Kapetanios, G., Serlenga, Laura and Shin, Yongcheol (2021) Estimation and Inference for Multi-dimensional Heterogeneous Panel Datasets with Hierarchical Multi-factor Error Structure. Journal of Econometrics. pp. 504-531. ISSN 0304-4076
Abstract
Given the growing availability of large datasets and following recent research trends on multi-dimensional modelling, we develop three dimensional (3D) panel data models with hierarchical error components that allow for strong cross-sectional dependence through unobserved heterogeneous global and local factors. We propose consistent estimation procedures by extending the common correlated effects (CCE) estimation approach proposed by Pesaran (2006). The standard CCE approach needs to be modified in order to account for the hierarchical factor structure in 3D panels. Further, we provide the associated asymptotic theory, including new nonparametric variance estimators. The validity of the proposed approach is con…rmed by Monte Carlo simulation studies. We also demonstrate the empirical usefulness of the proposed approach through an application to a 3D panel gravity model of bilateral export flows.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Elsevier B.V. All rights reserved. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > Economics and Related Studies (York) |
Depositing User: | Pure (York) |
Date Deposited: | 26 Nov 2018 11:10 |
Last Modified: | 16 Dec 2024 00:09 |
Published Version: | https://doi.org/10.1016/j.jeconom.2020.04.011 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1016/j.jeconom.2020.04.011 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:139172 |