Document Type

Working Paper

Date

Spring 4-2019

Keywords

Structural Changes, Heterogeneous Panels, Common Correlated Effects, Endogeneity

Language

English

Funding ID

M4011314

Acknowledgements

The authors would like to thank the editor Herman van Dijk and two anonymous referees for their constructive comments and suggestions. We are also grateful to helpful comments from Otilia Boldea, Le-yu Chen, Xu Cheng, Shigeyuki Hamori, Kazuhiko Hayakawa, Eiji Kurozumi, Wenjie Wang, Yohei Yamamoto, and participants of seminars at Academia Sinica, Hiroshima University, Hitotsubashi University, Kobe University, University of Connecticut and from the 2016 Econometric Society North American Summer Meeting in Philadelphia, 2016 China Meeting of Econometric Society in Chengdu, XIth World Conference of the Spatial Econometrics Association (SEA2017) in Singapore, 2017 Singapore Economic Review Conference, 2018 International Panel Data Conference in Seoul. Financial support from the MOE AcRF Tier 1 Grant M4011314 at Nanyang Technological University is gratefully acknowledged.

Disciplines

Economic Policy | Economics | Public Affairs, Public Policy and Public Administration

Description/Abstract

This paper extends Pesaran (2006) common correlated e¤ects (CCE) by allowing for endogenous regressors in large heterogeneous panels with unknown common structural changes in slopes and error factor structure. Since endogenous regressors and structural breaks are often encountered in empirical studies with large panels, this extension makes the Pesaran’s (2006) CCE approach empirically more appealing. In addition to allowing for slope heterogeneity and cross-sectional dependence, we find that Pesaran’s CCE approach is also valid when dealing with unobservable factors in the presence of endogenous regressors and structural changes in slopes and error factor loadings. This is supported by Monte Carlo experiments.

ISSN

1525-3066

Additional Information

Working paper no. 214

Source

Local input

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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