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Course 2020-2021 a.y.

30261 - EXPERIMENTAL ECONOMICS AND PSYCHOLOGY

Department of Decision Sciences

Course taught in English

Go to class group/s: 31

CLEAM (6 credits - I sem. - OP  |  3 credits SECS-P/01  |  3 credits SECS-S/06) - CLEF (6 credits - I sem. - OP  |  3 credits SECS-P/01  |  3 credits SECS-S/06) - CLEACC (6 credits - I sem. - OP  |  3 credits SECS-P/01  |  3 credits SECS-S/06) - BESS-CLES (6 credits - I sem. - OP  |  3 credits SECS-P/01  |  3 credits SECS-S/06) - WBB (6 credits - I sem. - OP  |  3 credits SECS-P/01  |  3 credits SECS-S/06) - BIEF (6 credits - I sem. - OP  |  3 credits SECS-P/01  |  3 credits SECS-S/06) - BIEM (6 credits - I sem. - OP  |  3 credits SECS-P/01  |  3 credits SECS-S/06) - BIG (6 credits - I sem. - OP  |  3 credits SECS-P/01  |  3 credits SECS-S/06) - BEMACS (6 credits - I sem. - OP  |  3 credits SECS-P/01  |  3 credits SECS-S/06)
Course Director:
PIERPAOLO BATTIGALLI

Classes: 31 (I sem.)
Instructors:
Class 31: PIERPAOLO BATTIGALLI


Lezioni della classe erogate in presenza

Suggested background knowledge

Students should have a good knowledge of elementary linear algebra, statistics, econometrics, and of intermediate microeconomic theory.


Mission & Content Summary
MISSION

In the last three decades economic models of behavior in single-person and interactive decision problems dropped some of the assumptions characterizing homo oeconomicus to bring in psychological considerations ranging from cognitive limitations to a richer set of motivations. This development occurred in tandem with the ever-increasing use of experimental methods (besides the analysis of observational data) in empirical economics. The goal of this course is to introduce to this exciting set of models and methods, providing the necessary elements of the theory of decisions and games, and of the econometrics methods to analyze experimental data.

CONTENT SUMMARY

 

1.      Introduction: correlation is not causation; experiments in social sciences; why we need models.

2.      Classic axiomatic approach to choices: everything breaks down if you change your mind.

3.      Axiomatic approach to uncertainty: Bayes rule.

4.      Von Neumann-Morgenstern expected utility. Subjective expected utility.

5.      Probabilistic biases and prospect theory.

6.      Intertemporal choice. Rational planning.

7.      Analysis of experimental data, I.

8.      Analysis of experimental data, II.

9.      Introduction to game theory: simultaneous moves.

10.    Introduction to game theory: sequential moves.

11.    Introduction to game theory: incomplete information.

12.    Introduction to psychological game theory.

13.    Trust and guilt aversion: theory.

14.    Trust and guilt aversion: experiments.

15.    Threats and anger: theory.

16.    Threats and anger: experiments.

17.    Reciprocity: theory.

18.    Reciprocity: experiments.

19.    Deception: theory.

20.    Deception: experiments.

21.    Setup of a lab experiment. Ethics.

22.    Dual theory.

23.    Covid19: (i) a perfect natural experiment? (ii) behavioral biases in the reaction of politicians and people.

24.    Sum up lecture. 


Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • describe (i) the classical models of choice in single-person and interactive decision problems and (ii) the rudiments of the psychological theory of decisions and games;
  • identify and illustrate what psychological considerations can be covered by such models, and what require different models;
  • distinguish between observational and experimental data;
  • explain the rudiments of experimental economics.
APPLYING KNOWLEDGE AND UNDERSTANDING
At the end of the course student will be able to...
  • Represent a concrete single-person or multi-person decision problem as a game
  • Implement such games in the lab, setting up an experiment
  • Express experimental hypotheses, possibly deriving them from models and auxiliary assumptions
  • Analyze experimental data, comparing them with theoretical predictions, devise possible reasons for the rejection of such predictions

Teaching methods
  • Face-to-face lectures
  • Online lectures
  • Individual assignments
  • Group assignments
DETAILS

Online lectures will consists of the recording and, possibly, the synchronous streaming of face-to-face lectures, or alternative methods, such as recorded presentations of slides, should face-to-lectures become unfeasible.

Individual assignements: solution of problem sets.

Group assignments: experimental project, from the theoretical motivation to the design, and--if possible--the implementation and analysis of the experiment.


Assessment methods
  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
  •     x
  • Individual assignment (report, exercise, presentation, project work etc.)
  •     x
  • Group assignment (report, exercise, presentation, project work etc.)
  •     x
    ATTENDING AND NOT ATTENDING STUDENTS

    The written exam will verify whether students have learned the more theoretical parts of the course and the most important experimental results.

    Individual assignements will allow students to self-assess their understanding of the more theoretical parts of the course, and the teacher to verify such understanding while the course is being taught.

    Group assignements will allow students to practice with experimental methods.

    The written exam is worth at most 19 points.

    Assignements are worth a total of at most 12 points.


    Teaching materials
    ATTENDING AND NOT ATTENDING STUDENTS

    There is a textbook that we use in the first 6 lectures of the course:

    ·         E. ANGNER, A Course in Behavioral Economics. Palgrave Macmillan, 2012;

    and a textbook that we will partially follow in lectures 7 and 8:

    ·         P. G. MOFFATT, Experimetrics: Econometrics for experimental economics. Palgrave Macmillan, 2015.

    Finally, for lectures 9-12 devoted to an introduction to (psychological) game theory we will use some chapters/sections of the lecture notes:

    ·         P. BATTIGALLI, Game Theory: Analysis of Strategic Thinking, mimeo;

    and the following survey, which also contains many relevant references to theoretical and experimental work:

    ·         P. BATTIGALLI and D. DUFWENBERG, “Belief-Dependent Motivations and Psychological Game Theory,” IGIER w.p. 646 (2019).

     

    Complementary lecture notes and/or slides will be distributed.

    Last change 15/07/2020 13:05