Einar Holm

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Att lokalisera utbildning, sysselsättning och boende

IN THIS STUDY methods are developed for locating places of education, employment opportunities and housing.The first model allocates places for upper secondary (Am. High School) education in space with the aid of a location-allocation model using capacity constraints and distance-dependent demand. The solution is obtained by an heuristic node-swapping method. For each line of study it sets down the number of locations that could offer such courses, their physical location, their capacities and their geographical catchment areas. The educational resources are allocated according to a criteria that minimizes a weighted sum of geographical distances between the schools and their potential pupils, their applicants and the labour market. In connection with applications of the model, analyses suggest that the location and dimensioning of upper secondary education are primarily steered by the local pupil demand, secondly by the desire for an even regional allocation and thirdly by the demand from the local labour market.In the second model, government employment programmes are allocated among sectors of the economy and sub-districts within a municipality over time. The aim is to offer a sufficient number of employment opportunities for the lowest possible level of public expenditure - irrespective of which support sectors happened to have resources at their disposal at the time of investigation. Given frequencies of persons employed are sought for various groups of people, e.g. men, women, or peripheral residents in the municipality. One general result is that the existing allocation of support resources on sectors only yields less than half as many employment opportunities as could be provided with the same resource input allocated in a different way. Even with a more efficent resource allocation, the amount of support needs to be at least doubled in order to produce national average levels of employment over the long term, within the studied municipality.The third model represents a local housing market with a varying housing stock and population. The changes of accommodation are described for the individual households, giving information on preferences and restrictions. A large proportion of home moves are due to changes in the household composition, changes which are explained internally within the model. The model shows how the new production of housing should be distributed by types of dwelling in different geographically delimited areas over time. The individual's welfare losses during the wait for a new place to live and the costs of empty accommodation are weighed against each other in the allocation algorithm of the model. The model is qualitatively different from traditional models using aggregated data. However models with data on individuals, individual decision processes, and interplay between different actors can probably be developed into usable bases for decision.