4 September 2019
Summer School on Complexity Economics, Behavioral Economics and Data Science
In three parallel tracks, Master students, PhD students and young researchers will be introduced to agent-based modelling, behavioral economics and text mining, as well as to complexity and pluralism in economics. The courses contain both, lectures on essential concepts and hands-on tutorials.
(Pre-)Lecture on Complexity and Pluralism
This talk will give a brief introduction to economic philosophy and will provide students with the analytical tools from the philosophy of science to adequately appreciate the methods to be learned in the upcoming days. The goal is to understand the link between the complexity of economies and the need for pluralism in economic theory as well as to understand the need for a pluralism in economic methodology.
The course gives an introduction to Behavioural Economics. We will discuss alternatives to standard rational choice theory, covering areas such as social preferences, decisions under risk and uncertainty and preferences anomalies. The applied part of the course will cover basics of experimental design and a hands-on demonstration of a software package used for economic lab experiments. Further, participants are introduced to insights of cultural evolution theory and gain a deeper understanding of the cultural roots of human cognition and its impact on decision-making.
The participants of this course will learn to incorporate the insights from complexity economics into (macro-) economic agent-based models (ABMs). In contrast to standard equilibrium models, ABMs view agents as heterogeneous, boundedly rational, interacting individuals. Besides learning the essential concepts of ABM, this course provides students with the programming skills needed to implement their ideas in computer code via NetLogo.
This course will train participants in the main concepts of data science andtext mining in particular. Text mining is the process of analysing collections of textual materials in order to capture key concepts and themes and uncover hidden relationships and trends without the requirement of knowing the precise words or terms that authors have used to express those concepts. Among other techniques, the classes cover text crawling and frequency analysis, basic lexicometrics, term extraction, (un)supervised learning and basic topic models. The course contains an introduction of the basic concepts as well as hands-on tutorials in R-Studio.
(Pre-)Lecture on Complexity and Pluralism: Dr. Claudius Gräbner (ICAE Linz)
Behavioral Economics: Prof. Dr. Christian Cordes (Universität Bremen) and Dr. Wolfgang Luhan (University of Portsmouth)
Agent-Based Modeling: Prof. Dr. Michael Roos and Tom
Interested PhD and Master students as well as young researchers are invited to submit an application containing a letter of motivation (max. 1.5 pages) that specifies the track of interest (agent-based modelling, behavioral economics or data science (text mining)) and a CV. The application should be directed to firstname.lastname@example.org until 30th April 2019.
Providing an introduction to progressive methods and theory in economics as data science, complexity economics and behavioral economics and their application
EUR 0: Participation Fee: 75 EUR for members of the Netzwerk ökonomische Bildung und Beratung e.V. (NÖBB e.V.) and 95 EUR for non-members. Lunches and coffee breaks as well as one social dinner are included. Due to limited funding, we cannot provide support to cover costs for travelling or accommodation.