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Validation of methods and data for SDG indicators

机译:验证SDG指标的方法和数据

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摘要

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.
机译:可持续发展目标(SDG)指标框架代表了各种主要挑战和全球统计系统方面的独特机会,无论是在方法论发展和治理方面。在过去三年中,SDG指标的机构间和专家组(IAEG-SDG)逐步制定了一些文件,提供了规范国家和监管机构之间的数据流量的标准和准则,以通知全球SDG报告进程所需的数据流动。 SDG指标的方法和数据验证,同时明显由两个完全分开的事项组成,在SDG过程中密切相关。在验证国家数据时,国家统计办公室(NSO)还有效地证明了监护人机构汇编指标汇编的具体方法,特别是使用的数据源以及统一国家定义和分类的调整。本文突出了数据流动指南的实际实施中的一些主要挑战,确定了IAEG-SDG的进一步指导的领域,并提供了一些旨在改善全球SDG报告进程的建议。

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