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Inference in models with adaptive learning

Listed author(s):
  • Chevillon, Guillaume
  • Massmann, Michael
  • Mavroeidis, Sophocles

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.

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File URL: http://www.sciencedirect.com/science/article/pii/S0304-3932(10)00015-2
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Article provided by Elsevier in its journal Journal of Monetary Economics.

Volume (Year): 57 (2010)
Issue (Month): 3 (April)
Pages: 341-351

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Handle: RePEc:eee:moneco:v:57:y:2010:i:3:p:341-351
Contact details of provider: Web page: http://www.elsevier.com/locate/inca/505566

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