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    Projecting population and labour market trends in rural areas.

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    Author
    Wiemers, Emily
    Commins, Patrick
    Pitts, Eamonn
    Ballas, Dimitris
    Clarke, Graham
    Keyword
    Spatial microsimulation model
    Labour market
    SMILE
    population
    Date
    2002-12-01
    
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    URI
    http://hdl.handle.net/11019/1234
    Citation
    Wiemers, E., Commins, P., Pitts, E., Ballas, D., Clarke, G., Projecting population and labour market trends in rural areas, End of Project Report, Teagasc, 2002.
    Abstract
    This purpose of this project is to develop a spatial model to project population and labour market variables at the small area level in Ireland. The model is called SMILE (Simulation Model for the Irish Local Economy) and is a static and dynamic spatial microsimulation model. Microsimulation attempts to describe economic and social events by modelling the behaviour of individual agents such as persons or firms. Microsimulation models have proved useful in evaluating the impact of policy changes at the micro level. Spatial microsimulation models contain information on geographic units and allow for a regional or local approach to policy analysis. SMILE is based on modelling work on urban systems and employs similar techniques for analysing rural areas. The static model creates a spatially referenced synthetic population of Ireland. Each individual enumerated in the 1991 Census of Population is synthetically constructed and is assigned 11 census characteristics including a District Electoral Division (DED) location. The dynamic element incorporated in SMILE ages the synthetic population by modelling demographic processes including fertility, mortality and internal migration. The dynamic process is used to project population in the medium term; it ages the synthetic 1991 population to 1996. For validation purposes, these 1996 projections are then compared to the 1996 Census of Population. The same process was used to project between the 1996 and the 2002 Census of Population. The results indicate that the accuracy at DED and county level is within acceptable limits. The model will be extended in the next three years, beginning in 2003, with additions including validating individual attributes such as employment status and social class and also including households in the model. This project has created a basic model that can be expanded and developed in the future.
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