QuantEcon is a @NumFOCUS fiscally sponsored project dedicated to developing open source computational tools for economics. Supported by the @SloanFoundation.
Tom and I have finally finished a draft of Dynamic Programming Vol 2! Exhausting but satisfying. New approach to DP theory, advanced material, many applications... https://t.co/PPDk98DFgV
Thrilled to share a project I've been refining: a complete, open-source repository on "Deep Learning for Solving and Estimating Dynamic Models in Economics and Finance."
I've cleaned up the materials from my PhD classes and summer schools into one coherent resource. 🧵 1/6
I know we shouldn't be driven by desire for accolades but I am proud of this one. Maybe I didn't entirely waste my short moment of time on this beautiful planet 🥹❤️ https://t.co/BKW3aMxAfq @SocCompEcon
We added a new and final chapter to Dynamic Programming Vol II (DP2) on approximation and reinforcement learning: https://t.co/PPDk98DFgV. DP1 and DP2 will always remain freely available online -- give me liberty or give me death 🤟💀
In the latest @QuantEcon Julia release, you can now launch notebooks directly in @GoogleColab.
Just click ▶️ on the online lecture to open it in Colab.
On first run, the notebook automatically installs all required packages.
Super happy to see Dynamic Programming by Sargent & Stachurski out in the world — rigorous, elegant, and full of applications. A beautiful piece of work❣️❣️❣️
Dynamic Programming by Thomas J Sargent and John Stachurski
Provides a rigorous and unified presentation of recent advances in dynamic programming, along with code, algorithms, and many applications.
📚 https://t.co/5k26qTjsj5
From hours to seconds 🤯. An economist from @QuantEcon tells the story of how JAX's simple and expressive API transformed a critical economic model for the Central Bank of Chile, making high performance accessible. #JAX#SciComp#Economics#Python
https://t.co/m1SVuOFr1B
The tentative program for the summer school/conference on "Deep Learning in Economics and Finance (August 25-29)" is online: https://t.co/QFxxce3L5z, and https://t.co/PUcv25Mhem @YuchengYang1993@glviolante@unito@nuvoloscloud
I added a notebook to @QuantEcon Notes. It shows how to use Julia JuMP for OLS and ML estimations.
Of course the purpose of the document is not to argue that we should use JuMP for OLS or ML! I wanted to see how JuMP could accommodate estimations with data.
@QuantEcon has released an updated version of the Julia lecture notes, with updated manifests and packages for Julia 1.11 support: https://t.co/QgudW2C6dc
You don't hear very often this kind of reflections on economics' methodology. So interesting to hear Tom Sargent talking about Lucas' approach to macro (today at NYU)
https://t.co/PFgmIDG68g