Validation and creation of the statistical reliability of small area estimates by microsimulation modelling is challenging due to the fact that the estimated data are typically unavailable from another source for the small areas. The literature suggest few methods including aggregating the small area estimates up to larger levels where reliable data are available to compare the results with the attempt of adopting alternative methods to determine the accuracy of the model (e.g. Tanton et al., 2014; Timmins and Edwards, 2016; Rahman and Harding, 2016; Whitworth et al., 2016). Bootstrapping approaches (Efron and Tibshirani, 1993; Steyerberg et al., 2003) can be another choice for validation of the estimates for small areas with smaller populations. Although bootstrapping is based on re-sampling technique, and widely used as methods of validating statistical prediction models (Gerds, et al., 2008; Kopec et al., 2010), bootstrapping approaches have not, to our knowledge, been applied to validate spatial microsimulation models. This research aims to introduce bootstrapping methodologies in calculating statistical reliability measures for small area estimates from a spatial microsimulation model in Australia. An empirical application demonstrates that the bootstrapping approaches seem most meaningful systems for validation of the spatial microsimulation model for those areas with smaller populations. Some key advantages of such methods are also explored.
Original languageEnglish
Number of pages2
Publication statusPublished - 2017
Event6th World Congress of the International Microsimulation Association: IMA 2017 - Collegio Carlo Alberto, Moncalieri, Italy
Duration: 21 Jun 201723 Jun 2017
http://www.carloalberto.org/ima-2017/ (Conference website)


Conference6th World Congress of the International Microsimulation Association
OtherThe 6th World Congress of the International Microsimulation Association (IMA 2017) will take place at the Collegio Carlo Alberto in Moncalieri, Italy from Wednesday, June 21 through Friday, June 23, 2017. We encourage submissions in the fields (broadly defined) of microsimulation, agent based modelling and computational methods.
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