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Jeudi 10 Avril 2014

Anders RAHBEK (University of Copenhagen and CREATES)
"Inference on Co-integration Parameters in Hetoroskedastic Vector Autoregressions"

16H15 en salle S016 au CREST, 15 Boulevard Gabriel Péri, 92245 MALAKOFF (Métro : Malakoff/Plateau de Vanves (Immeuble "Malakoff 2)).




It is well established that the shocks driving many key macro-economic and financial variables display time-varying volatility. We consider estimation and hypothesis testing on rank, coeffi cients of the co-integrating relations and the adjustment coe fficients in

vector autoregressions driven by both conditional and unconditional heteroskedasticity of a quite general and unknown form in the shocks. We show that the conventional results in Johansen (1996) for the maximum likelihood estimators and associated likelihood ratio tests derived under homoskedasticity do not in general hold in the presence of heteroskedasticity. As a consequence, standard con dence intervals and tests of hypothesis on these coe fficients are potentially unreliable. Solutions to this inference problem based on the use of the wild bootstrap are discussed. These do not require the practitioner to specify a parametric model for volatility, or to assume that the pattern of volatility is common to, or independent across, the vector of series under analysis. We formally establish the conditions under which these methods

are asymptotically valid. A Monte Carlo simulation study demonstrates that signifi cant

improvements in finite sample size can be obtained by the bootstrap over the corresponding asymptotic tests in both heteroskedastic and homoskedastic environments. An application to the term structure of interest rates in the US illustrates the diff erence between standard and bootstrap inferences regarding hypotheses on the co-integrating vectors and adjustment coe fficients.