Small Area Estimation and Microsimulation Modeling: 1st Edition (Paperback) book cover

Small Area Estimation and Microsimulation Modeling

1st Edition

By Azizur Rahman, Ann Harding

Chapman and Hall/CRC

521 pages | 70 B/W Illus.

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Description

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.

Reviews

"The book aims at introducing modern statistical small area estimation methodologies into the framework of spatial microsimulation modelling for a comprehensive presentation, providing a novel approach with much potential in comparative social research and regional statistics production. In my opinion, the strongest methodological developments are in the techniques of generating synthetic spatial microdata at small area levels. This book will be attractive for students, in economics, social sciences and statistics in particular. The increasing use of both SAE and microsimulation methods in different areas of society, such as social planning by government institutions and official or public statistics production by national and international statistical agencies. Finally, I want to congratulate the authors for writing a nice and well readable book on a quite complicated topic."

~Prof. Risto Lehtonen, University of Helsinki

". . .an interesting read for both beginning and more experienced microsimulation modellers. The two authors are well known within the microsimulation community. In this book, they share their experiences and insights into both the more theoretical and empirical aspects of microsimulation modelling. Across disciplines, there are several approaches towards the simulation or projection of small area statistics. However, since these different disciplines make use of different terminologies, there is less cross-pollination than expected (or hoped for). The aim of this book is to show and explain different approaches of small area estimation that are used in different research fields. The book gives an extensive theoretical and empirical overview of different microsimulation techniques and can be of relevance to researchers who want to expand their knowledges on ways to estimate small area characteristics."

~International Journal of Microsimulation

"The authors begin with a detailed classification tree of small area estimation techniques. The text then proceeds to review and describe these techniques. A familiarity with regression techniques and survey methods is assumed throughout. The text then proceeds to present some new small area estimation techniques, validation methods, and a detailed worked example. The appendices provide further details of the worked example and SAS code for the generalized regression weighting tool (GREGWT) method."

~Douglas Dover, International Society for Clinical Biostatistics

Table of Contents

Introduction

Introduction

Main Aims of the Book

Guide for the Reader

Concluding remarks

Small Area Estimation

Introduction

Small area estimation

Approaches to small area estimation

Direct estimation

Concluding remarks

Indirect Estimation: Statistical Approaches

Introduction

Implicit models approach

Explicit models approach

Methods for estimating explicit models

A comparison of three methods

Concluding remarks

Indirect Estimation: Geographic Approaches

Introduction

Microsimulation modelling

Methodologies in microsimulation modelling technology

Combinatorial optimisation reweighting approach

Reweighting: The GREGWT approach

A comparison between GREGWT and CO 87

Concluding remarks

Bayesian Prediction-Based Microdata Simulation

Introduction

The basic steps

The Bayesian prediction theory

The multivariate model

The prior and posterior distributions

The linkage model

Prediction for modelling unobserved population units

Concluding remarks

Microsimulation Modelling Technology for Small Area Estimation

Introduction

Data sources and issues

MMT-Based Model Specification

Housing stress

Small area estimation of housing stress

Concluding remarks

Applications of the Methodologies

Introduction

Results of the model: A general view

Estimation of households in housing stress by spatial scales

Small area estimates: Number of households in housing stress

Small area estimates: Percentage of households in housing stress

Concluding remarks

Analysis of Small Area Estimates in Capital Cities

Introduction

Sydney

Melbourne

Brisbane

Perth

Adelaide

Canberra

Hobart

Darwin

Concluding remarks

Validation and Measure of Statistical Reliability

Introduction

Some validation methods inthe literature

New approaches to validating housing stress estimation

Measure of statistical reliability of the MMT estimates

Concluding remarks

Conclusions and Computing Codes

Introduction

Summary of major findings

Limitations

Areas offurther studies

Computing codes and programming

Concluding remarks

References

Appendices

About the Authors

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.

Subject Categories

BISAC Subject Codes/Headings:
MAT029000
MATHEMATICS / Probability & Statistics / General
REF000000
REFERENCE / General