Annex B. Methodological notes

This annex provides an overview of the methodological notes for the data and evidence used in this report. Further information is available on the OECD’s States of Fragility platform at www3.compareyourcountry.org/states-of-fragility/about/0/.

Contexts referred to as “fragile contexts” are based on the OECD fragility framework, discussed below. Contexts referred to as “developing contexts” are based on the OECD DAC list of ODA Recipients (OECD, 2020[8]).

The OECD characterises fragility as the combination of exposure to risk and insufficient coping capacities of the state, system and/or communities to manage, absorb or mitigate those risks. The OECD multidimensional fragility framework, introduced in the 2016 edition of States of Fragility, measures fragility on a spectrum of intensity across five dimensions: economic, environmental, political, security and societal. It relies on a mixed methods approach that examines contexts within each dimension and then aggregates this information to obtain an overall picture of fragility.

The methodology is based a two-stage, principal components analysis (PCA), with a hierarchical clustering procedure to group contexts according to similar characteristics in each dimension. The foundation is 44 indicators derived from independent third-party data sources, all of which are recorded and explained in greater detail on the States of Fragility platform. Each of the five dimensions contains 8-12 indicators that are aggregated into principal components in the first stage PCA; the first two principal components in each dimension are used for the second stage PCA. The first principal component that results from this second-stage PCA represents the overall fragility score for each context. Based on this score, a context is classified as either fragile if its score is lower than -1.20 or extremely fragile if it is lower than -2.50. This analysis assesses fragility across 175 contexts for which sufficient data were available, as denoted by data being available for a context for at least 70% of indicators.

In Chapter 1 and Annex A, all figures representing regional or subregional fragility scores were calculated using a population-weighted average of all contexts within the respective region or subregion. Population statistics were sourced from UN DESA (2020[9]), with the latest year corresponding to the year 2019. Regional classifications were derived from the World Bank (2020[10]). Please note that in the radial graphs of each snapshot in Annex A, the indicators were scaled and adjusted to face the same direction, such that higher scores represent higher vulnerabilities (high risks/lower coping capacities).

An extensive discussion of this methodology is available in Annex A of the working paper accompanying this publication by Desai and Forsberg (2020[11]) and on the States of Fragility platform, including the step-by-step process for the PCA and hierarchical clustering procedure as well as the methodological notes and caveats regarding the data collected for the analysis. Additional information is available upon request.

Unless otherwise stated, all aid statistics cited in this report are deflated to USD constant (2018) and represented in USD million disbursements. They are sourced from the OECD aid statistics database (OECD, 2020[12]), specifically the DAC2a and Creditor Reporting System. Unless otherwise stated, statistics are deflated using the DAC total deflator (OECD, 2020[13]).

The sources of other financial statistics are cited in the text, using the most recent values, usually 2018. Due to data limitations, not all data are available for all contexts. Where values have been imputed, they use the latest available value or a simple average of the last three years, as indicated. In time series, projected values are identified with “p”, and estimates are identified with an “e”. Values after 2019 have not been deflated.

Violence comprises a broad range of actions, including among others sexual and gender-based violence, terrorism, armed conflict, and homicides. Categorisations of violence and violent deaths also vary and may differ based on norms, culture or definition in national and international law (Asylbek kyzy, Delgado and Milante, 2020[14]). The Global Registry of Violent Deaths categorises violent deaths in 16 different categories; intentional and unintentional homicides, killings in legal interventions, and direct conflict cause the largest numbers of deaths (Asylbek kyzy, Delgado and Milante, 2020[14]). In States of Fragility 2020, the primary focus is on violence in violent conflict, while recognising that all forms of violence contribute to fragility across multiple dimensions.

