Bootstrap Sequential Determination of the Co-integration Rank in VAR Models
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Bootstrap Sequential Determination of the Co-integration Rank in VAR Models. / Cavaliere, Giuseppe; Rahbek, Anders; Taylor, A. M. Robert.
Department of Economics, University of Copenhagen, 2010.Research output: Working paper
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TY - UNPB
T1 - Bootstrap Sequential Determination of the Co-integration Rank in VAR Models
AU - Cavaliere, Giuseppe
AU - Rahbek, Anders
AU - Taylor, A. M. Robert
N1 - JEL Classifications: C30, C32
PY - 2010
Y1 - 2010
N2 - Determining the co-integrating rank of a system of variables has become a fundamental aspect of applied research in macroeconomics and finance. It is wellknown that standard asymptotic likelihood ratio tests for co-integration rank of Johansen (1996) can be unreliable in small samples with empirical rejection frequencies often very much in excess of the nominal level. As a consequence, bootstrap versions of these tests have been developed. To be useful, however, sequential procedures for determining the co-integrating rank based on these bootstrap tests need to be consistent, in the sense that the probability of selecting a rank smaller than (equal to) the true co-integrating rank will converge to zero (one minus the marginal significance level), as the sample size diverges, for general I(1) processes. No such likelihood-based procedure is currently known to be available. In this paper we fill this gap in the literature by proposing a bootstrap sequential algorithm which we demonstrate delivers consistent cointegration rank estimation for general I(1) processes. Finite sample Monte Carlo simulations show the proposed procedure performs well in practice.
AB - Determining the co-integrating rank of a system of variables has become a fundamental aspect of applied research in macroeconomics and finance. It is wellknown that standard asymptotic likelihood ratio tests for co-integration rank of Johansen (1996) can be unreliable in small samples with empirical rejection frequencies often very much in excess of the nominal level. As a consequence, bootstrap versions of these tests have been developed. To be useful, however, sequential procedures for determining the co-integrating rank based on these bootstrap tests need to be consistent, in the sense that the probability of selecting a rank smaller than (equal to) the true co-integrating rank will converge to zero (one minus the marginal significance level), as the sample size diverges, for general I(1) processes. No such likelihood-based procedure is currently known to be available. In this paper we fill this gap in the literature by proposing a bootstrap sequential algorithm which we demonstrate delivers consistent cointegration rank estimation for general I(1) processes. Finite sample Monte Carlo simulations show the proposed procedure performs well in practice.
KW - Faculty of Social Sciences
KW - trace test
KW - sequential rank determination
KW - i.i.d. bootstrap
KW - wild bootstrap
M3 - Working paper
BT - Bootstrap Sequential Determination of the Co-integration Rank in VAR Models
PB - Department of Economics, University of Copenhagen
ER -
ID: 17581786