A Quality Assessment Framework for Maintaining & Publishing New Indicators

George Kapetanios and Fotis Papailias ()

No ESCOE-TR-18, Economic Statistics Centre of Excellence (ESCoE) Technical Reports from Economic Statistics Centre of Excellence (ESCoE)

Abstract: This technical report builds on the research output of “National Accounts and Beyond GDP: Predictive Performance of Real-Time Indicators” ESCoE/ONS collaborative project to summarise the key findings and provide a standardised methodology to guide the editing, maintenance, publishing and potential incorporation of new real-time indicators into the development of early estimates of headline economic statistics. Empirical results from previous tasks are revisited and standardised qualitative and quantitative criteria are discussed.

Keywords: machine learning; nowcasting; real-time indicators (search for similar items in EconPapers)
JEL-codes: C53 E37 (search for similar items in EconPapers)
Date: 2022-05
New Economics Papers: this item is included in nep-big and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://escoe-website.s3.amazonaws.com/wp-content/ ... 3802/ESCoE-TR-18.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nsr:escoet:escoe-tr-18

Access Statistics for this paper

More papers in Economic Statistics Centre of Excellence (ESCoE) Technical Reports from Economic Statistics Centre of Excellence (ESCoE) King's College London Strand London WC2R 2LS. Contact information at EDIRC.
Bibliographic data for series maintained by ESCoE Centre Manager ().