Description
Table of Contents Preface Introduction Introduction Main Aims of the Book Guide for the Reader Concluding Remarks Small Area Estimation Introduction Small area estimation Advantages of small area estimation Why small area estimation techniques? Applications of small area estimation Approaches to small area estimation Direct estimation Horvitz-Thomposn (H-T) estimator Generalized regression (GREG) estimator Modified direct estimator Design-based model-assited estimators A comparison of direct estimators Concluding remarks Indirect Estimation: Statistical Approaches Introduction Implicit models approach Synthetic estimaton Composite estimation Demographic estimation Comparison of various implicit models based indirect estimation Explicit models approach Basic area level model Basic unit leve model General linear mixed model Comparison of various explicit models based indirect estimation Methods for estimating explicit models E-BLUP approach EB approach HB approach A comparison of three methods Concluding remarks Indirect Estimation: Geographic Approaches Introduction Microsimulation modeling Process of microsimulation Types of microsimulation models Advantages of microsimulation modeling Methodologies in microsimulation modeling technology Techniques for creating spatial microdata Statistical data matching or fusion Iterative proportional fitting Repeated weighting method Reweighting Combinatorial optimisation reweighing approach The simulated annealing method in CO An illustration of CO process for hypothetical data Reweighting: The GREGWT approach Theoretical setting How does GREGWT generate new weights? Explicit numerical solution for a hypothetical data A comparison between GREGWT and CO 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 moedling unobserved population units Concluding remarks Microsimulation Modelling Technology for Small Area Estimation Introduction Data sources and issues The Census Data Survey Datasets Survey Datasets MMT based Model Specification Model inputs Generating small area synthetic weights Model inputs Generating small area synthetic weights Model inputs Gnerating small area synthetic weights Model outputs Housing stress Definition Measures of housing stress A comparison of various measures Small area estimation of housing stress Inputs at the second stae model Final model outputs Concluding remarks Applications of the Methodologies Introduction Results of the model: A general view Model accuracy report Scenarios of housing stress under various measures Distribution of housing stress estimation Lorenz curve for housing stress estimates Proportional cumulative frequency graph and index of dissimilarity Scenarios of households and housing stress by tenures Estimation of households in housing stress by spatial scales Results for different states Results for various statistical divisions Results for various statistical subdivisions Small area estimates: Number of households in housing stress Estimated numbers of overall households in housing stress Estimated numbers of buyerhouseholds in housing stress Estimated numbers of public renter households in housing stress Estimated numbers of private renter households in housing stress Estimated numbers of total renter households in housing stress Small area estimates: Percentage of households in housing stress Percentage estimates of housing stress for overall households Percentage estimates of housing stress for buyer households Percentage estimates of housing stress for public renter households Percentage estimates of housing stress for private renter households Percentage estimates of housing stress for total renter households Concluding remarks Analysis of Small Area Estimates in Capital Cities Introduction Scenarios of the results for major capital cities Trends in housing stress for some major cities Mapping the estimates at SLA levels within major cities Sydney Housing stress estimates for overall households Small area estimation by household’s tenure types Melbourne Housing stress estimates for overall households Small area estimation by household’s tenure types Brisbane Housing stress estimates for overall households Small area estimation by household’s tenure types Adelaide Housing stress estimates for overall households Small area estimation by household’s tenure types Canberra Housing stress estimates for overall households Small area estimation by household’s tenure types Hobart Housing stress estimates for overall households Small area estimation by household’s tenure types Darwin Housing stress estimates for overall households Small area estimation by household’s tenure types Concluding remarks Validation and Measure of Statistical Reliability Introduction Some validation methods in the literature New approaches to validating housing stress estimation Statistical significance test of the MMT estimates Results of the statistical significance test Absolute standardised residual estimate (ASRE) analysis Results from the ASRE analysis Measure of statistical reliability of the MMT estimates Confidence interval estimation Results from the estimates of confidence intervals Concluding remarks Conclusions and Computing Codes Introduction Summary of major findings Limitations Areas of further studies Computing codes and programming The general model file codes SAS programming for reweithing algorithms The second stage program file codes Concluding remarks Appendices.
