unit root;
nonlinear shift;
autoregressive process;
D O I:
10.1111/1467-9892.00285
中图分类号:
O1 [数学];
学科分类号:
0701 ;
070101 ;
摘要:
Unit root tests are considered for time series Which have a level shift at a known point in time. The shift can have a very general nonlinear form, and additional deterministic mean and trend terms are allowed for. Prior to the tests, the deterministic parts and other nuisance parameters of the data generation process are estimated in a first step., Then, the series are adjusted for these terms and unit root tests of the Dickey-Fuller type are applied to the adjusted series. The properties of previously suggested tests of this sort are analysed and modifications are proposed which take into account estimation errors in the nuisance parameters. An important result is that estimation under the null hypothesis is preferable to estimation under local alternatives. This contrasts with results obtained by other authors for time series without level shifts.
机构:
Univ Barcelona, Dept Econometr Stat & Appl Econ, AQR IREA Res Grp, Barcelona 08034, SpainUniv Barcelona, Dept Econometr Stat & Appl Econ, AQR IREA Res Grp, Barcelona 08034, Spain
Carrion-i-Silvestre, Josep Lluis
Gadea, Maria Dolores
论文数: 0引用数: 0
h-index: 0
机构:
Univ Zaragoza, Dept Appl Econ, Zaragoza, Spain
Univ Zaragoza, Dept Appl Econ, Gran Via 4, Zaragoza 50005, SpainUniv Barcelona, Dept Econometr Stat & Appl Econ, AQR IREA Res Grp, Barcelona 08034, Spain
机构:
Sun Yat Sen Univ, Sch Business, Guangzhou 510275, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Business, Guangzhou 510275, Guangdong, Peoples R China
Wang Guiyin
Zhang Jingyu
论文数: 0引用数: 0
h-index: 0
机构:
Nanjing Univ, Sch Software, Nanjing 210000, Jiangsu, Peoples R ChinaSun Yat Sen Univ, Sch Business, Guangzhou 510275, Guangdong, Peoples R China
Zhang Jingyu
Li Yong
论文数: 0引用数: 0
h-index: 0
机构:
Sun Yat Sen Univ, Sch Business, Guangzhou 510275, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Business, Guangzhou 510275, Guangdong, Peoples R China
Li Yong
DATA PROCESSING AND QUANTITATIVE ECONOMY MODELING,
2010,
: 517
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