Spatial microsimulation techniques have become an increasingly popular way to fulfil the need for generating small area … fundamental differences between the multiple data sources which spatial microsimulation techniques seek to combine. Using two … distributions for children are different in two Australian databases being combined within a spatial microsimulation model. We then …

Abstract Spatial microsimulation models typically match census of population data with survey data in order to simulate … synthetic populations of individuals and households within small-scale geographic areas. For most spatial microsimulation … presents a statistical matching approach for assigning simulated households from a spatial microsimulation model to unique …

In this paper, some vital methodological issues of spatial microsimulation modelling for small area estimation have … estimation have highlighted methodologies based on various statistical models and theories. However, spatial microsimulation …-based approaches, the spatial microsimulation model-based approaches can operate through reweighting techniques such as GREGWT and …

variables in two or more datasets. The farm level spatial microsimulation model developed in this paper uses one of many …

, the spatial distribution of individuals with depression is estimated at the small area, ED level using a spatial … microsimulation model. Finally, a spatial interaction model is used to analyse access to acute inpatient facilities at the national …

disaggregated data on individual earnings. Spatial microsimulation through a process of calibration provides a method which allows …

Abstract It has long been argued that spatial microsimulation models can be used to estimate the impact of major … have used SimLeeds, which is a spatial microsimulation model for the Leeds local labour market, in order to estimate the … multiplier effects at different localities within the city. This paper addresses all these multiplier effects in a spatial …