Convex Cost of Information via Statistical Divergence
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912559922151424 |
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| author | Bordoli, Davide Iijima, Ryota |
| author_facet | Bordoli, Davide Iijima, Ryota |
| contents | This paper characterizes convex information costs using an axiomatic approach. We employ mixture convexity and sub-additivity, which capture the idea that producing "balanced" outputs is less costly than producing ``extreme'' ones. Our analysis leads to a novel class of cost functions that can be expressed in terms of Rényi divergences between signal distributions across states. This representation allows for deviations from the standard posterior-separable cost, thereby accommodating recent experimental evidence. We also characterize two simpler special cases, which can be written as either the maximum or a convex transformation of posterior-separable costs. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2509_00229 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Convex Cost of Information via Statistical Divergence Bordoli, Davide Iijima, Ryota Theoretical Economics This paper characterizes convex information costs using an axiomatic approach. We employ mixture convexity and sub-additivity, which capture the idea that producing "balanced" outputs is less costly than producing ``extreme'' ones. Our analysis leads to a novel class of cost functions that can be expressed in terms of Rényi divergences between signal distributions across states. This representation allows for deviations from the standard posterior-separable cost, thereby accommodating recent experimental evidence. We also characterize two simpler special cases, which can be written as either the maximum or a convex transformation of posterior-separable costs. |
| title | Convex Cost of Information via Statistical Divergence |
| topic | Theoretical Economics |
| url | https://arxiv.org/abs/2509.00229 |