Valid Inference for a Class of Models Where Standard Inference Performs Poorly: Including Nonlinear Regression, ARMA, GARCH, and Unobserved Components

Export/share

Ma, Jun and Nelson, Charles R. (September 2010) Valid Inference for a Class of Models Where Standard Inference Performs Poorly: Including Nonlinear Regression, ARMA, GARCH, and Unobserved Components. Former Series > Working Paper Series > IHS Economics Series 256

Preview

Text
es-256.pdf
Download (466kB) | Preview

Abstract

from the Table of Contents: Introduction; Bias and test size when g(.) is linear; A reduced form test for non-linear g(.) and relative performance in four models; Summary and Conclusions; References; Appendices;

Item Type:	IHS Series
Keywords:	'ARMA' 'Unobserved components' 'State space' 'GARCH' 'Zero-information-limit-condition'
Classification Codes (e.g. JEL):	C120, C220, C330
Date Deposited:	26 Sep 2014 10:39
Last Modified:	19 Sep 2024 13:07
ISBN:	1605-7996
URI:	https://irihs.ihs.ac.at/id/eprint/2017

Actions (login required)

: View Item

Altmetric

CORE (COnnecting REpositories)