arXiv 6 May 2026 · Econometrics
arXiv:2605.04592 · PDF · DOI · OpenAlex · Extracted main text
Interaction effects are often economically central in environments where structural dynamic estimation becomes computationally infeasible. Under fixed group membership and sparse within-group interaction structure, the Bellman operator admits a block-diagonal decomposition that allows high-dimensional dynamic programs to be solved through independent group-level subproblems while preserving the original structural problem exactly. The result applies to a class of dynamic discrete choice models in which interactions are confined within stable local groups and state transitions depend only on within-group conditions. We apply the framework to replacement decisions across 14,344 GPU node locations in the Titan supercomputer, where operating environments differ systematically across cage positions. The structural estimates reveal significant spatial coordination: both neighboring failures and recent local replacement activity increase replacement incentives. Accounting for these interaction effects materially shifts predicted replacement timing and reveals significant misoptimization costs in benchmarks that assume conditional independence. More broadly, the results show how exploiting sparsity in interaction structures can make fully structural estimation feasible in large-scale networked systems without relying on simulation-based auxiliary moments or numerical approximation.
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| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Diamond, L and Gilbert, Benjamin (2025) The Economics of Spatial Coordination in Critical Infrastructure Investment self | 0.644 | 2 | 2 | 100% |
| 2 | Ostrouchov, George and Maxwell, Don and Ashraf, Rizwan A. and Engelm… (2020) GPU Lifetimes on Titan Supercomputer: Survival Analysis and Reliability | 0.644 | 2 | 2 | 100% |
| 3 | Rust, John (1987) Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher | 0.511 | 2 | 1 | 100% |
| 4 | Tsakiris, Manolis C. and Tarraf, Danielle C (2015) Algebraic decompositions of dynamic programming problems with linear dynamics | 0.405 | 1 | 1 | 100% |
| 5 | Aguirregabiria, Victor and Mira, Pedro (2007) Sequential Estimation of Dynamic Discrete Games | 0.405 | 1 | 1 | 100% |
| 6 | Anselin, Luc (1988) Spatial Econometrics: Methods and Models | 0.405 | 1 | 1 | 100% |
| 7 | Bajari, Patrick and Benkard, C. Lanier and Levin, Jonathan (2007) Estimating Dynamic Models of Imperfect Competition | 0.405 | 1 | 1 | 100% |
| 8 | Benkard, C Lanier (2000) Learning and forgetting: The dynamics of aircraft production | 0.405 | 1 | 1 | 100% |
| 9 | Bramoullé, Yann and Djebbari, Habiba and Fortin, Bernard (2009) Identification of Peer Effects through Social Networks | 0.405 | 1 | 1 | 100% |
| 10 | Cai, Yongyang and Judd, Kenneth L (2010) Dynamic Programming with Hermite Approximation | 0.405 | 1 | 1 | 100% |
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