Small area estimation and microsimulation modelling

Content: 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 IntroductionImplicit 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 87Concluding remarksBayesian Prediction-Based Microdata SimulationIntroduction 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 remarksMicrosimulation Modelling Technology for Small Area EstimationIntroduction Data sources and issuesMMT-Based Model SpecificationHousing stressSmall area estimation of housing stressConcluding remarksApplications of the Methodologies Introduction Results of the model: A general viewEstimation of households in housing stress by spatial scalesSmall area estimates: Number of households in housing stressSmall area estimates: Percentage of households in housing stressConcluding remarks Analysis of Small Area Estimates in Capital Cities IntroductionSydney Melbourne Brisbane Perth AdelaideCanberra Hobart Darwin Concluding remarks Validation and Measure of Statistical Reliability Introduction Some validation methods in the literatureNew approaches to validating housing stress estimationMeasure of statistical reliability of the MMT estimatesConcluding remarks Conclusions and Computing Codes Introduction Summary of major findings Limitations Areas offurther studies Computing codes and programming Concluding remarksReferencesAppendices