Modelling in the presence of cross-sectional error dependence

George Kapetanios; Camilla Mastromarco; Laura Serlenga; Yongcheol Shin

doi:10.1007/978-3-319-60783-2_10

Modelling in the presence of cross-sectional error dependence

George Kapetanios^*, Camilla Mastromarco, Laura Serlenga, Yongcheol Shin

^*Corresponding author for this work

King's Business School

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

5 Citations (Scopus)

Abstract

Given the growing availability of big datasets which contain information on multiple dimensions and following the recent research trend on multidimensional modelling, we develop three-dimensional panel data models with threeway error components that allow for strong cross-sectional dependence (CSD) through unobserved heterogeneous global factors, and propose appropriate consistent estimation procedures. We also discuss the extent of CSD in 3D models and provide a diagnostic test for cross-sectional dependence. We provide the extensions to unbalanced panels and 4D models. The validity of the proposed approach is confirmed by the Monte Carlo simulation results. We also demonstrate the empirical usefulness through the application to the 3D panel gravity model of the intra-EU trade flows.

Original language	English
Title of host publication	Advanced Studies in Theoretical and Applied Econometrics
Publisher	SPRINGER
Pages	291-322
Number of pages	32
DOIs	https://doi.org/10.1007/978-3-319-60783-2_10
Publication status	Published - 1 Jan 2017

Publication series

Name	Advanced Studies in Theoretical and Applied Econometrics
Volume	50
ISSN (Print)	1570-5811
ISSN (Electronic)	2214-7977

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10.1007/978-3-319-60783-2_10

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Modelling in the presence of cross-sectional error dependence. / Kapetanios, George; Mastromarco, Camilla; Serlenga, Laura et al.
Advanced Studies in Theoretical and Applied Econometrics. SPRINGER, 2017. p. 291-322 (Advanced Studies in Theoretical and Applied Econometrics; Vol. 50).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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AB - Given the growing availability of big datasets which contain information on multiple dimensions and following the recent research trend on multidimensional modelling, we develop three-dimensional panel data models with threeway error components that allow for strong cross-sectional dependence (CSD) through unobserved heterogeneous global factors, and propose appropriate consistent estimation procedures. We also discuss the extent of CSD in 3D models and provide a diagnostic test for cross-sectional dependence. We provide the extensions to unbalanced panels and 4D models. The validity of the proposed approach is confirmed by the Monte Carlo simulation results. We also demonstrate the empirical usefulness through the application to the 3D panel gravity model of the intra-EU trade flows.

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Modelling in the presence of cross-sectional error dependence

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