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A procedure to detect hidden cointegration with the sieve bootstrap

Authors: GEROLIMETTO, Margherita; PIZZI, Claudio; PROCIDANO, Isabella;

A procedure to detect hidden cointegration with the sieve bootstrap

Abstract

In this paper we consider a particular form of cointegration, called hidden cointegration, which arises between positive and/or negative components of a time series. Hidden cointegration is especially interesting to model asymmetric behaviours, but it requires specific estimation and testing procedures. In order to detect the existence of hidden cointegration we propose a bootstrap version of the two stage Engle and Granger procedure (originally thought for linear cointegration). We also present some Monte Carlo evidence and an application to real data.

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Italy
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Keywords

time series; Hidden cointegration; Sieve Bootstrap, Hidden cointegration; Sieve Bootstrap

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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