SA4M3E      Half Unit
Research Methods for Behavioural Science

This information is for the 2015/16 session.

Teacher responsible

Dr Matteo Galizzi

Availability

This course is compulsory on the Executive MSc in Behavioural Science. This course is not available as an outside option.

Course content

The course aims to introduce students to the main methodological concepts and tools in behavioural science. The course will combine rigorous conceptual discussion with practical applications. To achieve this objective, the course covers: Correlation versus causation: how randomization solves the sample selection bias; Randomized controlled experiments in the lab and the field: principles, issues, taxonomy; Experimental design and behavioural econometrics: between/within design, hypothesis tests, statistical analysis of data, structural estimation; Sampling: sample size, sampling methods, ethics, recruitment; When randomization is not possible: natural experiments, quasi-experiments, difference-in-difference, discontinuity regression design, propensity score matching; Measuring risk and time preferences: principles and experimental tests; Measuring rationality in strategic decision-making: principles of game theory; Measuring social preferences: behavioural game theory; Measuring preferences for goods: experimental auctions; Measuring attitudes and non-conscious mind states: constructing psychometric indexes, inducing moods and emotions, priming.

Teaching

17 hours and 30 minutes of lectures and 5 hours of seminars in the LT.

Formative coursework

Students will be expected to produce 1 piece of coursework in the LT.

Indicative reading

Andersen S, Harrison GW, Lau MI, Rutström EE (2010): Behavioral Econometrics for Psychologists. Journal of Economic Psychology, 31, 553-576.

Andrade EB, Ariely D (2009). The enduring impact of transient emotions on decision making. Organizational Behavior and Human Decision Processes, 109, 1-8 (2009).

Blundell R, Costa-Dias M (2002). Alternative approaches to evaluation in empirical microeconomics. Portuguese Economic Journal, 1, 91-115.

Camerer CF (2003). Behavioral Game Theory: Experiments in Strategic Interaction. Princeton University Press.

Cohen J (1988). Statistical Power Analysis for the Behavioural Sciences. Routledge.

Duflo E, Glennerster R, Kremer M (2007). Using randomization in development economics research: a toolkit. CEPR Discussion Paper No. 6059. Center for Economic Policy Research, London.

Harrison GW, List JA (2004). Field experiments. Journal of Economic Literature, XLII, 1009-1055.

List JA (2006). Field experiments: a bridge between the lab and naturally occurring data. Advances in Economic Analysis and Policy, 6, 8.

List JA, Sadoff S, Wagner M (2011). So you want to run an experiment, now what? Some simple rules of thumb for optimal experimental design. Experimental Economics, 14, 439-457.

Lusk JL, Shogren JF (2007). Experimental Auctions: Methods and Applications in Economic and Marketing Research. Cambridge University Press.

Mead R (1988). The Design of Experiments: Statistical Principles for Practical Applications. Cambridge University.

Rubin DB (1978). Bayesian inference for causal effect: the role of randomization. Annals of Statistics, 6, 34-58.

Assessment

Take home exam (100%) in the LT.

Key facts

Department: Social Policy

Total students 2014/15: Unavailable

Average class size 2014/15: Unavailable

Controlled access 2014/15: Yes

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Leadership
  • Self-management
  • Team working
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Commercial awareness
  • Specialist skills