical introduction to how such models might be constructed and employed. The focus of these papers is on the uses of simulation to gain understanding and inform policy decisions and action. Techniques represented in this volume include Monte Carlo simulation, system dynamics and agent based modeling.

This book provides a comprehensive approach to the study of policy analytics, modelling and informatics. It includes theories and concepts for understanding tools and techniques used by governments seeking to improve decision making through the use of technology, data, modelling, and other analytics, and provides relevant case studies and practical recommendations. Governments around the world face policy issues that require strategies and solutions using new technologies, new access to data and new analytical tools and techniques such as computer simulation, geographic information systems, and social network analysis for the successful implementation of public policy and government programs. Chapters include cases, concepts, methodologies, theories, experiences, and practical recommendations on data analytics and modelling for public policy and practice, and addresses a diversity of data tools, applied to different policy stages in several contexts, and levels and branches of government. This book will be of interest of researchers, students, and practitioners in e-government, public policy, public administration, policy analytics and policy informatics.

This book evaluates the Simulated International Processer (SIPER) model of the international political system, which was derived from the Inter-Nation Simulation model created at Northwestern University. Stuart Bremer makes a significant advance by programming all aspects of the basic theory so that it more completely and accurately reflects the complexity of international relations in the real world. After describing the SIPER model, the author sets forth the values of the variables and parameters used for the twenty-four runs, including those that remained the same throughout and those that were varied. He then undertakes to validate the model by determining the extent to which the simulated nations behave like real world nations and simulated international systems like real international systems. In conclusion, he assesses the model's strengths and weaknesses and points to possible future improvements. Originally published in 1977. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

Systems, decisions, and models. Simulation and symbolic models of dynamic systems. Simulation methodology. Model building and use. Developing the simulation model and program. Simulation languages. Model design; Analyzing a simulation run. Experimental optimization. A simulation model a computer center's operations. Simulation models of human behavior. The future of simulation.

This is a collection of independent works on the GLOBUS model. A first and basic application of the GLOBUS model was made through the computation of its standard run for the years 1970-2010. Stated in the simplest possible terms GLOBUS is a computer simulation model of many important macropolitical and macroeconomic relationships within and among 25 prominent contemporary nations plus a rest-of-world entity. It is designed and used to explore possible solutions to long-term global problems.

Many books instruct readers on how to use the tools of policy analysis. This book is different. Its primary focus is on helping readers to look critically at the strengths, limitations, and the underlying assumptions analysts make when they use standard tools or problem framings. Using examples, many of which involve issues in science and technology, the book exposes readers to some of the critical issues of taste, professional responsibility, ethics, and values that are associated with policy analysis and research. Topics covered include policy problems formulated in terms of utility maximization such as benefit-cost, decision, and multi-attribute analysis, issues in the valuation of intangibles, uncertainty in policy analysis, selected topics in risk analysis and communication, limitations and alternatives to the paradigm of utility maximization, issues in behavioral decision theory, issues related to organizations and multiple agents, and selected topics in policy advice and policy analysis for government.