An integrated panel data approach to modelling economic growth

Guohua Feng, Jiti Gao and Bin Peng

Journal of Econometrics, 2022, vol. 228, issue 2, 379-397

Abstract: Empirical growth analysis is plagued with three problems – variable selection, parameter heterogeneity and cross-sectional dependence – which are addressed independently from each other in most studies. This study is to propose an integrated framework that allows for parameter heterogeneity and cross-sectional error dependence, while simultaneously performing variable selection. We derive the asymptotic properties of the estimator, and apply the framework to a dataset of 89 countries over the period from 1960 to 2014. Our results support the “optimistic” conclusion of Sala-I-Martin (1997), and also reveal some cross-country patterns not found previously.

Keywords: Cross-sectional dependence; Growth regressions; Parameter heterogeneity; Variable selection (search for similar items in EconPapers)
JEL-codes: C23 O47 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407621000014
Full text for ScienceDirect subscribers only

Related works:
Working Paper: An Integrated Panel Data Approach to Modelling Economic Growth (2019)
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:eee:econom:v:228:y:2022:i:2:p:379-397

DOI: 10.1016/j.jeconom.2020.09.009

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().