Nonparametric transfer function models

Jun M. Liu, Rong Chen and Qiwei Yao

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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.

Keywords: nonparametric smoothing; time series; transfer function; ISI (search for similar items in EconPapers)
JEL-codes: C14 C22 (search for similar items in EconPapers)
Date: 2010-07
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Citations: View citations in EconPapers (10)

Published in Journal of Econometrics, July, 2010, 157(1), pp. 151-164. ISSN: 0304-4076

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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:28868

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