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Adaptive Learning and Labour Market Dynamics
| Content Provider | Scilit |
|---|---|
| Author | Pace, Federico Di Mitra, Kaushik Zhang, Shoujian |
| Copyright Year | 2016 |
| Description | Journal: SSRN Electronic Journal The standard search and matching model with rational expectations is well known to be unable to generate amplification in unemployment and vacancies. We document a new feature it is unable to replicate: properties of survey forecasts of unemployment in the near term. We present a parsimonious model with adaptive learning and simple autoregressive forecasting rules which provide a solution to both of these problems. Firms choose vacancies by forecasting wages using simple autoregressive models; they have greater incentive to post vacancies at the time of a positive productivity shock because of overoptimism about the discounted value of expected profits. |
| Related Links | http://www.st-andrews.ac.uk/~wwwecon/repecfiles/2/1408.pdf https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=2885250 |
| ISSN | 10914358 |
| e-ISSN | 15565068 |
| DOI | 10.2139/ssrn.2885250 |
| Journal | SSRN Electronic Journal |
| Language | English |
| Publisher | Elsevier BV |
| Publisher Date | 2016-12-09 |
| Access Restriction | Open |
| Subject Keyword | Journal: SSRN Electronic Journal History and Philosophy of Science Adaptive Learning Simple Autoregressive |
| Content Type | Text |
| Resource Type | Article |
| Subject | Public Health, Environmental and Occupational Health Psychiatry and Mental Health |