Liu, Jun M., Chen, Rong and Yao, Qiwei ORCID: 0000-0003-2065-8486 (2010) Nonparametric transfer function models. Journal of Econometrics, 157 (1). pp. 151-164. ISSN 0304-4076
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Abstract
In this paper a class of nonparametric transfer function models is proposed to model nonlinear relationships between 'input' and 'output' time series. The transfer function is smooth with unknown functional forms, and the noise is assumed to be a stationary autoregressive-moving average (ARMA) process. The nonparametric transfer function is estimated jointly with the ARMA parameters. By modelling the correlation in the noise, the transfer function can be estimated more efficiently. The parsimonious ARMA structure improves the estimation efficiency in finite samples. The asymptotic properties of the estimators are investigated. The finite-sample properties are illustrated through simulations and one empirical example.
Item Type: | Article |
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Official URL: | http://www.elsevier.com/locate/jeconom |
Additional Information: | © 2010 Elsevier B.V. |
Divisions: | Statistics |
Subjects: | H Social Sciences > HB Economic Theory Q Science > QA Mathematics |
JEL classification: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C22 - Time-Series Models |
Date Deposited: | 16 Aug 2010 08:45 |
Last Modified: | 01 Oct 2024 03:36 |
URI: | http://eprints.lse.ac.uk/id/eprint/28868 |
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