Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/308766 
Erscheinungsjahr: 
2024
Schriftenreihe/Nr.: 
IZA Policy Paper No. 215
Verlag: 
Institute of Labor Economics (IZA), Bonn
Zusammenfassung: 
Existing data are severely insufficient for monitoring progress on the Sustainable Development Goals (SDGs), particularly for poorer countries. While we should continue efforts to produce new, high-quality data, this approach seems not feasible for all poorer countries. We call for a more systematic use of recent innovations with techniques such as data imputation to address existing data challenges. Given some resistance to utilizing new methods for filling data gaps, efforts aiming at changing the current perception and employing a mix of new data collection and data imputation can be useful. We also note that the best and most cost-effective approach would be highly context-specific and depends on various factors such as available budget, logistical capacity, and timeline.
Schlagwörter: 
poverty
imputation
Sustainable Development Goals
developing countries
JEL: 
C15
I32
O15
Dokumentart: 
Working Paper

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