An integrated panel data approach to modelling economic growth

Guohua Feng, Jiti Gao, Bin Peng

Research output: Contribution to journalArticleResearchpeer-review

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.

Original languageEnglish
Number of pages19
JournalJournal of Econometrics
DOIs
Publication statusAccepted/In press - 2021

Keywords

  • Cross-sectional dependence
  • Growth regressions
  • Parameter heterogeneity
  • Variable selection

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