EconPapers    
Economics at your fingertips  
 

A new metric of consensus for Likert scales

Oscar Claveria ()

No 201810, AQR Working Papers from University of Barcelona, Regional Quantitative Analysis Group

Abstract: In this study we present a metric of consensus for Likert-type scales. The measure gives the level of agreement as the percentage of consensus among respondents. The proposed framework allows to design a positional indicator that gives the degree of agreement for each item and for any given number of reply options. In order to assess the performance of the proposed metric of consensus, in an iterated one-period ahead forecasting experiment we test whether the inclusion of the degree of agreement in consumers’ expectations regarding the evolution of unemployment improves out-of-sample forecast accuracy in eight European countries. We find evidence that the degree of agreement among consumers contains useful information to predict unemployment rates in most countries. The obtained results show the usefulness of consensus-based metrics to track the evolution of economic variables.

Keywords: Likert scales; consensus; geometry; economic tendency surveys; consumer expectations; unemployment JEL classification: C14; C51; C52; C53; D12; E24 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-for
Date: 2018-10, Revised 2018-10
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://www.ub.edu/irea/working_papers/2018/201821.pdf (application/pdf)

Related works:
Working Paper: A new metric of consensus for Likert scales (2018) Downloads
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:aqr:wpaper:201810

Access Statistics for this paper

More papers in AQR Working Papers from University of Barcelona, Regional Quantitative Analysis Group Contact information at EDIRC.
Bibliographic data for series maintained by Bibiana Barnadas ().

 
Page updated 2019-11-11
Handle: RePEc:aqr:wpaper:201810