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Structural Break Random Effects Model/Evidence
Method evidence record

Structural Break Random Effects Model

The structural break random effects model extends standard panel RE estimation by allowing one or more breakpoints at which slope coefficients or error variances shift across time. It combines structural change detection (e.g., Bai-Perron) with the GLS-based random effects estimator, producing regime-specific parameter estimates while retaining the efficiency gains of pooling individual-level variation as random draws from a common distribution.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Random Effects Panel Model with Structural Breaks
Taxonomic method record · regression-model / econometrics
  • Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. · DOI 10.2307/2998540
  • Baltagi, B. H. (2008). Econometric Analysis of Panel Data (4th ed.). Wiley. · ISBN 978-0470518861
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Curated claims

Claims persisted in the evidence ledger, each with its own assessment.

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketPanel Hausman Testmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPanel Random Effects Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketStructural Break Fixed Effects Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketStructural Break Panel Data Analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketZivot-Andrews Structural Break Testmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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