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Research PaperResearchia:202609.25038

Decision-Relevant Information in Partially Observed Production Networks

Shaowen Luo

Abstract

A production network can remain largely unidentified even when the economic decision it supports is identified. We characterize sufficient measurements for exposure-based decisions and compute sharp maximum regret over networks consistent with released totals. Using earlier and later vintages of Japan's interregional input-output accounts, we select measurements from the 1995 table and evaluate the frozen design against the 2005 benchmark. At roughly half the statistics required for full disclos...

Submitted: September 25, 2026Subjects: Economics; Environmental Science

Description / Details

A production network can remain largely unidentified even when the economic decision it supports is identified. We characterize sufficient measurements for exposure-based decisions and compute sharp maximum regret over networks consistent with released totals. Using earlier and later vintages of Japan's interregional input-output accounts, we select measurements from the 1995 table and evaluate the frozen design against the 2005 benchmark. At roughly half the statistics required for full disclosure, the resulting monitoring set loses only 0.07 percentage points of average exposure relative to the benchmark optimum, yet its sharp maximum regret across compatible networks is 4.83 points. In U.S. coal deliveries surrounding a 2005 Wyoming rail disruption, additional shipment measurements identify the optimal set of plants to monitor for inventory risk, even though four monitored plants' exposures to the affected coal supply remain unidentified. The results distinguish good benchmark performance from a decision guarantee and show that decisions can be identified before individual exposures. They suggest evaluating network data by the economic decisions they support.


Source: arXiv:2609.29905v1 - http://arxiv.org/abs/2609.29905v1 PDF: https://arxiv.org/pdf/2609.29905v1 Original Link: http://arxiv.org/abs/2609.29905v1

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Date:
Sep 25, 2026
Topic:
Environmental Science
Area:
Economics
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