Chen, Jia orcid.org/0000-0002-2791-2486, Li, Degui orcid.org/0000-0001-6802-308X, Linton, Oliver et al. (1 more author) (2018) Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series. Journal of the American Statistical Association. pp. 919-932. ISSN 0162-1459
Abstract
We propose two semiparametric model averaging schemes for nonlinear dynamic time series regression models with a very large number of covariates including exogenous regressors and autoregressive lags. Our objective is to obtain more accurate estimates and forecasts of time series by using a large number of conditioning variables in a nonparametric way. In the first scheme, we introduce a Kernel Sure Independence Screening (KSIS) technique to screen out the regressors whose marginal regression (or auto-regression) functions do not make a significant contribution to estimating the joint multivariate regression function; we then propose a semiparametric penalized method of Model Averaging MArginal Regression (MAMAR) for the regressors and auto-regressors that survive the screening procedure, to further select the regressors that have significant effects on estimating the multivariate regression function and predicting the future values of the response variable. In the second scheme, we impose an approximate factor modelling structure on the ultra-high dimensional exogenous regressors and use the principal component analysis to estimate the latent common factors; we then apply the penalized MAMAR method to select the estimated common factors and the lags of the response variable that are significant. In each of the two schemes, we construct the optimal combination of the significant marginal regression and auto-regression functions. Asymptotic properties for these two schemes are derived under some regularity conditions. Numerical studies including both simulation and an empirical application to forecasting inflation are given to illustrate the proposed methodology.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 Informa UK Limited. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Mathematics (York) The University of York > Faculty of Social Sciences (York) > Economics and Related Studies (York) |
Depositing User: | Pure (York) |
Date Deposited: | 04 Apr 2017 16:00 |
Last Modified: | 05 Jan 2025 00:13 |
Published Version: | https://doi.org/10.1080/01621459.2017.1302339 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1080/01621459.2017.1302339 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:114572 |