QuantEcon-RSE Intensive Course on Computational Modeling

This is the homepage for the 2019 QuantEcon-RSE Intensive Course on Computational Modeling, jointly organized by the Research School of Economics (RSE) at ANU, QuantEcon and the Australian Treasury.

The event is sposored by RSE.

Location and Dates

The course will be held at Australian National University in Canberra.

Lectures

• Dates: Monday 16th Dec -- Friday 20th Dec 2019
• Hours: 9am -- 5pm, Monday to Friday
• Lecture Room: Fred Gruen Seminar Room, HW Arndt Building, RSE

Social events

• Day 1 Mon 16 Dec -- Welcome Dinner, RSE terrace Courtyard 5-7pm
• Day 4 Thurs 19 Dec -- Workshop Dinner at Badger and Co

Equipment

Participants are expected to bring a laptop with the latest version of Anaconda Python installed.

Prior to Arrival

Prior to arrival, all participants are expected to read and step through all 6 lectures in the section Introduction to Python of the QuantEcon Python lectures.

Please anticipate spending at least one hour per lecture on this task.

All participants are required to sign up to GitHub, since we will be using it to communicate and share code throughout the workshop.

Contacts

• John Stachurski (RSE, ANU, co-organizer)
• Sebastian Wende (Treasury, co-organizer)
• Nicole Millar (RSE, ANU, administration)

Teaching Schedule

There will be a sequence of morning lectures and several ad hoc, informal lectures in the afternoon. Exercises will be provided in the morning lectures and participants are invited to remain in the seminar room for exercises throughout the afternoon. A teaching assistant will be present to provide help.

Morning Lectures (9am--12 noon, Monday to Friday)

Monday: Scientific Python

* Python for scientific computing
* NumPy 
* SciPy
* Matplotlib
* Numba

Tuesday: Introduction to Dynamics

* Coding principles (writing good code)
* Parallelization
* Heavy-tailed distributions
* Dynamics in one dimension
* AR(1) processes

Wednesday: Dynamics and Optimization

* Inventory dynamics
* Kesten processes and firm dynamics
* Wealth dynamics (fixed savings rate)

Thursday: More Dynamic Programming

* Shortest path problems 
* Job search with finite state space
* Job search with separation
* Fitted value function iteration
* Job search with correlated wages

Friday: Structural estimation

* Consumption-savings model
* VFI solution for the model
* Simulating consumption paths
* Method of simulated moments

Afternoon Lectures (4pm--5pm, Monday to Thursday)

• Monday: Introduction to git and GitHub (Matt McKay)
• Tuesday: pandas and data science (Varun Satish)
• Wednesday: Computational modeling at Treasury (Yi Yong Cai and Sebastian Wende)
• Thursday: Computational modeling at the RBA (TBA)