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dc.contributor.authorRamilan, Thiagarajah
dc.contributor.authorScrimgeour, Frank
dc.contributor.authorMarsh, Dan
dc.date.accessioned2012-04-20T03:02:37Z
dc.date.available2012-04-20T03:02:37Z
dc.date.copyright2011-11-29
dc.date.issued2011
dc.identifier.citationRamilan, T., Scrimgeour, F. & Marsh, D. (2011). Using microsimulation to maximise scarce survey data: applications for catchment scale modelling and policy analysis. Environmental Modeling & Assessment, available online 29 November 2011.en_NZ
dc.identifier.urihttps://hdl.handle.net/10289/6237
dc.description.abstractMicrosimulation can be used to extend the use of scarce survey resources by creating simulated populations whose characteristics are close to those of the real population. The technique involves merging detailed survey observations with variables from more extensive data sets in order to create a simulated population. We illustrate how microsimulated data enable analysis of the economic and environmental impact of different policies on a catchment for which detailed farm level data was unavailable. Use of microsimulation for agri-environmental policy analysis is applicable to diverse problems from simulation of nitrogen trading to modelling of agent response to policy shocks. Scale flexibility is easily implemented since data can be aggregated or disaggregated to the preferred scale. Simulated catchment data allows better understanding of the effects of policies on different types of farm and should be extremely valuable to organisations that want to minimise the economic impact of environmental policies.en_NZ
dc.language.isoen
dc.publisherSpringeren_NZ
dc.relation.ispartofEnvironmental Modeling & Assessment
dc.relation.urihttp://www.springerlink.com/content/k87kx42401186045/en_NZ
dc.subjectfarm surveyen_NZ
dc.subjectmicrosimulationen_NZ
dc.subjectenvironmental policyen_NZ
dc.subjectstatistical matchingen_NZ
dc.subjectNew Zealanden_NZ
dc.titleUsing Microsimulation to Maximise Scarce Survey Data: Applications for Catchment Scale Modelling and Policy Analysisen_NZ
dc.typeJournal Articleen_NZ
dc.identifier.doi10.1007/s10666-011-9300-4en_NZ
dc.relation.isPartOfEnvironmental Modeling & Assessmenten_NZ
pubs.begin-page399en_NZ
pubs.elements-id36828
pubs.end-page410en_NZ
pubs.issue4en_NZ
pubs.volume17en_NZ


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