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Modelling the Socio-economic Impacts of Major Job Loss or Gain at the Local Level: a Spatial Microsimulation Framework

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  • Dimitris Ballas
  • Graham Clarke
  • John Dewhurst

Abstract

Abstract It has long been argued that spatial microsimulation models can be used to estimate the impact of major changes in the local labour market through job losses or gains, including local multiplier effects. In a previous paper we have used SimLeeds, which is a spatial microsimulation model for the Leeds local labour market, in order to estimate the initial employment and income effect of a hypothetical closure of an engineering plant on different surrounding localities. This paper builds on that work and presents an extension of SimLeeds in order to provide estimates for the multiplier effects of such major changes in a local economy. In particular, we focus on the spatial distribution of the multiplier effects such as the event changes that are triggered by initial job and income effects. The disposable income gain or loss for each individual or household eventually leads to the increase/decrease of consumption of goods and services and to possible changes of the preferred retail location etc. (i.e. moving to more/less expensive stores). There are also net monetary losses for the government from the increase/decrease of income tax revenue and from the decrease/increase of the benefit claims from the households affected. In addition, the initial income and employment impacts would have second- and third-round multiplier effects, which could include the openings/closures of local convenience grocery stores as a result of the rise/fall of local demand for their goods. These closures in turn would generate further job creation or loss, which would have further multiplier effects at different localities within the city. This paper addresses all these multiplier effects in a spatial microsimulation context and provides a new framework for multiplier-effect micro-spatial analysis. RÉSUMÉ Modélisation des Effets Socio-économiques d'une Perte ou d'un Gain Important d'Emploi sur le plan Local: un Cadre Spatial de Micro SimulationOn a longtemps discuté du fait qu'on pouvait utiliser les modèles spatiaux de micro simulation dans l’évaluation des effets des variations importantes, affectant le marché du travail local, par le biais de pertes ou de créations d'emploi, et dans l’évaluation des effets multiplicateurs locaux dans l'analyse. Dans un article précédent, nous avons utilisé SimLeeds, modèle de micro simulation pour le marché du travail de Leeds, dans le but d’évaluer l'effet de la fermeture hypothétique d'une usine sur l'emploi et les revenus dans les différentes localités environnantes. L'article s'appuie sur ce travail et présente une extension de SimLeeds pour fournir des estimations des effets multiplicateurs, générés par des variations importantes, affectant une économie locale. En particulier, nous nous sommes intéressés à la distribution spatiale des effets multiplicateurs, par exemple, les changements provoqués par les modifications initiales, qui ont touché l'emploi et les revenus. Le revenu disponible en plus ou en moins pour chaque ménage entraîne en définitive une augmentation/diminution de la consommation des biens et services et peut amener les ménages à s'approvisionner ailleurs. (par exemple, s'approvisionner dans des magasins plus ou moins chers). Il y a aussi des pertes sèches pour le gouvernement du fait de l'augmentation/diminution de la rentabilité de l'impôt sur le revenu et du fait de l'augmentation/diminution de la base imposable des ménages affectés. De plus, les modifications initiales affectant le revenu et l'emploi auront des effects multiplicateurs de seond et de troisième rang, au nombre desquels on pourra ranger l'ouverture/la fermeture d’épiceries locales. C'est la demande locale, en hausse ou en baisse, qui provoquera les ouvertures/fermetures. Ces fermetures provoqueront à leur tour des créations ou suppressions d'emploi, qui auront donc comme conséquences des effects multiplicateurs supplémentaires sur les différentes localités composant la ville. Cet article explique tous ces effets multiplicateurs dans un contexte spatial de micro simulation, et donne un nouveau cadre à l'analyse micro spatiale des effets multiplicateurs. RESUMEN Modelo de impactos socioeconómicos de pérdida o ganancia de empleo importante en un ámbito local: structura de microsimulación espacialDesde hace tiempo se sostiene que los modelos de microsimulación espacial pueden utilizarse para calcular el impacto de los principales cambios en el mercado laboral de ámbito local mediante las pérdidas y ganancias de empleo, incluyendo los efectos multiplicadores locales. En un ensayo anterior utilizamos SimLeeds, que es un modelo de microsimulación espacial para el mercado laboral en Leeds, a fin de calcular el efecto inicial de un cierre hipotético de una planta de ingeniería en el empleo y los ingresos en diferentes localidades de la zona. Nos basamos en ese trabajo y presentamos una ampliación de SimLeeds a fin de ofrecer los cálculos para los efectos multiplicadores de tales cambios principales en una economía local. En particular nos enfocamos en la distribución espacial de los efectos multiplicadores como los cambios de eventos que son desencadenados por los efectos iniciales en el trabajo y los ingresos. La ganancia o pérdida de ingresos disponibles para cada individuo o familia conduce con el tiempo a un aumento o una disminución del consumo de bienes y servicios y a posibles cambios de la ubicación minorista favorita, etc. (es decir, a desplazarse a almacenes más caros o baratos). También existen las pérdidas monetarias netas para el gobierno debido al aumento o la disminución de los impuestos sobre la renta y al aumento o la disminución del número de solicitudes de prestaciones para las familias afectadas. Además, los impactos iniciales en los ingresos y el empleo tendrían efectos multiplicadores de segunda y tercera ronda que podría incluir la apertura o el cierre de tiendas de alimentación locales como resultado de ese aumento/descenso de la demanda local de bienes. Estos cierres generarían a su vez otra creación o pérdida de trabajo que tendrían otros efectos multiplicadores en diferentes lugares de una misma ciudad. En este ensayo abordamos estos efectos multiplicadores en un contexto de microsimulación espacial y ofrecemos una nueva estructura para el análisis micro espacial del efecto multiplicador.

