Handbook Of Microsimulation Modelling

Microsimulation Modelling involves the application of simulation methods to micro data for the purposes of evaluating the effectiveness and improving the design of public policy. The field has been applied to many different policies within both government and academia. This handbook describes and discusses the main issues within the field.

"The purpose of this book is to bring together for the first time a description, with examples, of the main methods used in microsimulation modelling, used in the field of income-distribution analysis. The book provides a practical complement to the Handbook of Microsimulation Modelling, published in 2014. It is structured to develop and use the different types of models used in the field, with a focus on household-targeted policy. The book aims to fill a gap in the literature in providing a greater degree of codified knowledge through a practical guide to developing and using microsimulation models. At present, the training of researchers and analysts that use and develop microsimulation modelling is done on a relatively ad-hoc basis through occasional training programmes and lecture series, built around lecture notes. This book would enable a more formalized and organized approach. Each chapter addresses a separate modelling approach in a similar, consistent way, describing in practical terms the key methodological skills for each approach: · It provides some policy context to each modelling approach so as to understand the modelling choices made and structures developed. · As a very data-intensive modelling approach, each chapter describes key data analysis and data-preparation methods. · As a modelling approach that is used extensively for deciding policy, often involving huge budgets, validation is key. Each chapter describes an approach to validating the model. · Depending upon the policy context, the analysis is assessed in different ways. Each chapter contains a section devoted to measurement issues and tabulating output from the models. · Last, each chapter contains an example simulation of a policy analysis using the chapter's methodological approach"--Publisher's description.

'Practical Microsimulation Modelling' brings together a description and examples of the main methods used in microsimulation modelling used in the field of income distribution analysis. It is structured to develop and use the different types of models used in the field, with a focus on household targeted policy.

This book is a practical guide on how to design, create and validate a spatial microsimulation model. These models are becoming more popular as academics and policy makers recognise the value of place in research and policy making. Recent spatial microsimulation models have been used to analyse health and social disadvantage for small areas; and to look at the effect of policy change for small areas. This provides a powerful analysis tool for researchers and policy makers. This book covers preparing the data for spatial microsimulation; a number of methods for both static and dynamic spatial microsimulation models; validation of the models to ensure the outputs are reasonable; and the future of spatial microsimulation. The book will be an essential handbook for any researcher or policy maker looking to design and create a spatial microsimulation model. This book will also be useful to those policy makers who are commissioning a spatial microsimulation model, or looking to commission work using a spatial microsimulation model, as it provides information on the different methods in a non-technical way.

Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata. Along with describing the necessary theories and their advantages and limitations, the authors illustrate the practical application of the techniques to a large number of substantive problems, including how to build up models, organize and link data, create synthetic microdata, conduct analyses, yield informative tables and graphs, and evaluate how the findings effectively support the decision making processes in government and non-government organizations. Features Covers both theoretical and applied aspects for real-world comparative research and regional statistics production Thoroughly explains how microsimulation modeling technology can be constructed using available datasets for reliable small area statistics Provides SAS codes that allow readers to utilize these latest technologies in their own work. This book is designed for advanced graduate students, academics, professionals and applied practitioners who are generally interested in small area estimation and/or microsimulation modeling and dealing with vital issues in social and behavioural sciences, applied economics and policy analysis, government and/or social statistics, health sciences, business, psychology, environmental and agriculture modeling, computational statistics and data simulation, spatial statistics, transport and urban planning, and geospatial modeling. Dr Azizur Rahman is a Senior Lecturer in Statistics and convenor of the Graduate Program in Applied Statistics at the Charles Sturt University, and an Adjunct Associate Professor of Public Health and Biostatistics at the University of Canberra. His research encompasses small area estimation, applied economics, microsimulation modeling, Bayesian inference and public health. He has more than 60 scholarly publications including two books. Dr. Rahman’s research is funded by the Australian Federal and State Governments, and he serves on a range of editorial boards including the International Journal of Microsimulation (IJM). Professor Ann Harding, AO is an Emeritus Professor of Applied Economics and Social Policy at the National Centre for Social and Economic Modelling (NATSEM) of the University of Canberra. She was the founder and inaugural Director of this world class Research Centre for more than sixteen years, and also a co-founder of the International Microsimulation Association (IMA) and served as the inaugural elected president of IMA from 2004 to 2011. She is a fellow of the Academy of the Social Sciences in Australia. She has more than 300 publications including several books in microsimulation modeling.

This book, which is the first to be published in the emerging field of farm-level microsimulation, highlights the different methodological components of microsimulation modelling: hypothetical, static, dynamic, behavioural, spatial and macro–micro. The author applies various microsimulation-based methodological tools to farms in a consistent manner and, supported by a set of Stata codes, undertakes analysis of a wide range of farming systems from OECD countries. To these case studies, O’Donoghue incorporates farming policies such as CAP income support payments, agri-environmental schemes, forestry planting incentives and biomass incentives – in doing so, he illuminates the merits of microsimulation in this environment.

The use of simulation modeling and analysis is becoming increasingly more popular as a technique for improving or investigating process performance. This book is a practical, easy-to-follow reference that offers up-to-date information and step-by-step procedures for conducting simulation studies. It provides sample simulation project support materi

Introduces various modeling and simulation methods and paradigms that are used to explain and solve the predominant challenges facing society Handbook of Real-World Applications in Modeling and Simulation provides a thorough explanation of modeling and simulation in the most useful, current, and predominant applied areas of transportation, homeland security, medicine, operational research, military science, and business modeling. Offering a cutting-edge and accessible presentation, this book discusses how and why the presented domains have become leading applications of modeling and simulation techniques. Contributions from leading academics and researchers integrate modeling and simulation theories, methods, and data to analyze challenges that involve technological and social issues. The book begins with an introduction that explains why modeling and simulation is a reliable analysis assessment tool for complex systems problems. Subsequent chapters provide an orientation to various modeling and simulation methods and paradigms that are used to explain and solve the predominant challenges across real-world applied domains. Additionally, the handbook: Provides a practical one-stop reference on modeling and simulation and contains an accessible introduction to key concepts and techniques Introduces, trains, and prepares readers from statistics, mathematics, engineering, computer science, economics, and business to use modeling and simulation in their studies and research Features case studies that are representative of fundamental areas of multidisciplinary studies and provides a concise look at the key concepts of modeling and simulation Contains a collection of original ideas on modeling and simulation to help academics and practitioners develop a multifunctional perspective Self-contained chapters offer a comprehensive approach to explaining each respective domain and include sections that explore the related history, theory, modeling paradigms, and case studies. Key terms and techniques are clearly outlined, and exercise sets allow readers to test their comprehension of the presented material. Handbook of Real-World Applications in Modeling and Simulation is an essential reference for academics and practitioners in the areas of operations research, business, management science, engineering, statistics, mathematics, and computer science. The handbook is also a suitable supplement for courses on modeling and simulation at the graduate level.