The likelihood ratio test for cointegration ranks in the I(2) model
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The likelihood ratio test for cointegration ranks in the I(2) model. / Nielsen, Heino Bohn; Rahbek, Anders Christian.
In: Econometric Theory, Vol. 23, No. 4, 2007, p. 615-637.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - The likelihood ratio test for cointegration ranks in the I(2) model
AU - Nielsen, Heino Bohn
AU - Rahbek, Anders Christian
N1 - JEL Classification: C32
PY - 2007
Y1 - 2007
N2 - This paper presents the likelihood ratio (LR) test for the number of cointegrating relations in the I(2) vector autoregressive model. It is shown that the asymptotic distribution of the LR test for the cointegration ranks is identical to the asymptotic distribution of the much applied test statistic based on the two-step estimation procedure in Johansen (1995, Econometric Theory 11, 25-59), Paruolo (1996, Journal of Econometrics 72, 313-356), and Rahbek, Kongsted, and Jørgensen (1999, Journal of Econometrics 90, 265-289). By construction the LR test statistic is smaller than the non-LR test statistic from the two-step procedure, and application of the LR test may change rank selection in empirical work. Based on a study of existing empirical applications and related Monte Carlo simulations we conclude that the LR test has much better size properties when compared to the two-step-based test. Overall, we propose use of the LR test for rank determination in I(2) analysis
AB - This paper presents the likelihood ratio (LR) test for the number of cointegrating relations in the I(2) vector autoregressive model. It is shown that the asymptotic distribution of the LR test for the cointegration ranks is identical to the asymptotic distribution of the much applied test statistic based on the two-step estimation procedure in Johansen (1995, Econometric Theory 11, 25-59), Paruolo (1996, Journal of Econometrics 72, 313-356), and Rahbek, Kongsted, and Jørgensen (1999, Journal of Econometrics 90, 265-289). By construction the LR test statistic is smaller than the non-LR test statistic from the two-step procedure, and application of the LR test may change rank selection in empirical work. Based on a study of existing empirical applications and related Monte Carlo simulations we conclude that the LR test has much better size properties when compared to the two-step-based test. Overall, we propose use of the LR test for rank determination in I(2) analysis
U2 - 10.1017/S0266466607070272
DO - 10.1017/S0266466607070272
M3 - Journal article
VL - 23
SP - 615
EP - 637
JO - Econometric Theory
JF - Econometric Theory
SN - 0266-4666
IS - 4
ER -
ID: 1385526