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Daniel Hidalgo is an Associate Professor in the Department of Political Science at the Massachusetts Institute of Technology. He holds a doctorate in Political Science from the University of California, Berkeley, and a BA from Princeton University. His research primarily focuses on the political economy of elections, campaigns, and representation in developing democracies, particularly in Latin America. Hidalgo applies quantitative methods in the social sciences, and his work has been published in prestigious journals including the Journal of Politics, Review of Economic Statistics, and American Journal of Political Science. His recent publications explore themes such as electoral accountability, informal institutions in electoral politics, and the implications of machine learning in political data analysis. With past grants from the National Science Foundation and the Fulbright program, he actively contributes to the field with an emphasis on both methodological rigor and substantive insights.