News & Announcements


An additional lecture on Pandas has been added that covers more advanced functions such as merging, grouping, and using multiindices. Pandas is a powerful Python package that contains useful tools for working with large and complicated datasets. The lecture specifically focuses on techniques useful for working with panel data, with applications to datasets from the OECD and Eurostat.


If you’re considering making the switch over to Python from STATA (or even R), we have a new cheatsheet to help you do so! The cheatsheet compares commonly used functions for data handling and manipulation across STATA, Base R, and the Pandas package for Python.


A Julia version of A Problem that Stumped Milton Friedman is now available. The lecture covers sequential analysis - a technique developed by Abraham Wald to solve decision making problems.


We have added a new lecture (in both Python and Julia) on the endogenous grid method for policy iteration. The EGM algorithm, invented by Chris Carroll, results in significant speed improvements over Coleman policy function iteration.


You can now find three new lectures on the Julia side of QuantEcon lectures covering Globalization and Cycles, Coleman Policy Iteration, and the Lake Model. Additionally, the lectures’ style has been refreshed to make reading code input and output simpler.


Following the lead of the Federal Reserve Bank of New York (FRBNY), an increasing number of central banks have expressed interest in converting their DSGE modeling implementations to Julia. To help meet this demand, QuantEcon ran workshops at the Reserve Bank of Australia and the Reserve Bank of New Zealand on the 10th and 13th of March 2017. They were presented by John Stachurski (QuantEcon and ANU), Pablo Winant (Bank of England), Erica Moszkowski (FRBNY) and Pearl Li (FRBNY). The workshops introduced central bank employees to the Julia programming language and its uses in macroeconomic modeling. Slides from the workshop can be found in the QuantEcon GitHub repository.


The Open Source Macroeconomics Laboratory (OSM Lab) at the Becker Friedman Institute is soliciting applications for a seven week computational macroeconomics boot camp for advanced undergraduate students and some graduate students, to be held at the University of Chicago from June 19 to August 4 of 2017. Funding is available to successful applicants and the QuantEcon lectures will be part of the curriculum. Applications must be submitted by February 17. For further details see


Position descriptions are now available for a PostDoc and a PreDoc. These positions are based at The Australian National University (ANU) in Canberra, Australia. Please send any expressions of interest to


QuantEcon is migrating from the Google Groups based forum to a new discussion forum built on Discourse. The new forum is located at and is also linked through the QuantEcon org and lecture websites. Please feel free to join the conversation, make suggestions for improvements, or tell us what project you’d like to see the QuantEcon team work on next.


A few months ago one of us (the one who’s better at fly fishing) gave a lecture on macroeconomics and computational methods at JuliaCon. The video can be found here. The talk provides a quick overview of the state of modern macroeconomics. It is aimed at a general audience with a background in computation, but will likely be of interest to some economists as well. Discussion centers on formation of beliefs and expectations, modeling of markets and technologies, and associated computational challenges.


A Julia version of the Aiyagari lecture has been added to the site. The code was written by NYU PhD student Victoria Gregory. We are also grateful to contributions from Maximilian Huber and Spencer Lyon.


As mentioned in an earlier news item, QuantEcon has received a large new grant from the Alfred P. Sloan Foundation. Among other things, the grant will allow us to hire a postdoctoral fellow, a pre-doctoral fellow, part time web developers and many new RAs. We will be looking for highly talented programmers with experience using Python, Julia and other open source tools. Formal announcements will go out shortly. In the meantime, please feel free to send your CV and informal expressions of interest to


We are delighted to announce that QuantEcon has received a very generous additional round of funding from the Alfred P. Sloan Foundation. The grant will support many new and existing activities over the coming years. Along with further development of the lecture site and code libraries, we have major plans for revamping the notebook gallery in order to make it more interactive, for building new code libraries, and for supporting a variety of open source scientific projects based around Python and Julia.


