Arbeitspapier
Estimation and inference for varying-coeffcient models with nonstationary regressors using penalized splines
This paper considers estimation and inference for varying-coefficient models with nonstationary regressors. We propose a nonparametric estimation method using penalized splines, which achieves the same optimal convergence rate as kernel-based methods, but enjoys computation advantages. Utilizing the mixed model representation of penalized splines, we develop a likelihood ratio test statistic for checking the stability of the regression coefficients. We derive both the exact and the asymptotic null distributions of this test statistic. We also demonstrate its optimality by examining its local power performance. These theoretical fundings are well supported by simulation studies.
- Sprache
-
Englisch
- Erschienen in
-
Series: SFB 649 Discussion Paper ; No. 2013-033
- Klassifikation
-
Wirtschaft
Hypothesis Testing: General
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Thema
-
Nonstationary Time Series
Varying-coefficient Model
Likelihood Ratio Test
Penalized Splines
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Chen, Haiqiang
Fang, Ying
Li, Yingxing
- Ereignis
-
Veröffentlichung
- (wer)
-
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
- (wo)
-
Berlin
- (wann)
-
2013
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Chen, Haiqiang
- Fang, Ying
- Li, Yingxing
- Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Entstanden
- 2013
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