Adaptive estimation of AR∞ models with time-varying variances

Erhua Zhang and Jilin Wu

Economics Letters, 2020, vol. 197, issue C

Abstract: This paper considers adaptive estimation of AR∞ models under time-varying variances of unknown forms. We utilize the sieve method to approximate the autoregressive model of infinite order, and then develop kernel-based estimators of the residual variances and associated adaptive least squares (ALS) estimators of the autoregressive coefficients. We prove the ALS estimator has the same efficiency as its infeasible counterpart. Simulation results show the adaptive procedure can help achieve efficiency gains in finite samples.

Keywords: Time-varying variances; Sieve approximation; Adaptive estimation; Lag selection (search for similar items in EconPapers)
JEL-codes: C14 C22 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:197:y:2020:i:c:s0165176520304018

DOI: 10.1016/j.econlet.2020.109641

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