EconStor >
Rutgers University >
Department of Economics, Rutgers University >
Working Papers, Department of Economics, Rutgers University >

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10419/23168
  
Title:Bootstrap Conditional Distribution Tests In the Presence of Dynamic Misspecification PDF Logo
Authors:Corradi, Valentina
Swanson, Norman R.
Issue Date:2003
Series/Report no.:Working papers / Rutgers University, Department of Economics 2003,11
Abstract:In this paper, we show the first order validity of the block bootstrap in the context of Kolmogorov type conditional distribution tests when there is dynamic misspecification and parameter estimation error. Our approach differs from the literature to date because we construct a bootstrap statistic that allows for dynamic misspecification under both hypotheses. We consider two test statistics; one is the CK test of Andrews (1997), and the other is in the spirit of Diebold, Gunther and Tay (1998). The limiting distribution of both tests is a Gaussian process with a covariance kernel that reflects dynamic misspecification and parameter estimation error. In order to provide valid asymptotic critical values we suggest an extention of the empirical process version of the block bootstrap to the case of non vanishing parameter estimation error. The findings from Monte Carlo experiments show that both statistics have good finite sample properties for samples as small as 500 observations.
Subjects:block bootstrap
conditional distributions
conditional Kolmogorov tests
dynamic misspecification
parameter estimation error
JEL:C12
C22
Document Type:Working Paper
Appears in Collections:Working Papers, Department of Economics, Rutgers University

Files in This Item:
File Description SizeFormat
2003-11.pdf306.91 kBAdobe PDF
No. of Downloads: Counter Stats
Download bibliographical data as: BibTeX
Share on:http://hdl.handle.net/10419/23168

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.