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Truncated sum of squares estimation of fractional time series models with deterministic trends

Javier Hualde () and Morten Nielsen
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Javier Hualde: Universidad Pública de Navarra, Postal: Department of Economics, Universidad Pública de Navarra, Campus Arrosadia, 31006 Pamplona, Spain

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

Abstract: We consider truncated (or conditional) sum of squares estimation of a parametric model composed of a fractional time series and an additive generalized polynomial trend. Both the memory parameter, which characterizes the behaviour of the stochastic component of the model, and the exponent parameter, which drives the shape of the deterministic component, are considered not only unknown real numbers, but also lying in arbitrarily large (but finite) intervals. Thus, our model captures different forms of nonstationarity and noninvertibility. As in related settings, the proof of consistency (which is a prerequisite for proving asymptotic normality) is challenging due to non-uniform convergence of the objective function over a large admissible parameter space, but, in addition, our framework is substantially more involved due to the competition between stochastic and deterministic components. We establish consistency and asymptotic normality under quite general circumstances, finding that results differ crucially depending on the relative strength of the deterministic and stochastic components. Finite-sample properties are illustrated by means of a Monte Carlo experiment.

Keywords: Asymptotic normality; consistency; deterministic trend; fractional process; generalized polynomial trend; noninvertibility; nonstationarity; truncated sum of squares estimation (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Pages: 70
Date: 2020-06-26
New Economics Papers: this item is included in nep-ore
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Citations: View citations in EconPapers (7)

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Related works:
Journal Article: TRUNCATED SUM OF SQUARES ESTIMATION OF FRACTIONAL TIME SERIES MODELS WITH DETERMINISTIC TRENDS (2020) Downloads
Working Paper: Truncated Sum Of Squares Estimation Of Fractional Time Series Models With Deterministic Trends (2019) Downloads
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