Adaptive Rules for Seminonparametric Estimators That Achieve Asymptotic Normality
In econometrics, seminonparametric (SNP) estimators originated in the consumer demand literature. The Fourier flexible form is a well-known example. The idea is to replace the consumer's indirect utility function with a truncated series expansion and then use a parametric procedure, such as nonlinear multivariate regression, to set a confidence interval on an elasticity. More recently, SNP estimators have been used in nonlinear time series analysis. A truncated Hermite expansion with an ARCH leading term is used as the conditional density of the process. The method of maximum likelihood is used to fit it to data.
Year of publication: |
1991
|
---|---|
Authors: | Eastwood, Brian J. ; Gallant, A. Ronald |
Published in: |
Econometric Theory. - Cambridge University Press. - Vol. 7.1991, 03, p. 307-340
|
Publisher: |
Cambridge University Press |
Description of contents: | Abstract [journals.cambridge.org] |
Saved in:
Saved in favorites
Similar items by person
-
Adaptive truncation rules for seminonparametric estimators that achieve asymptotic normality
Eastwood, Brian J., (1987)
-
Adaptive rules for seminonparametric estimators that achieve asymptotic normality
Eastwood, Brian J., (1991)
-
Eastwood, Brian J., (1992)
- More ...