Publication: Fractional cointegration rank estimation
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2014-05-28
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Taylor & Francis
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Abstract
We consider cointegration rank estimation for a p-dimensional Fractional Vector Error Correction Model. We propose a new two-step procedure which allows testing for furtherlong-run equilibrium relations with possibly different persistence levels. The first step consists in estimating the parameters of the model under the none hypothesis of the cointegration rank r = 1; 2,... p - 1: This step provides consistent estimates of the order of fractional cointegration, the cointegration vectors, the speed of adjustment to the equilibrium parameters and the common trends. In the second step we carry out a sup-likelihood ratio test of no-cointegration on the estimated p - r common trends that are not cointegrated under the none. The order of fractional cointegration is re-estimatedin the second step to allow for new cointegration relationships with different memory. We augment the error correction model in the second step to adapt to the representation of the common trends estimated in the first step. The critical values of the proposed tests depend only on the number of common trends under the none, p-r; and on the interval of the orders of fractional cointegration b allowed in the estimation, but not on the order of fractional cointegration of already identied relationships. Hence this reduces the set of simulations required to approximate the critical values, making this procedure convenient for practical purposes. In a Monte Carlo study we analyze the finite sample properties of our procedure and compare with alternative methods. We finally apply these methods to study the term structure of interest rates.
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Error correction model, Gaussian VAR model, Likelihood ratio tests, Maximum likelihood estimation
Bibliographic citation
Lasak, K. and C. Velasco. Fractional cointegration rank estimation. Journal of Business & Economic Statistics, forthcoming