class: center, middle, inverse, title-slide # Productivity Differences and Convergence Clubs in Latin America ### Carlos Mendez<br /><a href="https://carlos-mendez.rbind.io" class="uri">https://carlos-mendez.rbind.io</a><br /><br />Associate Professor<br />Graduate School of International Development<br />Nagoya University<br />JAPAN ### Prepared for the 2019 International Joint Conference of JAHSS・JASID <br /><br />[ Slides and paper available at: <a href="http://bit.ly/jasid2019n" class="uri">http://bit.ly/jasid2019n</a> ] --- ## Motivation: - Economic convergence is important for regional cohesion and competitiveness - Inconclusive literature about Latin America: Convergence vs Divergence vs Convergence Clubs (Galvao and Reis-Gomes, 2007; Barrios et. al, 2018; Martin and Vazquez, 2015) - Development potential of Latin America constrained by low productivity (Daude and Fernndez-Arias, 2010; Pages 2010; Restuccia, 2013) ## Research Objective: - (Re)evaluate the convergence hypothesis across economies in Latin America with particular emphasis on productivity differences and the formation of multiple convergence clubs. ## Methods: - Nonlinear dynamic factor model (Phillips and Sul, 2007, 2009) - Clustering algorithm for panel data (Phillips and Sul, 2007, 2009) ## Data: - Labor productivity and total factor productivity (Fernandez-Arias, 2017) - 20 Latin American countries over the 1980-2014 period --- class: middle ## Main Results: 1. **Lack of overall(global) convergence** in both labor productivity and total factor productivity 2. **Multiple local convergence clubs:** above and below the average 3. **Convergence clubs characteristics:** - Labor productivity: **Four clubs** of countries - Total factor productivity: **Three clubs** of countries - Clubs show non-parallel trends: crossings, limited stability, and separating trends - The lowest-productivity club (Honduras and Nicaragua) is diverging from the rest **at the highest speed**. --- class: middle # Outline of this presentation 1. Some stylized facts - Productivity across countries and over time - Heterogeneity across countries and over time 2. Convergence framework - Global convergence test (intuition) - Local convergence clubs (intuition) 3. Main results of the paper - Lack of overall convergence - Multiple convergence clubs above and bellow the average - Convergence clubs characteristics <br /> <br /> [ Slides and paper available at: http://bit.ly/jasid2019n ] --- class: center, middle # (1) Some stylized facts **Productivity heterogeneity across Latin America** Labor productivity Total factor productivity --- class: middle,center ## 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. --- class: middle,center ## Large and heterogeneous productivity differences across Latin America  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. --- class: middle,center ## Are there any signs of overall convergence/divergence or convergence clubs?  --- class: center, middle # (2) Convergence framework Global convergence test (intuition) Local convergence clubs (intuition) --- class: middle # Convergence framework (brief overview) - First, define a relative transition parameter, `\(h_{it}\)`, as `$$h_{it}=\frac{y_{it}}{\frac{1}{N}\sum_{i=1}^{N}y_{it}}$$` - Second, the convergence hypothesis is defined as `$$H_{t}=\frac{1}{N}\sum_{i=1}^{N}\left(h_{it}-1\right)^{2}\rightarrow 0$$` In other words, when the relative transition parameter converges to unity, `\(h_{it}\rightarrow1\)`, the cross-sectional variance converges to zero, `\(H_{t}\rightarrow0\)`. - Thrid, Phillips and Sul (2007) test this hypothesis by using the following log t regression model `$$log\left(\frac{H_{1}}{H_{t}} \right)-2log\left\{ log\left(t\right)\right\} = a+b\:log\left(t\right)+\epsilon_{t}$$` --- class: middle, center # Convergence test (intuition)  --- class: middle, center # Convergence clubs (intuition)  --- class: middle, center # (3) Main results Lack of overall convergence Multiple convergence clubs above and below the average Convergence clubs characteristics --- class: middle, center ## Lack of overall convergence  --- class: middle, center ## Multiple convergence clubs  --- class: middle, center ## Multiple convergence clubs: Above and below the average  --- class: middle, center ## Convergence clubs characteristics: Labor productivity  --- class: middle, center ## Convergence clubs characteristics: Total factor productivity  --- class: middle # Concluding Remarks - Reject the (overall) convergence hypothesis both in terms of labor productivity and total factor productivity - Multiple convergence clubs below and above the mean - The clubs show different convergence speeds and separating tendencies. -The poor economic performance of Honduras and Nicaragua is driving the separation of clubs over time. ## Implications and further research - Convergence clubs may help us identify economies facing similar challenges - Call for better coordination and cooperation policies both within and between clubs - International technology transfer initiatives to improve economic cohesion and competitiveness in Latin America. - Masked behind the low productivity of Latin America, there is still a high degree of heterogeneity that is worth exploring - Next extension: (Re)evaluate the composition of convergence clubs using subnational data, which is to be constructed using satellite nightlight data. --- class: center, middle # Thank you very much for your attention https://carlos-mendez.rbind.io Slides and working paper available at: http://bit.ly/jasid2019n  **Quantitative Regional and Computational Science lab** https://quarcs-lab.rbind.io *** This research project was supported by JSPS KAKENHI Grant Number 19K13669