Parameter Estimation of Standard AR(1) and MA(1) Models Driven by a Non-I.I.D. Noise

Violetta Dalla (), Liudas Giraitis () and Murad S. Taqqu ()
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Violetta Dalla: National and Kapodistrian University of Athens
Liudas Giraitis: Queen Mary University of London
Murad S. Taqqu: Boston University

Chapter Chapter 6 in Research Papers in Statistical Inference for Time Series and Related Models, 2023, pp 155-172 from Springer

Abstract: Abstract The use of a non-i.i.d. noise in parametric modeling of stationary time series can lead to unexpected distortions of the standard errors and confidence intervals in parameter estimation. We consider AR(1) and MA(1) models and motivate the need for correction of standard errors when these are generated by a non-i.i.d. noise. The impact of the noise on the standard errors and confidence intervals is illustrated with Monte Carlo simulations using various types of noise.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-99-0803-5_6

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DOI: 10.1007/978-981-99-0803-5_6

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