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Developing a Continuous Space Representation of a Simulated Population

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dc.contributor.author Cullinan, John en
dc.date.accessioned 2011-01-21T14:54:39Z en
dc.date.available 2011-01-21T14:54:39Z en
dc.date.issued 2010-09-03 en
dc.identifier.citation Cullinan, J. Developing a Continuous Space Representation of a Simulated Population. Spatial Economic Analysis, 5(3), 317 - 338. en
dc.identifier.uri http://hdl.handle.net/10379/1551 en
dc.description.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 applications this level of spatial precision is satisfactory. For others, more precise information on the location of simulated units may be required. To this end this paper develops a continuous space representation of a simulated population. It presents a statistical matching approach for assigning simulated households from a spatial microsimulation model to unique spatially-referenced residential locations. The allocation is based on a random assignment after splitting the simulated households into two groups: those predicted to reside in apartments and those predicted to reside in houses. The resulting 'geohouseholds' have a range of potential applications in economic and spatial analysis. en
dc.format application/pdf en
dc.publisher Taylor & Francis en
dc.subject Spatial microsimulation en
dc.subject Statistical matching en
dc.subject Spatial analysis en
dc.subject Recreation demand modelling en
dc.subject Irish Centre for Social Gerontology en
dc.title Developing a Continuous Space Representation of a Simulated Population en
dc.type Article en
dc.local.publishedsource http://www.informaworld.com/10.1080/17421772.2010.493954 en
dc.description.peer-reviewed peer-reviewed en
dc.contributor.funder Walsh Fellowship Scheme (Teagasc) en

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