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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
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Working Paper: An Integrated Panel Data Approach to Modelling Economic Growth (2019) Downloads
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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

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

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