eprintid: 34430
rev_number: 18
eprint_status: archive
userid: 3114
dir: disk0/00/03/44/30
datestamp: 2024-02-14 13:55:31
lastmod: 2024-02-15 09:39:24
status_changed: 2024-02-14 13:55:31
type: workingPaper
metadata_visibility: show
creators_name: Becker, Christoph K.
creators_name: Duersch, Peter
creators_name: Eife, Thomas A.
creators_name: Glas, Alexander
title: Using point forecasts to anchor probabilistic survey scales
subjects: ddc-330
divisions: i-181000
keywords: Inflation, density forecast, probabilistic forecast, experiment, survey design, personalized response scales
abstract: We present the results of an experiment where a random subset of the participants in the Bundesbank's household panel receive personalized response scales, centered at each participant's point forecast. Personalized response scales offer two advantages over the standard scale which is centered at zero inflation: First, they mitigate the impact of the central tendency bias which leads respondents to assign greater probability mass to the center of the scale at zero. Second, they eliminate the need to adjust the scale when actual inflation falls outside the range for which the response scale was designed. Our results show that the personalized survey responses are of higher quality in three dimensions: (i) higher internal consistency, (ii) more uni-modal responses, and (iii) a significant reduction in the use of the (minimally informative) unbounded intervals of the response scale.
date: 2024
publisher: Universität
id_scheme: DOI
id_number: 10.11588/heidok.00034430
schriftenreihe_cluster_id: sr-3
schriftenreihe_order: 0743
ppn_swb: 1880837269
own_urn: urn:nbn:de:bsz:16-heidok-344309
language: eng
bibsort: BECKERCHRIUSINGPOINT20240126
full_text_status: public
series: AWI Discussion Paper Series
volume: 0743
place_of_pub: Heidelberg
pages: 9
citation:   Becker, Christoph K. ; Duersch, Peter ; Eife, Thomas A. ; Glas, Alexander  (2024) Using point forecasts to anchor probabilistic survey scales.  [Working paper]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/34430/7/using_point_forecast_p743_2024.pdf