This paper reviews the econometric methodology on panel data estimation and testing as applied to the study of convergence in growth empirics. The concept of absolute convergence states that the poorer economies should be growing at a faster rate, catching up the richer ones. The empirical failure of absolute convergence resulted in the development of alternative theories to explain long-term growth: the endogenous growth theories and the conditional convergence, the idea that countries may have different steady-states and it is the distance from their own steady-state that determines the rate of economic growth. This paper focuses on conditional convergence and its empirical testing. It discusses and compares the different econometric methodologies used in cross-section and panel data studies of conditional convergence. Also presented are the empirical results obtained by the various authors.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Paper provided by Universidade Nova de Lisboa, Faculdade de Economia in its series FEUNL Working Paper Series with number
wp518.
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.: