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Title: Simulation, estimation and selection of mixed causal-noncausal autoregressive models: The MARX package Authors:  Alain Hecq - Maastricht University (Netherlands)
Lenard Lieb - Maastricht University (Netherlands)
Sean Telg - Maastricht University (Netherlands)
Sean Telg - Maastricht University (Netherlands) [presenting]
Abstract: The MARX package is presented for the analysis of mixed causal-noncausal autoregressive processes with possibly exogenous regressors. The distinctive feature of MARX models is that they abandon the Gaussianity assumption on the error term. This deviation from the Box-Jenkins approach allows researchers to distinguish backward- (causal) and forward-looking (noncausal) stationary behavior in time series. The MARX package offers functions to simulate, estimate and select mixed causal-noncausal autoregressive models, possibly including exogenous regressors.