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Innovations in Multiple Time Series Analysis

Edited by Jörg Breitung and Helmut Herwartz

Innovations in multiple time series analysis
–Jörg Breitung, Helmut Herwartz [] []

Structural analysis with Multivariate Autoregressive Index models
–Andrea Carriero, George Kapetanios, Massimiliano Marcellino [] []

A multi-country approach to forecasting output growth using PMIs
–Alexander Chudik, Valerie Grossman, M. Hashem Pesaran [] []

The structure of multivariate AR and ARMA systems: Regular and singular systems; the single and the mixed frequency case
–Brian D.O. Anderson, Manfred Deistler, Elisabeth Felsenstein, Lukas Koelbl [] []

Large Bayesian VARMAs
–Joshua C.C. Chan, Eric Eisenstat, Gary Koop [] []

Dynamic prediction pools: An investigation of financial frictions and forecasting performance
–Marco Del Negro, Raiden B. Hasegawa, Frank Schorfheide [] []

Striated Metropolis–Hastings sampler for high-dimensional models
–Daniel F. Waggoner, Hongwei Wu, Tao Zha [] []

Joint confidence sets for structural impulse responses
–Atsushi Inoue, Lutz Kilian [] []

Robust econometric inference with mixed integrated and mildly explosive regressors
–Peter C.B. Phillips, Ji Hyung Lee [] []

Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point
–David Harris, Stephen J. Leybourne, A.M. Robert Taylor [] []

Vector autoregressive moving average identification for macroeconomic modeling: A new methodology
–D.S. Poskitt [] []

Gaussian mixture vector autoregression
–Leena Kalliovirta, Mika Meitz, Pentti Saikkonen [] []

TENET: Tail-Event driven NETwork risk
–Wolfgang Karl Härdle, Weining Wang, Lining Yu [] []

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