Inference on the dimension of the nonstationary subspace in functional time series

Morten Ørregaard Nielsen*, Wonk-ki Seo, Dakyung Seong

*Corresponding author af dette arbejde

Publikation: Working paper/Preprint Working paperForskning

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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.
OriginalsprogEngelsk
UdgivelsesstedAarhus
UdgiverÅrhus Universitet
Antal sider38
StatusUdgivet - 24 jan. 2022
NavnCREATES Research Paper
Nummer2022-4

Emneord

  • cointegration
  • functional data
  • nonstationarity
  • stochastic trends
  • variance ratio

Citationsformater