Determination of the infrastructure needs for municipalities using an objective method

Nowadays, in Spain, the state of the infrastructure and equipment at different municipalities is estimated using indices, which are based on surveys. Thus, the level of need at each municipality is established depending on 14 individual indices, which are related to three facets: health, services, and leisure. With the aim of obtaining only one need ranking, these indicators define a general index, which is a weighted average. However, the weights are incoherent when the individual indices are related to the three facets. In this work, the use of the Rasch model as a measurement instrument is proposed. This alternative to the general index allows municipalities to discriminate in terms of the indices and vice versa. Thus, in an objective manner, a ranking of the municipalities according to their infrastructure needs and, moreover, a ranking of the more (or less) frequent needs for all municipalities can be determined. With this method, it is not necessary to employ previous weights that distort the original data. As an example, data relating to the municipalities of the province of Badajoz, Spain, have been processed. The results are in accordance with the initial hypothesis that the priority ranking of the individual indices for all municipalities are: first, health; second, services; and finally, leisure. Moreover, with the Rasch model measure, we have observed a general propensity of the studied municipalities to enjoy a good quality of life because there are no important infrastructure needs. Finally, a Geographical Information System (GIS) was used to carry out different analyses. Thus, when population and quality of life were jointly mapped, a relationship between the two variables was not observed. Abnormal values of the indices for the municipalities were also visualized. The use of the Rasch model plus a GIS is fundamental to developing an objective allocation of resources to improve the infrastructures of the municipalities.