3 resultados para MCDONALD EXTENDED EXPONENTIAL MODEL

em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom


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Paper delivered at the Western Regional Science Association Annual Conference, Sedona, Arizona, February, 2010.

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This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they need to make forecasts of the conditional variance of a stock’s return. Recursive updating of both the conditional variance and the expected return implies several mechanisms through which learning impacts stock prices. Extended periods of excess volatility, bubbles and crashes arise with a frequency that depends on the extent to which past data is discounted. A central role is played by changes over time in agents’ estimates of risk.

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This paper presents a general equilibrium model in which nominal government debt pays an inflation risk premium. The model predicts that the inflation risk premium will be higher in economies which are exposed to unanticipated inflation through nominal asset holdings. In particular, the inflation risk premium is higher when government debt is primarily nominal, steady-state inflation is low, and when cash and nominal debt account for a large fraction of consumers' retirement portfolios. These channels do not appear to have been highlighted in previous models or tested empirically. Numerical results suggest that the inflation risk premium is comparable in magnitude to standard representative agent models. These findings have implications for management of government debt, since the inflation risk premium makes it more costly for governments to borrow using nominal rather than indexed debt. Simulations of an extended model with Epstein-Zin preferences suggest that increasing the share of indexed debt would enable governments to permanently lower taxes by an amount that is quantitatively non-trivial.