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Title: Community detection in large vector autoregressions Authors:  Gudmundur Gudmundsson - Aarhus University (Denmark) [presenting]
Abstract: A class of vector autoregressive (VAR) models are introduced in which the time series are partitioned into unknown communities. Spillovers are stronger between series that belong to the same community than otherwise. A natural question which arises in this framework is how to detect the communities from data. To this end, we propose an algorithm that uses the eigenvectors of a function of the estimated autoregressive matrices to consistently recover the communities. The methodology is applied to study clustering in industrial production among a group of major economies. We also introduce a regularised VAR estimator motivated by the algorithm, which performs favourably relative to a number of alternatives in an out-of-sample forecasting exercise.