Saddlepoint approximations for short and long memory time series: A frequency domain approach

Davide La Vecchia and Elvezio Ronchetti

Journal of Econometrics, 2019, vol. 213, issue 2, 578-592

Abstract: Saddlepoint techniques provide numerically accurate, small sample approximations to the distribution of estimators and test statistics. Except for a few simple models, these approximations are not available in the framework of stationary time series. We contribute to fill this gap. Under short or long range serial dependence, for Gaussian and non Gaussian processes, we show how to derive and implement saddlepoint approximations for two relevant classes of frequency domain statistics: ratio statistics and Whittle’s estimator. We compare our new approximations to the ones obtained by the standard asymptotic theory and by two widely-applied bootstrap methods. The numerical exercises for Whittle’s estimator show that our approximations yield accuracy’s improvements, while preserving analytical tractability. A real data example concludes the paper.

Keywords: Periodogram; Tilted edgeworth expansion; Macroeconomic time series; Relative error; Whittle’s estimator (search for similar items in EconPapers)
JEL-codes: C01 C02 C22 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:213:y:2019:i:2:p:578-592

DOI: 10.1016/j.jeconom.2018.10.009

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