This paper is a supplementary resource of the forthcoming book:
Convergence clubs characteristics:
Some stylized facts
Convergence framework
Main results of the paper
[ Slides, paper, and video presentation are available at: http://bit.ly/bcde2020 ]
Large and heterogeneous productivity differences across Latin America
Note: Labor productivity is computed as the long-run trend of (log) GDP per worker. The Hodrick-Prescott filter with a smoothing parameter of 6.25 is applied to obtain the long-run trends.
Note: Total factor productivity is computed by dividing GDP per worker by an aggregate index of physical capital and human capital. The Hodrick-Prescott filter with a smoothing parameter of 6.25 is applied to obtain the long-run trends.
Global convergence test (intuition)
Local convergence clubs (intuition)
hit=yit1N∑Ni=1yit
Ht=1NN∑i=1(hit−1)2→0
In other words, when the relative transition parameter converges to unity, hit→1, the cross-sectional variance converges to zero, Ht→0.
log(H1Ht)−2log{log(t)}=a+blog(t)+ϵt
Lack of overall convergence
Multiple convergence clubs above and below the average
Convergence clubs characteristics
https://carlos-mendez.rbind.io
Slides and working paper available at: http://bit.ly/bcde2020
Quantitative Regional and Computational Science lab
This research project was supported by JSPS KAKENHI Grant Number 19K13669
This paper is a supplementary resource of the forthcoming book:
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