At the end of this course, you are able to
(Theory)
- identify, explain, and relate (to current development and debates) the most important ideas, theories, and concepts
- identify and distinguish the concepts of behavioural economics research
- discriminate between traditional economics concepts and behavioural economics concepts
- identify the behavioural bias and psychological characteristics of decision-makers.
- critically evaluate the most important ideas, theories and concepts
- evaluate risky prospects by applying expected utility theory and prospect theory
(Research)
- understand experimental methods in economics
- identify and understand selected analysis tools of data generated by experimental economics
- apply selected analysis tools of experimental data-analysis
- apply experimental economics methodology
(Application)
- identify behavioural bias mitigation techniques
(Communication)
- summarise essential elements of an experimental project in a research report
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The behavioural economics of the 80s and 90s has emerged as a distinct subfield of economics. It aims to describe better actual economics decision making in contrast to the neo-classical assumption of a decision-maker model. Bluntly speaking, the econ101 rational man is an egoistic psychopath, only maximising his own utility, not making any errors and having unlimited computational power. However, actual people like you and us behave differently. They are bounded rational – people have limited computation capability and rather satisfice than optimise (more is not always better), they produce cognitive and emotional ‘errors’ when making decisions, have social preferences (some are psychopaths though), and use heuristics. Behavioural economics takes up such behaviour aiming to make economics models more ‘realistic’. Of course, this relatively new field yielded more questions than answers. For example, we don’t know how individual economic decision-making aggregates in markets or what model to apply for predicting the behaviour of people. However, many researchers added to the knowledge base, and the Nobel Prize for economics has also recognised the behavioural economics contributions of Herbert A. Simon (in 1978), George Akerlof (in 2001), Daniel Kahneman (in 2002), Robert Shiller (in 2013), and Richard Thaler (in 2017).
This course provides insights into the key concepts of behavioural economics and critically reflects on the field. Building upon the rational agent framework, you will learn about behavioural biases and heuristics and their impact on economic decision making and market outcomes. We discuss methods to detect and understand BE issues using Experimental Economics (EE).
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We presume knowledge of ‘economics 101’, i.e. lements derived from courses like Micro- and Macro Economics and introduction to economics. . We might recall some of those elements but expect to be familiar with the underlying concepts. Your mathematical skills should be in line with 3rd-year ECON bachelor student skills. Expect analytical and numerical examples, including optimisation problems and probability calculation. Make yourself comfortable with the natural logarithm and the related e-function. We also deal with data analysis methods, so we expect fundamental knowledge in statistics and econometrics. For example, you will perform hypothesis testing tests and might use OLS regressions using Excel, STATA or other software packages (your choice).
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Written exam.
In a working group, you will conduct a project yielding a scientific short paper.
Partial results do not remain valid
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In this course you will have to participate in experiments and online surveys also during the lectures. Hence, you should bring a notebook/tablet/smartphone.
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