Details
| Original language | English |
|---|---|
| Pages (from-to) | 78-94 |
| Number of pages | 17 |
| Journal | Econometrics and Statistics |
| Volume | 9 |
| Early online date | 31 Jan 2018 |
| Publication status | Published - Jan 2019 |
Abstract
An automatic model order selection procedure for k-factor Gegenbauer processes is proposed. The procedure is based on sequential tests of the maximum of the periodogram and semiparametric estimators of the model parameters. As a byproduct, a generalized version of Walker's large sample g-test is introduced that allows to test for persistent periodicity in stationary short memory processes. Simulation studies show that the model order selection procedure performs well in identifying the correct order under various circumstances. An application to Californian electricity load data illustrates its value in empirical analyses and allows new insights into the periodicity of this process that has been the subject of several studies.
Keywords
- Electricity loads, k-factor Gegenbauer processes, Model selection, Seasonal long memory
ASJC Scopus subject areas
- Mathematics(all)
- Statistics and Probability
- Economics, Econometrics and Finance(all)
- Economics and Econometrics
- Decision Sciences(all)
- Statistics, Probability and Uncertainty
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In: Econometrics and Statistics, Vol. 9, 01.2019, p. 78-94.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Model order selection in periodic long memory models
AU - Leschinski, Christian
AU - Sibbertsen, Philipp
N1 - Funding information: We are grateful to Liudas Giraitis, Uwe Hassler and the participants of the NSVCM 2014 Workshop in Paderborn for their helpful remarks on earlier versions of this paper. The financial support of DFG SI 745/9-2 is gratefully acknowledged.
PY - 2019/1
Y1 - 2019/1
N2 - An automatic model order selection procedure for k-factor Gegenbauer processes is proposed. The procedure is based on sequential tests of the maximum of the periodogram and semiparametric estimators of the model parameters. As a byproduct, a generalized version of Walker's large sample g-test is introduced that allows to test for persistent periodicity in stationary short memory processes. Simulation studies show that the model order selection procedure performs well in identifying the correct order under various circumstances. An application to Californian electricity load data illustrates its value in empirical analyses and allows new insights into the periodicity of this process that has been the subject of several studies.
AB - An automatic model order selection procedure for k-factor Gegenbauer processes is proposed. The procedure is based on sequential tests of the maximum of the periodogram and semiparametric estimators of the model parameters. As a byproduct, a generalized version of Walker's large sample g-test is introduced that allows to test for persistent periodicity in stationary short memory processes. Simulation studies show that the model order selection procedure performs well in identifying the correct order under various circumstances. An application to Californian electricity load data illustrates its value in empirical analyses and allows new insights into the periodicity of this process that has been the subject of several studies.
KW - Electricity loads
KW - k-factor Gegenbauer processes
KW - Model selection
KW - Seasonal long memory
UR - http://www.scopus.com/inward/record.url?scp=85044716973&partnerID=8YFLogxK
U2 - 10.1016/j.ecosta.2017.11.002
DO - 10.1016/j.ecosta.2017.11.002
M3 - Article
AN - SCOPUS:85044716973
VL - 9
SP - 78
EP - 94
JO - Econometrics and Statistics
JF - Econometrics and Statistics
ER -