The effects of outdated data and outliers on Kenya’s 2019 Global Food Security Index score and rank
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| dc.contributor.author | Atieno, Prisca
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| dc.contributor.author | Hendriks, Sheryl L.
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| dc.date.accessioned | 2024-04-18T13:13:55Z | |
| dc.date.available | 2024-04-18T13:13:55Z | |
| dc.date.issued | 2023-03-29 | |
| dc.description | AVAILABILITY OF DATA AND MATERIAL : The datasets generated and analysed during the current study are available in the Global Food Security Index repository at https://foodsecurityindex.eiu.com/. | en_US |
| dc.description | ADDITIONAL FILE 1: TABLE S1. GFSI dimensions, indicators and sub indicators. TABLE S2. Changes in scores for the 113 countries after winsorisation of the outlier data points. TABLE S3. Shifts in ranks for the 113 countries after the winsorisation of the outlier data points in the 2019 GFSI database. | en_US |
| dc.description.abstract | The heterogeneity of food security indicators and the lack of consensus on comparing and ranking countries have driven international organisations to build composite indicators (Santeramo 2015). Composite indicators are aggregated indexes comprising individual indicators and weights, each representing an indicator’s relative importance based on a given underlying model (Nardo et al. 2005). Policymakers often rely on composite indicators as useful diagnostic tools for prioritising policies (Turan et al. 2018), while in benchmarking exercises, poor-performing countries also learn from better-performing countries. Moreover, composite indicators are essential for public communication due to ease of interpretation (Santeramo 2017). | en_US |
| dc.description.department | Agricultural Economics, Extension and Rural Development | en_US |
| dc.description.librarian | am2024 | en_US |
| dc.description.sdg | SDG-02:Zero Hunger | en_US |
| dc.description.sponsorship | Mastercard Foundation Bursary. | en_US |
| dc.description.uri | https://cabiagbio.biomedcentral.com | en_US |
| dc.identifier.citation | Atieno, P. & Hendriks, S.L. 2023, 'The effects of outdated data and outliers on Kenya’s 2019 global food security index score and rank', CABI Agriculture and Bioscience, vol. 4, no. 6, pp. 1-12. https://DOI.org/10.1186/s43170-023-00140-y | en_US |
| dc.identifier.issn | 2662-4044 | |
| dc.identifier.other | 10.1186/s43170-023-00140-y | |
| dc.identifier.uri | http://hdl.handle.net/2263/95662 | |
| dc.language.iso | en | en_US |
| dc.publisher | BMC | en_US |
| dc.rights | © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License. | en_US |
| dc.subject | Policymakers | en_US |
| dc.subject | Policies | en_US |
| dc.subject | Diagnostic tools | en_US |
| dc.subject | Benchmarking | en_US |
| dc.subject | Food security indicators | en_US |
| dc.subject | SDG-02: Zero hunger | en_US |
| dc.title | The effects of outdated data and outliers on Kenya’s 2019 Global Food Security Index score and rank | en_US |
| dc.type | Article | en_US |
