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Forecasting Population Changes and Service Requirements in the Regions: A Study of Two Regional Councils in Queensland, Australia

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  • Wasantha Athukorala

    (School of Economics and Finance, Faculty of Business, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia)

  • Clevo Wilson

    (School of Economics and Finance, Faculty of Business, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia. Email: clevo.wilson@qut.edu.au.)

  • Prasad Neelawela

    (School of Economics and Finance, Faculty of Business, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia. Email: clevo.wilson@qut.edu.au.)

  • Evonne Miller

    (School of Design, Faculty of Built Environment and Engineering, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia.)

  • Tony Sahama

    (Tony Sahama, Faculty of Science and Technology, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia. Email: t.sahama@qut.edu.au)

  • Peter Grace

    (School of Natural Resource Sciences, Faculty of Science, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia.)

  • Mike Hefferan

    (School of Management, University of the Sunshine Coast, Australia)

  • Premawansa Dissanayake

    (Institute of Sustainable Resources, Faculty of Science and Technology, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia.)

  • Oshan Manawadu

    (Faculty of Science and Technology, Queensland University of Technology, GPO Box 2434, Brisbane QLD 4001, Australia.)

Abstract

Forecasting population growth to meet the service needs of a growing population is a vexed issue. The task of providing essential services becomes even more difficult when future population growth forecasts are unavailable or unreliable. The aim of this paper is to identify the main methods used in population forecasting and thereby select an approach to demonstrate that such forecasting can be undertaken with certainly and transparency, barring exogenous events. We then use the population forecasts to plan for service needs that arise from changes in population in the future. Interestingly, although there are techniques available to forecast such future population changes and much of this forecasting occurs, such work remains somewhat clouded in mystery. We strive to rectify this situation by applying an approach that is verifiable, transparent, and easy to comprehend. For this purpose we select two regional councils in Queensland, Australia. The experience derived from forecasting shows that forecasts for service needs of larger populations are more easily and accurately derived than for smaller populations. Hence, there is some evidence, at least from a service provision point of view, to justify the benefits of council/municipality amalgamation in recent times in Australia and elsewhere. The methodology used in this paper for population forecasting and the provision of service needs based on such forecasts will be of particular interest to policy decision-makers and planners.

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Bibliographic Info

Article provided by Queensland University of Technology (QUT), School of Economics and Finance in its journal Economic Analysis and Policy (EAP).

Volume (Year): 40 (2010)
Issue (Month): 3 (December)
Pages: 327-349

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Handle: RePEc:eap:articl:v:40:y:2010:i:3:p:327-349

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Postal: GPO Box 2434, BRISBANE QLD 4001
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Web page: http://www.journals.elsevier.com/economic-analysis-and-policy/
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Keywords: Regional Population forecasting; service provision; Box-Jenkins model;

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