Also in States of Fragility 2020, violent conflict refers to all state-based (both intrastate and inter-state) and non-state conflicts. A state-based conflict (also referred to as armed conflict) is understood in this publication to be “a contested incompatibility that concerns government or territory or both where the use of armed force between two parties results in at least 25 battle-related deaths. Of these two parties, at least one is the government of a state” (Gleditsch et al., 2002[15]). A high-intensity conflict is a conflict that reaches the intensity of war, resulting in at least 1 000 battle-related deaths. These definitions are in accordance with the Uppsala Conflict Data Program (UCDP) definitions. A non-state conflict refers to “the use of armed force between two organized armed groups, neither of which is the government of a state, which results in at least 25 battle-related deaths in a year” in accordance with the UCDP definition (Sundberg, Eck and Kreutz, 2012[16]). Conflict-affected contexts are contexts in which at least one armed conflict was active in 2019. States of Fragility 2020 also makes reference to one-sided violence, defined by UCDP as the “the use of armed force by the government of a state or by a formally organized group against civilians which results in at least 25 deaths in a year” (Eck and Hultman, 2007[17]).

References

[14] Asylbek kyzy, G., C. Delgado and G. Milante (2020), Gaps Report: Challenges of Counting All Violent Deaths Worldwide, GReVD, https://grevd.org/images/uploads/resources/GReVD_GAPS_RPT_FINAL.pdf.

[11] Desai, H. and E. Forsberg (2020), “Analysing the multidimensional fragility framework for States of Fragility 2020”, OECD Publishing, Paris.

[2] Disaster Risk Management Knowledge Centre (2019), INFORM Risk Myanmar 2019, European Commission, Luxembourg, https://drmkc.jrc.ec.europa.eu/inform-index/INFORM-Subnational-Risk/Myanmar.

[17] Eck, K. and L. Hultman (2007), “One-sided violence against civilians in war”, Journal of Peace Research, Vol. 44/2, pp. 233-246, http://dx.doi.org/10.1177/0022343307075124.

[15] Gleditsch, N. et al. (2002), “Armed conflict 1946-2001: A new dataset”, Journal of Peace Research, Vol. 39(5), pp. 615-637, https://doi.org/10.1177/0022343302039005007.

[1] Global Data Lab (2020), Subnational Human Development Index (database), version 4.0, Institute for Management Research, Radboud University, https://globaldatalab.org/shdi/.

[8] OECD (2020), DAC List of ODA Recipients for reporting on aid in 2018 and 2019, http://www.oecd.org/dac/financing-sustainable-development/development-finance-standards/DAC-List-of-ODA-Recipients-for-reporting-2018-and-2019-flows.pdf.

[12] OECD (2020), “Detailed aid statistics: ODA Official development assistance: disbursements”, in OECD International Development Statistics (database), https://doi.org/10.1787/data-00069-en.

[13] OECD (2020), Development Finance Data: Data Tables: Deflators for Resource Flows from DAC Countries (2018=100), https://www.oecd.org/dac/financing-sustainable-development/development-finance-data/.

[5] Pettersson, T. and M. Öberg (2020), “Organized violence, 1989-2019”, Journal of Peace Research, Vol. 57/4, https://journals.sagepub.com/doi/pdf/10.1177/0022343320934986.

[4] PSRP (2020), PA-X Gender Peace Agreement Database, Political Settlements Research Programme, https://www.peaceagreements.org/wsearch.

[3] Runfola, D. et al. (2020), “geoBoundaries: A global database of political administrative boundaries”, PLOS ONE, https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0231866.

[16] Sundberg, R., K. Eck and J. Kreutz (2012), “Introducing the UCDP Non-State Conflict Dataset”, Journal of Peace Research, Vol. 49/2, pp. 351-362, http://dx.doi.org/10.1177/0022343311431598.

[6] Sundberg, R. and E. Melander (2013), “Introducing the UCDP Georeferenced Event Dataset”, Journal of Peace Research, Vol. 50/4, pp. 523-532, https://journals.sagepub.com/doi/10.1177/0022343313484347.

[9] UN DESA (2020), World Population Prospects 2019 (database), United Nations Department of Economic and Social Affairs (UN DESA), New York, https://population.un.org/wpp/.

[7] UNDP (2020), Gender Inequality Index (GII), database, United Nations Development Programme, http://hdr.undp.org/en/content/gender-inequality-index-gii.

[10] World Bank (2020), World Bank Country and Lending Groups, The World Bank, Washington, DC, https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups.

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