Estimating dynamic rational expectations models when the trend specification is uncertain

Timothy Cogley ()

No 96-01, Working Papers in Applied Economic Theory from Federal Reserve Bank of San Francisco

Abstract: This paper explores various strategies for estimating rational expectations models when the trend specification is uncertain. One approach modified the likelihood function in order to reduce the influence of low-frequency dynamics. Hansen and Sargent (1993) conjectured that this would have little cost in correctly specified models and would improve estimated in mis-specified models. This paper confirms the first part of their conjecture but not the second. Contrary to intuition, the effects of trend-specification errors are spread across the entire frequency domain and are not confined to low-frequencies. Hence, deleting low-frequency dynamics does not remove the specification error. Another approach seeks a representation of the approximating model that does not condition on a specification of the trend, and it estimated parameters by GMM. This approach compares favorably with MLS when the trend is correctly specified and is superior when the trend is mis-specified.

Keywords: Rational expectations (Economic theory); Econometric models (search for similar items in EconPapers)
Date: 1996
New Economics Papers: this item is included in nep-ecm and nep-ets
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