Adaptive Rules for Seminonparametric Estimators That Achieve Asymptotic Normality
- 1 September 1991
- journal article
- research article
- Published by Cambridge University Press (CUP) in Econometric Theory
- Vol. 7 (3), 307-340
- https://doi.org/10.1017/s0266466600004497
Abstract
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.Keywords
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