Defining Demographic Change in Locational Planning Problems
AbstractSince population, which actually represents demand in any organised or rearranged service system, is the final target and recipient of every planning strategy or policy action, the success of locational analysis and the locational planning process, is largely determined upon the decision makers' ability to estimate the study area's future population size and distribution. Such estimations can be demographically achieved through the analysis and extrapolation into the future of carefully measured birth, death and migration rates according to observed trends and tendencies of the relevant socio-economic factors that affect them. As opposed to traditional generalisations and recent practices, which deal with population as a whole, the approach presented in this paper focuses on each individual's attitude towards the issue of intended births, which when aggregated formulate a fertility rate. More specifically, certain socio-economic characteristics, based on questionnaire data, are analysed using discrete choice models in order to estimate the prospective family-size desires. In this respect, a birth-rate choice model is derived through the assessment of the expected number of children to be born in a household during a specific time period and with regard to its socio-economic identity. Moreover, modifications of the above characteristics generate alternative family-size scenarios and thus differing population forecasts, which in turn can lead to unforeseen solution strategies and thus a more sophisticated and pragmatic decision-making process when dealing with facility-location problems both in the public and the private sector.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 20757.
Date of creation: 1996
Date of revision: 1996
Publication status: Published in Proceedings of the 36th European Regional Science Association Congress 19.19(1996): pp. 352-373
Locational Planning; Discrete Choice models; Population Projections; Greece;
Find related papers by JEL classification:
- R53 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Public Facility Location Analysis; Public Investment and Capital Stock
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
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