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An integrated panel data approach to modelling economic growth

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  • Feng, Guohua
  • Gao, Jiti
  • Peng, Bin

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.

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  • Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
  • Handle: RePEc:eee:econom:v:228:y:2022:i:2:p:379-397
    DOI: 10.1016/j.jeconom.2020.09.009
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    Cited by:

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    2. Robert C. M. Beyer & Konstantin M. Wacker, 2024. "Good enough for outstanding growth: The experience of Bangladesh in comparative perspective," Development Policy Review, Overseas Development Institute, vol. 42(2), March.
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    More about this item

    Keywords

    Cross-sectional dependence; Growth regressions; Parameter heterogeneity; Variable selection;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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