Coarse Information Design
Fuente:
arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| _version_ | 1866908410896711680 |
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| author | Lyu, Qianjun Suen, Wing Zhang, Yimeng |
| author_facet | Lyu, Qianjun Suen, Wing Zhang, Yimeng |
| contents | We study an information design problem with continuous state and discrete signal space. Under convex and S-shaped value functions, the optimal information structure is interval-partitional and exhibits a dual expectations property: each induced signal is the conditional mean (taken under the prior density) of each interval; and each interval cutoff is the barycenter (taken under the value function curvature) of the interval formed by neighboring signals. This property enables an examination into which part of the state space is more finely partitioned. The analysis can be extended to general value functions and adapted to study coarse mechanism design. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2305_18020 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Coarse Information Design Lyu, Qianjun Suen, Wing Zhang, Yimeng Theoretical Economics We study an information design problem with continuous state and discrete signal space. Under convex and S-shaped value functions, the optimal information structure is interval-partitional and exhibits a dual expectations property: each induced signal is the conditional mean (taken under the prior density) of each interval; and each interval cutoff is the barycenter (taken under the value function curvature) of the interval formed by neighboring signals. This property enables an examination into which part of the state space is more finely partitioned. The analysis can be extended to general value functions and adapted to study coarse mechanism design. |
| title | Coarse Information Design |
| topic | Theoretical Economics |
| url | https://arxiv.org/abs/2305.18020 |