Suggested Citation

  • Dimitris Ballas & Graham Clarke & John Dewhurst, 2006. "Modelling the Socio-economic Impacts of Major Job Loss or Gain at the Local Level: a Spatial Microsimulation Framework," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(1), pages 127-146.
  • Handle: RePEc:taf:specan:v:1:y:2006:i:1:p:127-146
    DOI: 10.1080/17421770600697729
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    References listed on IDEAS

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    1. John Tomaney & Andy Pike & James Cornford, 1999. "Plant Closure and the Local Economy: The Case of Swan Hunter on Tyneside," Regional Studies, Taylor & Francis Journals, vol. 33(5), pages 401-411.
    2. Merz, Joachim, 1991. "Microsimulation -- A survey of principles, developments and applications," International Journal of Forecasting, Elsevier, vol. 7(1), pages 77-104, May.
    3. A. W. Coats, 1996. "Introduction," History of Political Economy, Duke University Press, vol. 28(5), pages 3-11, Supplemen.
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    Citations

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    Cited by:

    1. Eveline S. van Leeuwen, 2010. "The effects of future retail developments on the local economy: Combining micro and macro approaches," Papers in Regional Science, Wiley Blackwell, vol. 89(4), pages 691-710, November.
    2. Mark Birkin & Graham Clarke, 2012. "The enhancement of spatial microsimulation models using geodemographics," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 49(2), pages 515-532, October.
    3. Azizur Rahman & Ann Harding & Robert Tanton & Shuangzhe Liu, 2010. "Methodological Issues in Spatial Microsimulation Modelling for Small Area Estimation," International Journal of Microsimulation, International Microsimulation Association, vol. 3(2), pages 3-22.
    4. Malcolm Campbell & Dimitris Ballas, 2013. "A spatial microsimulation approach to economic policy analysis in Scotland," Regional Science Policy & Practice, Wiley Blackwell, vol. 5(3), pages 263-288, August.
    5. Ann Harding & Robert Tanton, 2014. "Policy and people at the small-area level: using micro-simulation to create synthetic spatial data," Chapters,in: Handbook of Research Methods and Applications in Spatially Integrated Social Science, chapter 25, pages 560-586 Edward Elgar Publishing.
    6. Marta Yánez Contreras & Marta Yánez Contreras, 2010. "El mercado laboral desde una perspectiva espacial," REVISTA APUNTES DEL CENES, UNIVERSIDAD PEDAGOGICA Y TECNOLOGICA DE COLOMBIA, September.
    7. Cathal O'Donoghue & Karyn Morrissey & John Lennon, 2014. "Spatial Microsimulation Modelling: a Review of Applications and Methodological Choices," International Journal of Microsimulation, International Microsimulation Association, vol. 7(1), pages 26-75.

    More about this item

    Keywords

    Spatial microsimulation; small-area microdata; small-area income data; multiplier effects; socio-economic impact assessment; R; R2; C61;

    JEL classification:

    • R2 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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