Adaptive Rules for Seminonparametric Estimators That Achieve Asymptotic Normality

B-Tier
Journal: Econometric Theory
Year: 1991
Volume: 7
Issue: 3
Pages: 307-340

Authors (2)

Score contribution per author:

1.005 = (α=2.01 / 2 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:cup:etheor:v:7:y:1991:i:03:p:307-340_00
Journal Field
Econometrics
Author Count
2
Added to Database
2026-01-25