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Nonparametric transfer function models

Liu, Jun M., Chen, Rong and Yao, Qiwei (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
Official URL: http://www.elsevier.com/locate/jeconom
Additional Information: © 2010 Elsevier B.V.
Library of Congress subject classification: H Social Sciences > HB Economic Theory
Q Science > QA Mathematics
Journal of Economic Literature Classification System: 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
Sets: Collections > Economists Online
Departments > Statistics
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Identification Number: UT ISI:000278781400014
Date Deposited: 16 Aug 2010 08:45
URL: http://eprints.lse.ac.uk/28868/

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