Unemployment and econometric learning
Daniel Schaefer () and
Carl Singleton ()
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Daniel Schaefer: https://sites.google.com/site/danielschaefereconomics/
Authors registered in the RePEc Author Service: Daniel Schäfer
ESE Discussion Papers from Edinburgh School of Economics, University of Edinburgh
We apply well-known results of the econometric learning literature to the Mortensen-Pissarides real business cycle model. The unique rational expectations equilibrium (REE) is always expectationally stable with decreasing gain learning, and this result is robust to over-parametrisation of the econometric model relative to the minimum state variable form used by agents. And so, from this perspective, the assumption of rational expectations in the model is not unreasonable. However, using a parametrisation with UK data, simulations suggest that the implied rate of convergence to the REE with least squares learning is slow. The cyclical response of unemployment to structural shocks is muted under learning, and a parametrisation which guarantees root-t convergence is generally not consistent with attempts to match the observed volatility of labour market data using the standard model.
Keywords: real business cycle; unemployment; adaptive learning; expectational stability (search for similar items in EconPapers)
JEL-codes: E24 E32 J64 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dge, nep-lab and nep-mac
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Journal Article: Unemployment and econometric learning (2018)
Working Paper: Unemployment and econometric learning (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:edn:esedps:267
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