SEEC

29/10/2017

ESONERATO!

DOPO L'ENNESIMA SCONFITTA, IL MILAN SORPRENDE TUTTI E PRENDERE LA DECISIONE!

E' UFFICIALE: http://bit.ly/ESONERO-MILAN

22/04/2017

Summer School in Computational Econometrics

05/04/2017

Workshop in Computational Econometrics 2017
Lecce - Dipartimento di Scienze dell'Economia
July 24, 2017 – July 28, 2017

The main aim of this 25 hours course is to provide an introduction to working with Matlab and Python.
The approach is problem based, i.e. students will be made familiar with the software using well-known examples from applied macroeconomics/-econometrics.
The 10 lectures will give an introduction to the examples and the required programming tools.
Participants are expected to have a solid background in time series econometrics.
Preparation for the course: Favero (2001), Chapter 6.
Lecturer:
Prof. Ulrich Woitek
Department of Economics, University of Zurich, Zürichbergstr. 14, 8032 Zurich, email: [email protected]

Material:

Python: www.python.org
Anaconda: www.continuum.io/downloads
Spyder (IDE): www.github.com/spyder-ide/spyder
Course Quantitative Economics (Thomas J. Sargent and John Stachurski): quant-econ.net
Reproducible research projects in economics (Hans-Martin von Gaudecker): wiwi.uni-bonn.de/gaudecker/computing_resources.html
References:
Favero, C. A. (2001), Applied Macroeconometrics. Oxford: Oxford University Press.

Over the course of teaching several classes using Python for programming and/or econometric analyses, I have compiled a set of instructions for setting up an environment that is useful for economic research. You may find it