Inference in models with adaptive learning

G. Chevillon, M. Massmann, S. Mavroeidis

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Identification of structural parameters in models with adaptive learning can be weak, causing standard inference procedures to become unreliable. Learning also induces persistent dynamics, and this makes the distribution of estimators and test statistics non-standard. Valid inference can be conducted using the Anderson-Rubin statistic with appropriate choice of instruments. Application of this method to a typical new Keynesian sticky-price model with perpetual learning demonstrates its usefulness in practice. © 2010 Elsevier B.V.
Original languageEnglish
Pages (from-to)341-351
JournalJournal of Monetary Economics
Volume57
DOIs
Publication statusPublished - 2010

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