Publication Type

Journal Article

Version

acceptedVersion

Publication Date

9-2007

Abstract

A new econometric approach to testing for economic growth convergence is overviewed. The method is applicable to panel data, involves a simple regression based one-sided t-test, and can be used to form a clustering algorithm to assess the existence of growth convergence clubs. The approach allows for heterogeneous technology, utilizes some new asymptotic theory for nonlinear dynamic factor models, and is easy to implement. Some background growth theory is given which shows the form of augmented Solow regression (ASR) equations in the presence of heterogeneous technology and explains sources of potential misspecification that can arise in conventional formulations of ASR equations that are used to analyze growth convergence and growth determinants. A short empirical application is given illustrating some aspects of the methodology involving technological heterogeneity and learning in growth patterns for selected groups of countries.

Keywords

Convergence parameter, Conditional convergence, Determinants of growth, Economic growth, Growth convergence, Heterogeneity, Learning, Neoclassical economics, Speed of learning, Transition curve, Transitional divergence

Discipline

Econometrics | Macroeconomics

Research Areas

Econometrics

Publication

Journal of Macroeconomics

Volume

29

Issue

3

First Page

455

Last Page

469

ISSN

0164-0704

Identifier

10.1016/j.jmacro.2007.03.002

Publisher

Elsevier

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1016/j.jmacro.2007.03.002

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