This 16-month programme normally starts in September and is divided into six half-unit taught courses for the first eight months, followed by a dissertation unit for the remaining eight months. Teaching sessions take place in September, January and April.
Provisionally, the teaching dates for the 2024/25 academic year will be as follows:
9-20 September 2024
6-17 January 2025
31 March - 11 April 2025
(* denotes a half unit)
First year
September
Behavioural Science and Policy*
Examines the main concepts and tools of the growing fields of behavioural science. Topics covered include: What is behavioural science?; What are preferences to economists and psychologists?; Dual-process models of behaviour and the role of the unconscious mind; dual processing into policy using the MINDSPACE checklist; the role of emotions in decision making; compensating behaviours; breaking and creating habits.
Behavioural Decision Science*
Examines the field of behavioural 'decision' science and explores a selection of current research topics relevant to personal and managerial decision-making as well as policy-making. The course will cover topics such as: origin of behavioural decision science; the building blocks of behavioural decision science: preferences, utility and value; probability, uncertainty and risk; choice architecture and behavioural change; heuristics and biases in decisions about money, health, consumer products and people.
January
Research Methods for Behavioural Science*
The course aims to introduce students in an intuitive and accessible way to the main methodological concepts and tools in behavioural science. To achieve this objective, the self-contained course combines rigorous conceptual discussion with hands-on practical applications. The course covers: the beauty of experiments: how randomization solves the sample selection bias; randomized controlled experiments from the lab to the field; online experiments, lab-field experiments; internal validity, external validity, generalizability, and reproducibility of experiments; statistical tools; experimental design, the mechanics of randomization, principles of experimental design; tests of hypothesis: principles and practices, intuitions and rules of thumbs; introduction to econometrics: simple and multiple linear regression models, econometric analysis of experimental data; sampling: optimal sample size calculation in practice, useful rules of thumbs; experimental best practices and challenges; when randomization is not possible; outcomes and behavioural measures in experiments, principles of survey design. The seminars involve hands-on practical applications using Stata, R, and online resources.
One from:
The Science of Time at Work*
Students taking this course will gain a) a multidisciplinary perspective on managing time at work and beyond; b) will learn to think critically about their own experience and use of time, and how this shapes their expectations and behaviours in their personal life, at work, and in society; c) they will be able to recognise the barriers that prevent them from pursuing activities that are beneficial for them; d) will gain knowledge about how innovations and the growing knowledge economy has changed the way we think about time; and e) will learn how to formulate solutions that enable positive behavioural change in the way they use and experience time across all aspects of their lives.
Policy Appraisal and Ethics*
Aims to introduce the main concepts and tools of policy appraisal and yield insight into key moral and political values that are essential for policy-makers when they draw on behavioural science. The topics that the course covers include architecture of cost-benefit analysis for market and non-market goods; elicitation of monetary values through revealed and stated preference methods; welfare analysis of policy interventions; evaluating welfare beyond monetary choices; and moral problems associated with libertarian paternalism or Nudge.
Corporate Behaviour and Decision Making*
Discusses behavioural sciences in the context of corporate firms and high stakes decisions. From their core courses students will be familiar with biases in decision making in general and this course builds on these courses. The course will discuss contexts in which behavioural biases affect high stake decisions in corporate settings. Specifically, it will cover behavioural biases in: trade and investment, compliance, search and hiring processes and day to day decision making in business. It will draw on empirical evidence from experiments, quasi-experimental, observational and qualitative research.
April
Frontiers in Behavioural Science Methods*
Behavioural science is the scientific study of human behaviour, and it combines research techniques from experimental psychology and economics. The course offers an integrated training in advanced behavioural science methods by introducing students to state-of-the-art experimental techniques that stretch across the spectrum of both disciplines. The course covers the following topics: advanced considerations in experimental design; determining evidential value of behavioural science research: undisclosed flexibility in data collection, p-curve analysis; pre-registration, pre-analysis plan; reproducibility practices in modern behavioural science experiments; measuring attitudes and preferences; designing behavioural priming experiments and measures that tap into implicit cognition; behavioural game theory and experimental games of strategic interaction; non-linear regression models; understanding the mechanisms behind behavioural effects by employing experimental-causal-chain, measurement-of-mediation, and moderation-of-process designs; state-of-the-art physiological research techniques; tests of hypotheses and sample size calculations for experiments in theory and practice; systematic reviews of the literature.
Either
Behavioural Science in an Age of AI and New Technology*
The course aims to a) introduce major technological advancements that are relevant for predicting, influencing, and understanding human behaviour; b) outline how they supplement and extend commonly used tools of behavioural change; and c) examine how they can be used to propel behavioural science into the future. The course will tackle behavioural science in relation to artificial intelligence (AI), virtual environments, social robots, digital footprints, and other relevant developments in the field of technology. Emphasis will be placed on how the technological tools covered throughout the course can be used to change behaviour in applied settings, and students will be encouraged to discuss implications for their organisations and other areas of interest.
Or
Behavioural Science for Health and Regulation*
The course aims to introduce to students the main principles, insights, and state-of-the-art applications of behavioural science to health and regulation. It covers: heterogeneity and behavioural economics; behavioural health economics and behavioural public policy; behavioural experiments in health; behavioural data linking; risk perception and risk communication; behavioural insights for information policies; information overload and information avoidance; financial and non-financial incentives; behaviourally supercharged incentives; nudging behavioural change in health; beyond nudging: ‘nudge+’ and ‘boosts’; behavioural spillovers; behavioural insights for taxation on risky health behaviours; behavioural public health; regulation, policy-making, and the role of the ‘behavioural regulator’; behavioural biases in regulated markets and behavioural market failures; health regulation, the UK health regulatory landscape; digital health and regulating decisions made in online environments; boosting prevention through personalised data and interventions; mental health, behavioural science, and AI; de-shrouding the food system; shaping markets for better health outcomes.
Plus
Dissertation in Behavioural Science
An independent research project of 10,000 words on an approved topic of your choice. To view a selection of past dissertation topics, please visit this page.
For the most up-to-date list of optional courses please visit the relevant School Calendar page.
You must note, however, that while care has been taken to ensure that this information is up to date and correct, a change of circumstances since publication may cause the School to change, suspend or withdraw a course or programme of study, or change the fees that apply to it. The School will always notify the affected parties as early as practicably possible and propose any viable and relevant alternative options. Note that the School will neither be liable for information that after publication becomes inaccurate or irrelevant, nor for changing, suspending or withdrawing a course or programme of study due to events outside of its control, which includes but is not limited to a lack of demand for a course or programme of study, industrial action, fire, flood or other environmental or physical damage to premises.
You must also note that places are limited on some courses and/or subject to specific entry requirements. The School cannot therefore guarantee you a place. Please note that changes to programmes and courses can sometimes occur after you have accepted your offer of a place. These changes are normally made in light of developments in the discipline or path-breaking research, or on the basis of student feedback. Changes can take the form of altered course content, teaching formats or assessment modes. Any such changes are intended to enhance the student learning experience. You should visit the School’s Calendar, or contact the relevant academic department, for information on the availability and/or content of courses and programmes of study. Certain substantive changes will be listed on the updated graduate course and programme information page.