Estimating and testing rational expectations models when the trend specification is uncertain
✍ Scribed by Timothy Cogley
- Publisher
- Elsevier Science
- Year
- 2001
- Tongue
- English
- Weight
- 299 KB
- Volume
- 25
- Category
- Article
- ISSN
- 0165-1889
No coin nor oath required. For personal study only.
✦ Synopsis
This paper explores various strategies for estimating and testing rational expectations models when the trend speci"cation is uncertain. One approach seeks to make estimators and tests robust to trend misspeci"cation by reducing the in#uence of low frequency dynamics. However, contrary to intuition, the e!ects of trend speci"cation errors are not con"ned to low frequencies, but are spread across the entire frequency domain. Thus, operations that damp low frequency components do not remove trend speci"cation errors and are not su$cient for constructing robust estimators and tests. Another approach seeks representations of approximating models that do not condition on a speci"cation of the trend, and it uses GMM to estimate parameters and test overidentifying restrictions. Because these methods do not condition on assumptions about trends, they are robust to errors in that part of the approximating model.