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PhD Week October 2012

The next IIDEOS PhD course will take place at Marburg University from 8th to 12th October 2012.


1. Program Overview

Below you can find the program for the PhD course.

Mon, 8th
09:00 - 12:30 
 Introduction to R
 Supervisor: Holger Graf
 Necessary for the PhD course on Network Analysis (for those without experience in R).
Mon, 8th
13:30 -
Wed, 10th
17:00
 PhD course: "Network Analysis"
 Lecturer: Holger Graf
Thu, 11th
& Fri, 12th

09:00 - 17:00

 PhD course: Statistics and Causality
 Lecturer: Alessio Moneta

2. Registration and course fees

If you are interested in attending the event, please contact iideos@uni-marburg.de, stating your full name, the university you are enrolled as PhD student, and which courses you would like to attend.

Some PhD presentations will be integrated in the program. If you would like to present your PhD project, please indicate this intention together with a very short outline of the project and the current status in your email.

The program fee is 50 € for the entire week, regardless of the number of courses you attend.

Responsible for the PhD program IIDEOS:

Prof. Dr. Dr. Thomas Brenner
Deutschhausstr. 10
35032 Marburg
Tel.: (0049) (0)6421 2824211
Fax: (0049) (0)6421 2828950

 

3. Introduction to R

Supervisor:  PD Dr. Holger Graf, Friedrich Schiller University Jena
Room:   00A12 (Carolinenhaus)
Time:   Mon, 8th, 09:00 - 12:30

Necessary for the PhD course on Network Analysis (for those without experience in R).

4. "Network Analysis" (12 vacancies)

Lecturer:   PD Dr. Holger Graf, Friedrich Schiller University Jena
Room:    00A12 (Carolinenhaus)
Time:   Mon, 8th, 13:30 - Wed, 10th, 17:00

Innovation is an interactive process in which actors create novelty by drawing on existing, internal and external, knowledge. Increasingly, actors collaborate in this process and thereby form innovation networks, which have received growing interest during the past decades:

  • How are these networks formed and how do they evolve over time?
  • What is the influence of actors' positions within the network on the amount and kind of knowledge that can be acquired and on their subsequent performance?
  • How is the system performance shaped by network structure?

The purpose of this lecture is to present an overview of theories, concepts, and methods as a prerequisite to analyse social networks with an emphasis on innovation networks.
As a methodological course, the focus will be on relational data and on some popular software tools for the analysis of social networks.

5. "Causality in Econometrics" (number of participants is not limited)

Lecturer:  Alessio Moneta, Scuola Superiore Sant'Anna, Pisa, Italy
Room:
 01A03 (Carolinenhaus)
Time:  Thu, 11th & Fri, 12th, 09:00 - 17:00

Goal of the lecture is to familiarize participants with the problem of causal inference in empirical economics and to present methods that adress this problem. Topics to be covered in the course are:

  • Introduction to the main methodological approaches to causality in economics (structuralist vs. probabilistic accounts)
  • Causal inference based on graphical causal models
  • Application of graphical causal models to time series data (in the framework of Vector Autoregressions)