日期精度：到日 9 篇 · 到月 91 篇 · 到年 3 篇
GARCH(l,1) 模型中的渐近展开
We develop order T −1 asymptotic expansions for the quasi-maximum likelihood estimator (QMLE) and a two-step approximate QMLE in the GARCH(l,l) model. We calculate the approximate mean and skewness and, hence, the Edgeworth-B distribution function. We suggest several methods of bias reduction based on these approximations.
半参数回归模型中 MINPIN 估计量的 Edgeworth 近似
We examine the higher order asymptotic properties of semiparametric regression estimators that were obtained by the general MINPIN method described in Andrews (1989, Semiparametric Econometric Models: I. Estimation, Discussion paper 908, Cowles Foundation). We derive an order n −1 stochastic expansion and give a theorem justifying order n −1 distributional approximation of the Edgeworth type.
部分线性回归模型中的二阶近似
The author examines the second order properties of various quantities of interest in the partially linear regression model: a stochastic expansion with remainder of order n[superscript -2 mu] in distribution, where mu Copyright 1995 by The Econometric Society.
ARCH 模型中的自适应估计
We construct efficient estimators of the identifiable parameters in a regression model when the errors follow a stationary parametric ARCH( P ) process. We do not assume a functional form for the conditional density of the errors, but do require that it be symmetric about zero. The estimators of the mean parameters are adaptive in the sense of Bickel [2]. The ARCH parameters are not jointly identifiable with the error density. We consider a reparameterization of the variance…