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Article type: Research Article
Authors: Gennari, Pietro* | Navarro, Dorian Kalamvrezos
Affiliations: Food and Agriculture Organization of the United Nations, Viale delle Terme di Caracalla, 00153 Rome, Italy
Correspondence: [*] Corresponding author: Pietro Gennari, Food and Agriculture Organization of the United Nations, %****␣sji-35-sji190519_temp.tex␣Line␣100␣**** Viale delle Terme di Caracalla, 00153 Rome, Italy. E-mail: [email protected].
Note: [1] The views expressed in this publication are those of the author(s) and do not necessarily reflect the views or policies of the Food and Agriculture Organization of the United Nations.
Abstract: The Sustainable Development Goals (SDG) indicator framework represents a major challenge and a unique opportunity for the advancement of the global statistical system, both in terms of methodological development and governance. Over the past three years, the Inter-Agency and Expert Group on SDG indicators (IAEG-SDG) has gradually developed a number of documents providing criteria and guidelines for regulating data flows between countries and custodian agencies needed to inform the global SDG reporting process. The validation of methods and data for SDG indicators, while apparently consisting of two completely separate matters, have been closely linked in the SDG process. When validating country data, National Statistics Offices (NSOs) are effectively also certifying the specific methodology used by the custodian agency for the compilation of the indicator, in particular the data source used and the adjustments made to harmonize national definitions and classifications. This article highlights some of the main challenges in the practical implementation of the guidelines on data flows, identifies areas in need of further guidance from the IAEG-SDG and provides some proposals aimed at improving the global SDG reporting process.
Keywords: Guidelines on data flows, global statistics governance, international standards, non-official data sources, independence of official statistics
DOI: 10.3233/SJI-190519
Journal: Statistical Journal of the IAOS, vol. 35, no. 4, pp. 735-741, 2019
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