pablo a. astudillo-estévez
exploring how economies and places evolve, learn and innovate #geography #economics #datascience
Pablo Astudillo-Estevez is a doctoral researcher in Economic Geography and Complexity Economics at the University of Oxford. Former research fellow at the Growth Lab at Harvard University, and visiting fellow at the Massachussets Institute of Technology's Media Lab. His main interest lies in understanding how economies and places evolve, learn and finding ways to unlock their potential to create knowledge and innovate. More specifically, by analyzing massive data sets, Pablo studies the dynamics of the economic landscape that enable places (specially in the Global South) to become innovative and to climb the technology ladder.
Pablo is a Senior Data Scientist in the Technology and Start-Up Ecosystem Project at the World Bank - IBRD, have worked as consultant for the Inter-American Development Bank, and also advices governments and the private sector on ways to develop the foundations for sustainable, technology-enabled economies as well as to harness the power of disruptive technology and data to solve development challenges.
Pablo has more than 12 years of experience in sustainable development and climate change. He was part of the Ecuadorian delegation that negotiated the UN Sustainable Development Goals in Rio + 20 and the Paris Agreement at COP 21. Winner of the World Bank’s Development Prize - Ecuador and several academic awards.
Pablo has worked and/or lived in more than 15 countries in 5 continents. He practices archery and enjoys playing the piano and the bass guitar.
/ featured projects /
Towards the 4th Industrial Revolution: Production networks, diversification and geography
In this project, we explore how countries can diversify their economies and transform their technological base to embrace the 4th Industrial Revolution.
Based on millions of data points on single transactions between all the firms located in an oil exporting country, we use state-of-the-art tools for analyzing economic data such as network analysis to reconstruct the productive network of the whole country and generate scenarios to identify the potential areas for diversification. We also combine Geographic Information System to understand the interactions between productive network and regional dynamics. Finally, we use artificial intelligence tools to recreate scenarios and potentially predict the emergence of new economic [business] activities.
Augmented Reality for Economic and Business Insights
With the advent of 5G technology, AR combined with AI will increase the potential to analyze data and interact in real time.
In this project, we explore the possible uses of combining AR and AI to provide interactive and real time analyses to support strategic decision making for business and governments, based on large datasets."
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Vietnam's HCMC Growth and Export Potential
Ecuador's 1972 Oil Boom Structural Economic Impact (Data)
Identification of Physical Infrastructure Development
/ research /
economics and place
Economic and place dynamics are deeply intertwined. The political, historical, sociocultural and biophysical characteristics of a location are determinants for economic growth. These components should be analyzed together to understand the evolution and development of an economy and place on different scales.
My work aims to understand the entanglements, how the various elements interact with each other and steer the development of a place. Currently, I study crude oil-exporting developing-economies, how their economic structures have evolved over time and how they become heavily dependent on natural resources extraction. My main goal is to find ways to help these countries to diversify towards other productive activities.
complex systems and networks
"We are being controlled by the random outcome of a complex system"
Jacob Samiel, THE NEW YORKER
The economy is a dynamic system, which is constantly evolving, learning and out of equilibrium. It follows non-linear behaviors and it is path- and place-dependent. Its components can not be studied separately because economic actors interact with and depend on each other to create aggregate behaviors.
My work focuses on the study of firms and their productions chains, network configurations and how their spatial locations influence the creation of new economic activities. My goal is to predict where new firms might emerge and assess where investments could be allocated to foster future economic diversification.
Data on human dynamics can be turn into information, and information into economic insights.
In my research, I study and handle hundreds-of-millions of data points on individual firm transactions to understand how production networks work and evolve, as well as the patterns of economic specialization and diversification in regions. Further, with the use of the state-of-the-art data analysis tools, I attempt to predict the evolution of economic spaces and where new productive activities (entrepreneurship) may emerge.
CHINA - Productive Structure Evolution
USA - Productive Structure Evolution
/ resources /
Kate Crawford is a leading researcher and professor who has spent the last decade studying the social implications of data systems, machine learning and artificial intelligence. She is the co-director and co-founder of the AI Now Institute at New York University.
The Atlas of Economic Complexity (2014)
Hausmann, R., Hidalgo C., et al.
¨Economic Complexity," a measure of a society's productive knowledge
National Bureau of Economic Research
Director of the Complexity Economics program.
His current research is in economics, including agent-based modeling, financial instability and technological progress.