Autoregressive Lag—Order Selection Using Conditional Saddlepoint Approximations

Ronald W. Butler and Marc S. Paolella
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Ronald W. Butler: Department of Statistical Science, Southern Methodist University, Dallas, TX 75275-0332, USA
Marc S. Paolella: Department of Banking and Finance, University of Zurich, Zurich 8032, Switzerland

Econometrics, 2017, vol. 5, issue 3, 1-33

Abstract: A new method for determining the lag order of the autoregressive polynomial in regression models with autocorrelated normal disturbances is proposed. It is based on a sequential testing procedure using conditional saddlepoint approximations and permits the desire for parsimony to be explicitly incorporated, unlike penalty-based model selection methods. Extensive simulation results indicate that the new method is usually competitive with, and often better than, common model selection methods.

Keywords: ARMA; saddlepoint approximation; simplicity (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2017
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