Understanding Income Gaps within Mexico: Place-Specific vs. Individual Factors
Speaker: Tim Cheston
The literature on income gaps between Chiapas and the rest of Mexico revolves around individual factors. Yet, twenty years after the Zapatista rebellion, the schooling gap has shrunk while the income gap has widened, and we find no evidence indicating that Chiapas indigenes are worse-off than their likes elsewhere in Mexico. We explore a different hypothesis. Based on census data, we calculate the economic complexity of Mexico’s municipalities, a measure of knowledge agglomeration. Economic complexity explains a larger fraction of the income gap than any individual factor. Our results suggest that chiapanecos are not the problem; the problem is Chiapas.
The Sense of Us and Agenda for Development
Global Empowerment Meeting (GEM18), April 17-18, 2018
Speaker: Ricardo Hausmann, Professor of the Practice of Economic Development at the Harvard Kennedy School and Director of the Center for International Development at Harvard University
Photo credits:
Erdogan: kafeinkolik / Shutterstock.com
Orban: Alexandros Michailidis / Shutterstock.com
Putin: Nikolay Androsov / Shutterstock.com
Le Pen: Frederic Legrand – COMEO / Shutterstock.com
Farage: david muscroft / Shutterstock.com
Maduro: Marcos Salgado / Shutterstock.com
Trump: Evan El-Amin / Shutterstock.com
Cambridge Analytica: chrisdorney / Shutterstock.com
The Coevolution of State Capability and Economic Development
Global Empowerment Meeting (GEM19), April 9-10, 2019
Speaker: Ricardo Hausmann, Director, Center for International Development; Professor of the Practice of Economic Development, Harvard Kennedy School
Albania’s Strategies for Diaspora Engagement: A Conversation with Pandeli Majko
Pandeli Majko, Albania’s Minister of Diaspora, visited Harvard’s Kennedy School in February 2018 and shared newly set strategies to engage Albania’s diaspora for political and economic development, and transform migration into an added value.
Path to Prosperity: Protectionism or Free Trade?
While the late 1970s were characterized by trade liberalization, Sri Lanka has since increased trade protection, using trade policy as a tool to promote import substitution and local industry. Today, the effective rate of protection is at a similar level as it was in the 1980s, and includes a complex and unpredictable web of paratariffs.
Is protecting local businesses from foreign competition the way forward for Sri Lanka? Or should the country embrace globalization and free trade? In this lecture Professor Robert Lawrence from Harvard University’s Kennedy School of Government explores the topic.
Venezuela: How an Oil Rich Country Went Bust and the Roadmap to Get It Back on Track
Venezuela is currently undergoing the worst economic crisis in its history. By the end of 2016, more than 30% of the gross domestic product (GDP) it had three years ago will be lost. Poverty has soared to record levels. Monthly inflation rates are gradually approaching hyperinflation. Shortages of basic food staples and medicines are rampant. In order to promote a better understanding of the causes, magnitudes, and possible remedies of the crisis, the Center for International Development (CID) at Harvard University launched a research initiative on Venezuela at the end of 2015.
To learn more about this work and some preliminary findings, visit the Venezuela project. Members of our research team shared their experiences and previewed their findings at this seminar, which was held Nov 4, 2016.
Michele Coscia: Building Data-Driven Development
Postdoctoral Fellow, Center for International Development at Harvard University
“Many of the fastest growing companies today in the world and definitely the ones that are shaping the progress of humanity are data intensive companies. Here at CID we have a simple task: we just want to add the rest of the world to the party”.
Coscia’s talk focuses on CID’s efforts to participate on data development of economics and growth.
Sendhil Mullainathan: Machine Intelligence and Public Policy
Powered by large amounts of data, algorithms today can do pretty amazing things; from recognizing faces to understanding language. Remarkably, the engine underneath these feats is a statistical one – combining large amounts of data to produce fundamental statistical insights. If viewed from the correct light, could this same engine be used to transform public policy? Could we leverage approaches designed for facial recognition to shape the way we think about the social sciences? How would these algorithms perform in these alternative settings?
Sendhil Mullainathan, Robert C. Waggoner Professor of Economics in the Faculty of Arts and Sciences at Harvard University
Photo credits
Frisbee photo: (Rommi Saar) [CC BY-SA 3.0 (http://creativecommons.org/licenses/b…)], via Wikimedia Commons
Motorcross photo: Graeme Main/MOD [OGL (http://www.nationalarchives.gov.uk/do…)], via Wikimedia Commons
Dani Rodrik and Tyler Cowen on Economics Rules
After the financial crisis the credibility of the economics profession took a major hit in the public eye. However, it is worthwhile to ask “what failed?” Is the theoretical underpinning of the profession structurally flawed or have some practitioners simply gone astray from the fundamental principles of economic analysis? Understanding what are the intellectual blind spots of economics and how they should be internalized is a key component of a fundamental shift in thinking that is required in the profession in order to responsibly move forward. The future of economics might be better served by avoiding the question of “which is the right model?” alternatively focusing on identifying “which model is appropriate for the specific task at hand.”
Dani Rodrik, Ford Foundation Professor of International Political Economy at the Harvard Kennedy School
Moderated by Tyler Cowen, Holbert L. Harris Professor of Economics at George Mason University and General Director of the Mercatus Center