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Saddlepath learning

  • Ellison, Martin
  • Pearlman, Joseph

Saddlepath learning occurs when agents learn adaptively using a perceived law of motion that has the same form as the saddlepath relationship in rational expectations equilibrium. Under saddlepath learning, we obtain a completely general relationship between determinacy and e-stability, and generalise minimum state variable results previously derived only under full information. When the system is determinate, we show that a learning process based on the saddlepath is always e-stable. When the system is indeterminate, we find there is a unique MSV solution that is iteratively e-stable. However, in this case there is a sunspot solution that is learnable as well. We conclude by demonstrating that our results hold for any information set.

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Article provided by Elsevier in its journal Journal of Economic Theory.

Volume (Year): 146 (2011)
Issue (Month): 4 (July)
Pages: 1500-1519

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Handle: RePEc:eee:jetheo:v:146:y:2011:i:4:p:1500-1519
Contact details of provider: Web page: http://www.elsevier.com/locate/inca/622869

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