Alberto Simpser
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Alberto Simpser
Alberto Simpser is a professor and researcher in the Department of Political Science at ITAM, with affiliations to the Center for Economic Research (CIE) and the Center for Energy and Natural Resources (CIERN). Prior to joining ITAM in 2014, he was a faculty at the Department of Political Science at the University of Chicago. He has been a residential Fellow at the Institute for Advanced Study of Toulouse at the Toulouse School of Economics, a Fellow at the Niehaus Center for Globalization and Governance at Princeton University, and a National Fellow at the Hoover Institution at Stanford University. Currently, he is a member of the National System of Researchers in Mexico with Level I. He holds a Ph.D. in Political Science and a Master’s in Economics from Stanford University, and a Bachelor's degree in Environmental Engineering from Harvard College. Before entering academia, he worked on energy issues at McKinsey & Co.
His research addresses politico-economic problems in developing countries, including corruption, electoral manipulation, governance and accountability failures, and the relationship between institutions, culture, and behavior. His research has been published in journals such as the American Political Science Review, American Journal of Political Science, Journal of Politics, Journal of Public Economics, Journal of the European Economic Association, and Annual Review of Political Science, among others. His books, Why Governments and Parties Manipulate Elections and Constitutions in Authoritarian Regimes (co-edited with Professor Tom Ginsburg), have been published in different series by Cambridge University Press. He has served on the Council of the American Political Science Association and the Planning Committee of the Comparative Study of Electoral Systems; he is currently a member of the Advisory Board of the Latin American Public Opinion Project and an Affiliate of J-PAL.
Academic Studies
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Topics of Interest
- Political Economy
- Political psychology
- Corruption
- electoral fraud
- causal inference and experimental methods