Inference on the dimension of the nonstationary subspace in functional time series
Morten Nielsen,
Won-Ki Seo (won-ki.seo@sydney.edu.au) and
Dakyung Seong (dakyung.seong@sydney.edu.au)
No 1420, Working Paper from Economics Department, Queen's University
Abstract:
We propose a statistical procedure to determine the dimension of the nonstationary subspace of cointegrated functional time series taking values in the Hilbert space of square-integrable functions defined on a compact interval. The procedure is based on sequential application of a proposed test for the dimension of the nonstationary subspace. To avoid estimation of the long-run covariance operator, our test is based on a variance ratio-type statistic. We derive the asymptotic null distribution and prove consistency of the test. Monte Carlo simulations show good performance of our test and provide evidence that it outperforms the existing testing procedure. We apply our methodology to three empirical examples: age-specific US employment rates, Australian temperature curves, and Ontario electricity demand.
Keywords: cointegration; functional data; nonstationarity; stochastic trends; variance ratio (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2020-10
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
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Citations: View citations in EconPapers (1)
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https://www.econ.queensu.ca/sites/econ.queensu.ca/files/wpaper/qed_wp_1420.pdf First version 2020 (application/pdf)
Related works:
Journal Article: INFERENCE ON THE DIMENSION OF THE NONSTATIONARY SUBSPACE IN FUNCTIONAL TIME SERIES (2023)
Working Paper: Inference on the dimension of the nonstationary subspace in functional time series (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:qed:wpaper:1420
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