Application of Statistical Visualization Tools on Global Competitiveness Data

Many global organizations provide valuable sources of country-specific data to the general public. The data are a very good source of secondary information to the global firms making country entry decisions as well as providing input to the policy makers in the international organizations and the country governments. One such organization is the World Economic Forum disseminating the results of a global competitiveness study every year. The Global Competitiveness Index (GCI) focuses on 12 variables that are deemed to be important for the country's competitiveness and hence suitability for investment. The coverage of the GCI has been increasing over the years. The latest report (2012-2013) carries data on 144 countries. With the amount of data increasing it becomes important to summarize the intrinsic elements with the use of visual tools. Multivariate statistical tools could summarize vast amounts of data while retaining the critical pieces of information and the interdependencies between the variables and the objects. This chapter demonstrates the use of two such techniques, namely Cluster Analysis and Multidimensional Scaling (MDS) on the World Economic Forum 2012-2013 Global Competitiveness data.