After studying Commercial Engineering in Bolivia and Chile, I worked as a consultant for Pro-Mujer International, The World Bank, DANIDA, and JICA. I have a M.A. and a Ph.D. in International Development from Nagoya University. My research interests focus on the integration of econometrics, spatial data science, and machine learning methods to understand and inform the process of development of countries, regions, and industries. My current research deals with (1) the quantitative geography of development; (2) regional economic growth and convergence; (3) regional labor markets outcomes and macroeconomic shocks; and (4) structural change and productivity dynamics.
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PhD in International Development, 2015
MA in International Development, 2012
Lic in Commercial Engineering, 2008
Bolivian Catholic University
This book introduces a modern framework to study the cross-country convergence dynamics of labor productivity and its proximate sources: capital accumulation and aggregate efficiency.
Across ASEAN regions, almost 60 percent of the differences in GDP per capita can be predicted by a luminosity-based measure of GDP. Based on this measure, regional inequality within most countries has not significantly decreased, spatial dependence is increasing, and spatial clusters (hotspots and coldspots) cross multiple national boundaries.
The paper incorporates some recent developments from the unsupervised machine learning literature to re-evaluate the cross-country convergence hypothesis in a context beyond GDP. The application of a distribution-based clustering algorithm suggests the formation of three local convergence clubs.