Juan D Carrillo
استاد · Neuroeconomic Theory
Ifo Institute - Leibniz Institute for Economic Research at the University of Munichمعرفی
Juan D Carrillo is a Professor of Economics at the University of Southern California, a Research Fellow in the Organizational Economics Programme of the Center for Economic Policy Research (CEPR), and Co-Director of the Theoretical Research in Neuroeconomic Decision-making (TREND) Institute.
His educational background includes:
- Graduate of Universidad Complutense de Madrid (1992)
- Master in Statistics from Harvard University (1993)
- PhD in Economics from Toulouse University (1996)
Carrillo specializes in neuroeconomic theory, microeconomic theory, and experimental economics, with particular focus on how cognitive development affects economic decision-making across age groups. His research employs interdisciplinary approaches combining economics, neuroscience, and psychology to understand the bounds of rationality in human behavior.
His publication record shows a consistent trajectory of research on strategic thinking development, with particular emphasis on children and adolescents. The work demonstrates how contextual factors like stress influence decision-making processes in economic games and portfolio choices. His research bridges theoretical economic models with empirical findings from neuroscience.
His scientific recognition includes:
- Research Fellow position at CEPR's Organizational Economics Programme
- Co-Directorship of the TREND Institute
- Multiple publications in respected economics discussion paper series
Carrillo has edited two books at the intersection of psychology and economics, contributing to the theoretical foundations of neuroeconomics. His work has implications for understanding developmental aspects of economic behavior and designing interventions that account for cognitive limitations at different life stages.
As Co-Director of the TREND Institute, Carrillo leads research initiatives that bring together economists, neuroscientists, and psychologists to advance our understanding of decision-making processes through both theoretical modeling and experimental approaches.
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