Along with several collaborators, we have created an organization called QuantEcon to coordinate developement and documentation of open source software for economists. This lecture site now falls under the QuantEcon umbrella, as a QuantEcon sponsored project. QuantEcon has been accepted as a member of NumFOCUS, a nonprofit that supports open source scientific software development. Other members of NumFOCUS include IPython, Julia, Matplotlib, NumPy, pandas and Jupyter. QuantEcon is run for the benefit of the economics community, and contributions of code, documentation, ideas or developer time are most welcome. The QuantEcon website provides information for anyone who would like to get involved.


On June 16 we’ll be running a workshop based around at the North American summer meeting of the Econometric Society. The workshop will provide a quick start introduction to programming in Python and Julia for economists. The target audience is economists with some experience with programming in Matlab, Stata or similar, who are curious about Python and Julia, and how they might be useful for research in quantitative economics. The workshop page contains further details.


We’ve added a notebook gallery to the QuantEcon organization site in order to collect interesting Jupyter notebooks related to quantitative economics. Please feel free to submit your notebook for possible inclusion. Instructions are available on the notebook page.


I’ve seen the future of central bank forecasting and it’s written in Julia (to paraphrase Jon Landau). That’s right, with a small amount of help from the team at QuantEcon, the FRBNY has converted its main DSGE model from Matlab to Julia. Moreover, the code has been posted on GitHub, a public repository hosting service. This means that anyone can fork their code, mess around with it and suggest changes, using the full power of the open source development ecosystem. This seems like a big win for transparency and open science, while at the same time shifting the FRBNY code base to a cutting edge language and delivering significant speed gains.


The entire Python side of the website has now been updated to Python 3.5, along with all code examples. Our build environment is based on the latest Python 3.5 version of Anaconda. Apart from all the other goodies, this environment includes the @ operator for matrix multiplication, which comes with NumPy 1.10 and above.


A new lecture on discrete dynamic programming has been added to the the Python side of It demonstrates how to exploit some very high quality code for solving infinite horizon discrete dynamic programming problems written by Daisuke Oyama. We plan to develop a Julia version over the next few months. Please get in touch if you are interested in helping out on porting this code to Julia.


A new lecture on uncertainty traps has been added to the the Python side of (Hopefully we’ll get a Julia version up before too long.) The lecture studies a simplified version of a very interesting model due to Pablo Fajgelbaum, Edouard Schaal, and Mathieu Taschereau-Dumouchel. The model shows how self-reinforcing uncertainty can have large impacts on economic activity.


We have added a new lecture on the Python side on default risk and income fluctuations. The lecture computes versions of Cristina Arellano’s popular and important model of sovereign default. A Julia version of the lecture should be out in the next few days.


Our lectures draw heavily on code from two parallel code libraries, and QuantEcon.jl. These libraries have been unified under the QuantEcon project, and a website for the project is now up and running. The code libraries are separate entities from the lectures and are constructed in the usual open source way. All manner of contributions are welcome, from documentation improvements and minor bug fixes to new algorithms and models. More details can be found here. Thanks to Matt McKay and Andrij Stachurski for most of the leg work in getting the new website on line.


After a fair bit of work we’re finally ready to set loose on the world a Julia version of our lectures, as well as a nice new front end for the website. Most credit goes to our talented RAs Chase Coleman, Spencer Lyon and Matt McKay. Credit for the new website design and implementation goes to Andrij Stachurski.


Largely thanks to the efforts of our RAs Chase Coleman and Spencer Lyon, we now have a shiny new on-line documentation page for QuantEcon.


We are delighted to announce that the Alfred P. Sloan Foundation has awarded quant-econ a very generous and helpful grant to support its development. The grant will allow us to spend a large amount of time working together over the coming years, with the objective of building up the code libraries and adding many new applications in all fields of economics and econometrics. It will also fund travel, workshops and conference presentations, and allow us to employ a postdoctoral fellow and a number of research assistants.

We feel very fortunate to be partnering with the outstanding team at the Sloan Foundation, and look forward to seeing quant-econ develop into a important resource for all economists.


The past few weeks have been spent reorganizing the code library, combining the most useful programs into a package called QuantEcon. In practice this means that you can now import quantecon as qe, in just the same way that you import numpy as np. The package can be found on pypi. Details and installation instructions can be found here.

Like the great majority of Python libraries, QuantEcon is open source and we welcome contributions of high quality code for solving important economic models.