Title: Frequency domain minimum distance inference for possibly noninvertible and noncausal ARMA models
Authors: Carlos Velasco - Universidad Carlos III de Madrid (Spain) [presenting]
Ignacio Lobato - ITAM (Mexico)
Abstract: Frequency domain minimum distance procedures are introduced for performing inference in general, possibly non causal and/or noninvertible, autoregressive moving average (ARMA) models. We use information from higher order moments to achieve identification on the location of the roots of the AR and MA polynomials for non-Gaussian time series. We study minimum distance estimation that combines the information contained in second, third, and fourth moments. Contrary to existing estimators, the proposed estimator is consistent under general assumptions, and improves on the efficiency of the estimates based on only second order moments.