Robust Market Interventions
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909447417233408 |
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| author | Galeotti, Andrea Golub, Benjamin Goyal, Sanjeev Talamàs, Eduard Tamuz, Omer |
| author_facet | Galeotti, Andrea Golub, Benjamin Goyal, Sanjeev Talamàs, Eduard Tamuz, Omer |
| contents | When can interventions in markets be designed to increase surplus robustly -- i.e., with high probability -- accounting for uncertainty due to imprecise information about economic primitives? In a setting with many strategic firms, each possessing some market power, we present conditions for such interventions to exist. The key condition, recoverable structure, requires large-scale complementarities among families of products. The analysis works by decomposing the incidence of interventions in terms of principal components of a Slutsky matrix. Under recoverable structure, a noisy signal of this matrix reveals enough about these principal components to design robust interventions. Our results demonstrate the usefulness of spectral methods for analyzing imperfectly observed strategic interactions with many agents. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_03026 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Robust Market Interventions Galeotti, Andrea Golub, Benjamin Goyal, Sanjeev Talamàs, Eduard Tamuz, Omer Theoretical Economics Econometrics Applications When can interventions in markets be designed to increase surplus robustly -- i.e., with high probability -- accounting for uncertainty due to imprecise information about economic primitives? In a setting with many strategic firms, each possessing some market power, we present conditions for such interventions to exist. The key condition, recoverable structure, requires large-scale complementarities among families of products. The analysis works by decomposing the incidence of interventions in terms of principal components of a Slutsky matrix. Under recoverable structure, a noisy signal of this matrix reveals enough about these principal components to design robust interventions. Our results demonstrate the usefulness of spectral methods for analyzing imperfectly observed strategic interactions with many agents. |
| title | Robust Market Interventions |
| topic | Theoretical Economics Econometrics Applications |
| url | https://arxiv.org/abs/2411.03026 |