LASSO estimation of threshold autoregressive models

Ngai Hang Chan, Chun Yip Yau and Rong-Mao Zhang

Journal of Econometrics, 2015, vol. 189, issue 2, 285-296

Abstract: This paper develops a novel approach for estimating a threshold autoregressive (TAR) model with multiple-regimes and establishes its large sample properties. By reframing the problem in a regression variable selection context, a least absolute shrinkage and selection operator (LASSO) procedure is proposed to estimate a TAR model with an unknown number of thresholds, where the computation can be performed efficiently. It is further shown that the number and the location of the thresholds can be consistently estimated. A near optimal convergence rate of the threshold parameters is also established. Simulation studies are conducted to assess the performance in finite samples. The results are illustrated with an application to the quarterly US real GNP data over the period 1947–2009.

Keywords: Group lasso; Information criterion; Least angle regression (LARS); Multiple regimes (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:189:y:2015:i:2:p:285-296

DOI: 10.1016/j.jeconom.2015.03.023

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