Template-type: ReDIF-Paper 1.0
Author-Name: Canepa, Alessandra
Author-Email: alessandra.canepa@unito.it 
Author-Workplace-Name: University of Turin
Author-Workplace-Homepage: http://www.est.unito.it/
Title: Bootstrap Bartlett Adjustment for Hypotheses Testing on Cointegrating Vectors.
Abstract: Johansen?s (2000) Bartlett correction factor for the LR test of linear restrictions on cointegrated vectors is derived under the 
i.i.d. Gaussian assumption for the innovation terms. However, the distribution of most data relating to ?nancial variables are fat-tailed and 
often skewed, there is therefore a need to examine small sample inference procedures that require weaker assumptions for the innovation term. 
This paper suggests that using a non-parametric bootstrap to approximate a Bartlett-type correction provides a statistic that does not require 
speci?cation of the innovation distribution and can be used by applied econometricians to perform a small sample inference procedure that is less 
computationally demanding than estimating the p-value of the observed statistic.
Length: pages 37
Creation-Date: 2020-03
File-URL: https://www.est.unito.it/do/home.pl/Download?doc=/allegati/wp2020dip/wp_06_2020.pdf
File-Format: Application/PDF
Handle: RePEc:uto:dipeco:202006