An integrated panel data approach to modelling economic growth
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 cros...
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| Veröffentlicht in: | Journal of econometrics 2022-06, Vol.228 (2), p.379-397 |
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| container_end_page | 397 |
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| container_issue | 2 |
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| container_title | Journal of econometrics |
| container_volume | 228 |
| creator | Feng, Guohua Gao, Jiti Peng, Bin |
| description | 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. |
| doi_str_mv | 10.1016/j.jeconom.2020.09.009 |
| format | Article |
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| ispartof | Journal of econometrics, 2022-06, Vol.228 (2), p.379-397 |
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| language | eng |
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| source | Access via ScienceDirect (Elsevier) |
| subjects | Asymptotic methods Cross-sectional dependence Econometrics Economic growth Growth regressions Longitudinal studies Optimism Panel data Parameter heterogeneity Regression analysis Variable selection |
| title | An integrated panel data approach to modelling economic growth |
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