CLUSTER ANALYSIS OF COST LIVING DATA IN EUROPE

Abstract

There are a lot of studies, research, summaries, reports, and articles on the cost of living in different cities around the world. Although these studies are rich and powerful, only final results are published, such as city rankings, or summaries of the most important and least ranked cities. This paper aims to study the most livable cities in Europe using the cluster analysis of cost-of-living price data for the year 2019. I will apply the method of grouping according to similarities or differences in distance and cluster analysis algorithms, as there are many methods of cluster clustering and they are technical or an algorithm (Linking), where the results are different using the most common linking methods to draw the dendrogram, namely: the minimum or individual linking, the maximum or full linking, average or average linking, where we will notice that cities can cluster in a different cluster according to the method of linking, and the geographical location, Where this type of block analysis is done to help companies or even people determine which city to move to reduce the cost of living. Where it is important to avoid making the wrong decision in case of changing the next block for a specific city. The results allow us to describe the similarities and differences in the price structure of products and services in different cities and European countries. The results of the analysis showed that there are some similarities in the cost of living in some European countries and grouping them into one cluster, taking into account the difference in their geographical location. This indicates that the composition of the clusters depends on the method of linking in the analysis. These results can be used by individuals or institutions to choose the best European countries to live by comparing the cost of living in them compared to the available budget.