Estimating dynamic rational expectations models when the trend specification is uncertain
AbstractThis 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.
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Bibliographic InfoPaper provided by Federal Reserve Bank of San Francisco in its series Working Papers in Applied Economic Theory with number 96-01.
Date of creation: 1996
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-1999-11-28 (All new papers)
- NEP-ECM-1999-11-28 (Econometrics)
- NEP-ETS-1999-11-28 (Econometric Time Series)
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