Development status as a measure of development

Abstract

This study analyses to which extent the classification of countries as developing corresponds with their actual development level. It tracks the evolution of the development status classification schemes (DSCSs) of international organisations over time, identifies three broad concepts of a developing country, based on the social sciences literature, and analyses the degree of correspondence between classifications and concepts, based on eight indicators. The results suggest that development status is a fairly accurate measure of development. All DSCSs strongly correspond with all indicators analysed. Over time, the outcomes of DSCSs have become increasingly heterogeneous. As a result, different classification schemes match different concepts. Schemes of a first generation, which emerged before the 1990s, and which nominate countries for classes, correspond mainly with concepts focusing on difficult starting points or an early stage in systemic transition, whereas schemes of a second generation, set up in the 1990, which classify countries based on specified criteria, typically reflect a welfare-based concept. The paper argues that the growing heterogeneity of DSCSs and deficits in their documentation negatively impact on the quality of international official statistics. It makes proposals for the further development of DSCSs, also in the context of the 2030 Agenda for Sustainable Development.

Territorial Development as an Innovation Driver: A Complex Network Approach

“…, K, one can evaluate for each group the related mean µ c and variance σ 2 c . The definition of R is based on the fact [63] that the overall variance σ 2 can be viewes as composed of two positive contributions…”

Constructing a criteria-based classification for Small Island Developing States: An Investigation

“…Shorrock (2019) argues that a classi cation should pass the plausibility test of 'face validity', meaning it should make sense to the people who use it. The higher the congruence between the categories de ned in the classi cation system with people's ideas of those categories, the more the classi cation will make sense to users and the more easily it will be understood by them (Hoffmeister, 2020). But classi cation schemes also shape people's understanding of categories.…”

“…This is the reason why high incongruence between SIDS hampers productive discourse and scienti c progress (Neilsen, 2011). The "match between classi cations applied in statistics and concepts formed in people's minds constitutes an important determinant of the clarity, interpretability and relevance of aggregated or grouped data" (Hoffmeister, 2020(Hoffmeister, : 1098.…”

“…A further weakness is that the M49 classi cation itself is not criterion-based -there are no universally agreed concepts or de nitions to determine if a state is developing or not. So, although widely used, the M49 and the other development classi cations suffer from a lack of clarity with regard to their underlying rationale (Neilsen, 2011), as well as ambiguities and uncertainties regarding their actual meaning (Hoffmeister, 2020).…”

“…The World Bank provides a classi cation for 55 of the 63 possible SIDS . However, the World Bank themselves stopped using the 'development' classi cation in 2016 to avoid having to make such a distinction (Hoffmeister, 2020). The IMF also employs a broader measure of economic development that includes export diversi cation and the degree of integration into the global nancial system (IMF, 2020).…”