An Integrated Panel Data Approach to Modelling Economic Growth

Guohua Feng (), Jiti Gao () and Bin Peng ()

No 6/19, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: Empirical growth analysis has three major problems -- variable selection, parameter heterogeneity and cross-sectional dependence -- which are addressed independently from each other in most studies. The purpose of this study is to propose an integrated framework that extends the conventional linear growth regression model to allow for parameter heterogeneity and cross-sectional error dependence, while simultaneously performing variable selection. We also derive the asymptotic properties of the estimator under both low and high dimensions, and furtherinvestigate the finite sample performance of the estimator through Monte Carlo simulations. We apply the framework to a dataset of 89 countries over the period from 1960 to 2014. Our results reveal some cross-country patterns not found in previous studies (e.g., "middle income trap hypothesis", "natural resources curse hypothesis", "religion works via belief, not practice", etc.).

Keywords: growth regressions; variable selection; parameter heterogeneity; cross-sectional dependence. (search for similar items in EconPapers)
JEL-codes: C23 O47 (search for similar items in EconPapers)
Pages: 70
Date: 2019
New Economics Papers: this item is included in nep-gro
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Citations: View citations in EconPapers (3)

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