Data · dataset · 2025
The framing effect of cross-period temporal choice in the loss domain will influence the preference for debt-swapping decisions
Listed in ScienceDB
The framing effect stands out as one of the most robust effects among numerous effects that violate rational axioms.
Description
This study focuses on two innovative research directions: First, on a theoretical level, it explores whether the framing effect exists in cross-period temporal choice in the loss domain, which has not been empirically studied before; second, on a practical level, it examines how to use this effect to optimize the implementation of the debt swap policy proposed in the “Local Government Debt Risk Resolution Plan” passed by the Standing Committee of the National People’s Congress in 2024. This paper recruited online participants through a survey platform to complete preference evaluation tasks, consisting of five Studies.
Study 1a (N=1200) employed a 2 (repayment frequency: annual vs. monthly) × 2 (presentation format: text vs. graphic) between-subjects design. Study 1b (N=403) used a mixed design with 3 (repayment frequency: annual vs. monthly vs. weekly, within-subject) × 2 (presentation format: text vs. graphic, between-subjects). Study 2a (N=900) utilized a one-factor (condition: monthly, annual vs. compressed) between-subjects design.
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The first experiment in Study 2b (N=180) adopted a within-subject design (repayment frequency: monthly vs. weekly), while the second experiment (N=180) used a within-subject design (compression condition: normal vs. compressed). In the within-subject designs, evaluation under different conditions were separated by at least a 3-day interval. The task in Study 1 required participants to rate their acceptance of a single debt repayment plan under different conditions, while the task in Study 2 involved participants rating their acceptance of paired debt plans (initial debt vs. swapped debt) under different conditions.The findings are as follows: First, different descriptions of a single debt plan, where “both the debt maturity and the total amount of debt remain unchanged,” can trigger the framing effect.
Whether presented in textual or graphical format, the framing of repayment plans with different frequencies significantly influences creditors' acceptance of the repayment plan. Compared to the high-frequency frame that “appears to last longer” (e.g., weekly payments), the low-frequency frame that “appears to last shorter” (e.g., annual payments) enhances creditors' acceptance of a debt plan where both the maturity and the total amount remain unchanged.
Second, even without changing the basic facts, varying descriptions can generate framing effects for a bi-choice between two debt-repayment scheme where “the debt maturity is different but the total debt remains constant.” Different frames (e.g., monthly payments vs. annual payments, conventional timeline vs. compressed timeline) significantly affect creditors’ preferences for the two options (initial debt vs. swapped debt).
Compared to the monthly payment frame/conventional timeline frame, the annual payment frame/compressed timeline frame makes creditors more inclined to accept the initial debt plan.Participants’ exhibited preferences in the loss domain across different debt repayment timeframes align with the explanation and prediction of the equate-to-differentiate way of seeing cross-period temporal choice. We hope that our findings on the exploration of framing effects can open up our understanding of cross-period temporal choice, add one more tool to the to the “time nudge toolbox,” and provide psychological science support for evaluating the effectiveness of the policy measure of “debt swapping” and optimizing debt management.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.30338 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Text 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.30338 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:text | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |