Estimation and Inference for Three-Dimensional Panel Data Models

Guohua Feng Feng (), Jiti Gao, Fei Liu and Bin Peng ()

No 8/24, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: Hierarchical panel data models have recently garnered significant attention. This study contributes to the relevant literature by introducing a novel three-dimensional (3D) hierarchical panel data model, which integrates panel regression with three sets of latent factor structures: one set of global factors and two sets of local factors. Instead of aggregating latent factors from various nodes, as seen in the literature of distributed principal component analysis (PCA), we propose an estimation approach capable of recovering the parameters of interest and disentangling latent factors at different levels and across different dimensions. We establish an asymptotic theory and provide a bootstrap procedure to obtain inference for the parameters of interest while accommodating various types of cross-sectional dependence and time series autocorrelation. Finally, we demonstrate the applicability of our framework by examining productivity convergence in manufacturing industries worldwide.

Keywords: Asymptotic Theory; Bias Correction; Dependent Wild Bootstrap; Hierarchical Model (search for similar items in EconPapers)
JEL-codes: C23 L60 O10 (search for similar items in EconPapers)
Pages: 67
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.monash.edu/business/ebs/research/publications/ebs/2023/wp08-2024.pdf (application/pdf)

Related works:
Working Paper: Estimation and Inference for Three-Dimensional Panel Data Models (2024)
Working Paper: Estimation and Inference for Three-Dimensional Panel Data Models (2023)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:msh:ebswps:2024-8

Ordering information: This working paper can be ordered from
http://business.mona ... -business-statistics

Access Statistics for this paper

More papers in Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics PO Box 11E, Monash University, Victoria 3800, Australia. Contact information at EDIRC.
Bibliographic data for series maintained by Professor Xibin Zhang ().