QuantEcon hosts lecture series on economics, finance, econometrics and data science. All lecture series are based on open source languages and open computing environments.
This book is about dynamic programming and its applications in economics, finance, and adjacent fields like operations research. It brings together recent innovations in the theory of dynamic programming.
This book is an introduction to economic networks and it emphasizes quantitative modeling, with the main underlying tools being graph theory, linear algebra, fixed point theory and programming.
QuantEcon runs remote and in-person workshops and short courses on quantitative economics and high-performance computing using Python and Julia.
Past locations include the Econometric Society meetings, Columbia University, Copenhagen, the Reserve Bank of Australia, Stanford, Princeton, Harvard, MIT, Berkeley, UCLA, Paris and the Central Bank of Chile.
Working for QuantEcon
Natasha is a PhD candidate in Economics at the University of California. During her pre-doctoral fellowship at QuantEcon, Natasha assisted in running workshops on data analysis and econometrics in Python. She has contributed material to QuantEcon lectures, covering the Pandas and Statsmodels libraries, and maintains QuantEcon news and social media.
Flint is a QuantEcon research assistant and student in Economics at Stanford University. His primary interest is in macro-finance and mathematical economics. Flint is working to understand the nature of default and debt as amplification mechanisms in the macroeconomy. He is also a research assistant for QuantEcon and was Professor Stachurski's Honours student at the ANU.
Zejin is a PhD student at the University of Arizona, working on Macro labor economics, understanding people's marital and labor supply decisions. He is a research assistant at QuantEcon and has helped construct lecture notebooks and Python modules.