Saddlepath learning
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 general...
| Main Authors: | , |
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| Format: | Working paper |
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University of Oxford
2010
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| _version_ | 1826269889685356544 |
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| author | Ellison, M Pearlman, J |
| author_facet | Ellison, M Pearlman, J |
| author_sort | Ellison, M |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-06T21:32:15Z |
| format | Working paper |
| id | oxford-uuid:450fcea0-288c-4a6c-896c-25eac6a4366c |
| institution | University of Oxford |
| last_indexed | 2024-03-06T21:32:15Z |
| publishDate | 2010 |
| publisher | University of Oxford |
| record_format | dspace |
| spelling | oxford-uuid:450fcea0-288c-4a6c-896c-25eac6a4366c2022-03-26T15:05:34ZSaddlepath learningWorking paperhttp://purl.org/coar/resource_type/c_8042uuid:450fcea0-288c-4a6c-896c-25eac6a4366cBulk import via SwordSymplectic ElementsUniversity of Oxford2010Ellison, MPearlman, JSaddlepath 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. |
| spellingShingle | Ellison, M Pearlman, J Saddlepath learning |
| title | Saddlepath learning |
| title_full | Saddlepath learning |
| title_fullStr | Saddlepath learning |
| title_full_unstemmed | Saddlepath learning |
| title_short | Saddlepath learning |
| title_sort | saddlepath learning |
| work_keys_str_mv | AT ellisonm saddlepathlearning AT pearlmanj saddlepathlearning |