A new classification of small island economies based on geography, demography and sovereignty

• Main Authors: Goujon, Michaël, Razafindravaosolonirina, Justinien
• Other Authors: Centre d'Études et de Recherches sur le Développement International (CERDI), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Centre d'Économie et de Management de l'Océan Indien (CEMOI), Université de La Réunion (UR)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2022
• Subjects: clustering; formal sovereignty index; principal component analysis; small island states; small island territories; sovereignty; [SHS]Humanities and Social Sciences; [SHS.GEO]Humanities and Social Sciences/Geography; [SHS.SCIPO]Humanities and Social Sciences/Political science; Alberti; Greenland; Nunavut; Pacific
• Online Access: https://uca.hal.science/hal-03826752; https://uca.hal.science/hal-03826752/document; https://uca.hal.science/hal-03826752/file/A_new_classification_of_small_island_economies_based_on_geography_demography_and_sovereignty.pdf

International audience We explore and use correlations (not causations) between geographic and demographic characteristics and current levels of sovereignty in order to propose a new classification of small, island and coastal territories. While previous analyses mostly rely on descriptive statistics between the group of UN-members and subnational jurisdictions, we take advantage of a "formal sovereignty" index developed by Alberti and Goujon (2020) that provides a continuous and multidimensional measure of sovereignty or autonomy for a sample of 100 small island states and coastal/island territories. Huge heterogeneity within such a sample leads us to use a data-driven method of principal component analysis and clustering in order to secure a multidimensional typology of small islands relative to their main geographic and demographic characteristics and their level of sovereignty. The PCA results show that heterogeneity is firstly explained by a combination of geographic and demographic variables, and secondly by sovereignty, associated (positively) with population size and (negatively) with insularity. The clustering analysis leads to divide the 100 territories into four clusters mainly characterized by, respectively: Group 1 (32 territories): high sovereignty associated with a large population; Group 2 (26 territories): high values of latitude and life expectancy (mostly Atlantic and Baltic territories); Group 3 (40 territories): large distance to metropolitan power and high insularity (Pacific Regions); and Group 4: Greenland and Nunavut, two territories with a large land area, high latitude, low populations and large EEZ surface area.