MSc/PGCert/ PGDip Behavioural Economics in Action

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Programme Specification for MSc/PGCert/ PGDip Behavioural Economics in Action 1. Programme title MSc Behavioural Economics in Action 2. Awarding institution Middlesex University 3. Teaching institution Middlesex University 4. Details of accreditation by professional/statutory/regulatory body 5. Final qualification Master in Science PGDip PGCert 6. Year of validation Year of amendment 7. Language of study English 8. Mode of study Full-time/ Part-time 9. Criteria for admission to the programme Enterprising graduates from any areas (Economics, Business Management, Business Administration, Finance, Psychology, Sociology, Anthropology, Neuroscience etc.) are welcome from a British University or a recognised overseas equivalent. Full-time participation is encouraged. However, if reasonably justified, part time participation is also possible. Students whose first language is not English will need to demonstrate English language proficiency in addition to the other entry requirements. A minimum score of 6.5 IELTS (with a minimum of 6.0 in each component) or a TOEFL score of 575 for the written test or 230 for the computer test or an equivalent qualification recognised by Middlesex University must be obtained. The equivalence of qualifications from outside UK will be determined according to

NARIC guidelines. 10. Aims of the programme The programme aims to equip students with the ability to: apply insights from Behavioural Economics to address real world problems; design and implement an experiment in the lab and in the field; use analytical tools to aid with critical thinking; apply relevant statistical methods to analyse experimental data; provide implementable solutions to real world problems; use a common programming package z-tree; undertake real world training - our students will work with individuals implementing and designing experiments. 11. Programme outcomes A. Knowledge and understanding On completion of this programme the successful student will have knowledge and understanding of : 1. Equilibrium predictions in strategic situations. 2. Individual s behaviour and decision making process in both the labour and financial markets. 3. Locating, handling, presenting, analysing and interpreting data. 4. Modelling economic relationships using regression analysis. 5. Designing experiments to examine human behaviour and/or with policy implications. Teaching/learning methods Students gain knowledge and understanding through: lectures, seminars and research seminars; lab work; directed reading; coursework and case studies; visiting speakers; group work; dissertation. Assessment methods Students knowledge and understanding is assessed by: individual coursework; unseen tests dissertation. B. Cognitive (thinking) skills Teaching/learning methods

On completion of this programme the successful student will be able to: 1. Use economic and psychological reasoning to explain firm s and individual s behaviour in the labour market. 2. Determine the most appropriate sampling methods and tests to help with experimental design and interpreting results. 3. Differentiate behavioural approaches to decision making of consumers and firms from the traditional approach. Students learn cognitive skills through: discussion, debate, and on-line activities from external sources such as Moblab and presentation; lectures, seminars, lab work and research seminars Assessment methods Students cognitive skills are assessed by: case studies and in-class tests; presentations; dissertation. 4. Critically evaluate related theoretical and/or empirical literature. C. Practical skills On completion of the programme the successful student will be able to: 1. Program basic environments in Z- tree. 2. Search, prepare and manipulate experimental data for regression analysis using econometric software. 3. Identify real problems with real-world applications. 4. Design and execute an experiment. Teaching/learning methods Students learn practical skills through: lab work and on-line activities; participating in field work; experimental design; dissertation. Assessment methods Students practical skills are assessed by: reports on field work; dissertation and presentation of dissertation. 5. Run an experiment in the field. D. Graduate skills On completion of this programme the successful student will be able to: 1. Manipulate numerical data. Teaching/learning methods Students acquire graduate skills through: lectures and seminars; lab work; presentations.

2. Use communication and information technology to acquire, analyse and communicate information, including acknowledgement, and referencing of sources. 3. Communicate effectively: using quantitative and qualitative information, together with analysis, arguments and commentary, in a form appropriate to the intended audience. Assessment methods Students graduate skills are assessed by coursework and in-class tests; dissertation; presentations. 4. Have the capacity for independent and self-managed learning. 12. Programme structure (levels, modules, credits and progression requirements) 12. 1 Overall structure of the programme The MSc Behavioural Economics in Action (180 credits) programme will offer both fulland part-time modes, with the latter being run over two years. We also offer a Post- Graduate Diploma (120 credits) and a Post-Graduate Certificate (60 credits) for the same program with analogous part-time options. The programme will consist of four core modules, practical training and a dissertation. Four modules will be taught in classroom format and will be worth 15 credits each. These will be either taught on a term only basis (full-time) or in two terms (part-time). The practical training consists of 60 credits and will be achieved during the second term. The dissertation will carry 60 credits. Full-time students, you will do four core modules plus the practice plus a dissertation for the whole year. Meanwhile, part-time students can spread the core courses along the first year. They will then undertake the practice module during the second year. Students will present their end of course project (dissertation) upon completion. MSc Full-time Term 1 ECS4002 Data Analysis (15 credits) Term 2 ECS4005 Practice (60 credits)

Term 3 ECS4006 Dissertation (60 credits) MSc Part-time Year 1 ECS4002 Data Analysis (15 credits) Year 2 ECS4005 Practice (60 credits) ECS4006 Dissertation (60 credits) PGDip Full-time ECS4002 Data Analysis (15 credits) ECS4005 Practice (60 credits) PGDip Part-time Year 1 ECS4002 Data Analysis (15 credits) Year 2 ECS4005 Practice (60 credits) PGCert Full-time ECS4002 Data Analysis (15 credits) PGCert Part Time Year 1

ECS4002 Data Analysis (15 credits) Year 2 12.2 Levels and modules Level 7 (4) COMPULSORY OPTIONAL PROGRESSION REQUIREMENTS Students must take all of the following: ECS4001 ECS4002 Pass ECS4001, ECS4002, ECS4003 and ECS4004 before practice term (ECS4005). ECS4003 ECS4004 (all the above four modules are for all three programmes) ECS4005 (for MSc & PGDip only) ECS4006 (for MSc only) 12.3 Non-compensatable modules (note statement in 12.2 regarding FHEQ levels) Module level Level 7 Level 7 Module code ECS4005 (for PGDip award) ECS4005 & ECS4006 (for MSc award) 13. Curriculum map See attached.

14. Information about assessment regulations Assessment regulations will follow the University s general regulations for postgraduate programmes. 15. Placement opportunities, requirements and support (if applicable) The Practical training module is an essential part of course (ECS4005). Students are expected to identify an interesting problem and implement it in a real environment, or seek training at an experimental economics laboratory. Students are expected to learn hands-on the design and implementation of experiments. Students will receive guidance towards their projects. 16. Future careers (if applicable) The University provides an employability service that is available to support students in this programme. Graduates from this programme will be able to : progress onto the DProf and DBA programmes; pursue a career, academic or otherwise, in policy focused institutions such as the HMRC, Bank of England, Health policy etc.; apply the experimental methodology to improve workplace environment and efficiency; look for professional improvement within their own organisations; look to implement scientifically developed experiments and further data analysis. 17. Particular support for learning (if applicable) Dedicated programme support team English Language support Learning Resources Learner Development Unit Personal and professional development sessions Programme Handbook and Module Handbooks Induction and orientation programme Access to student counsellors On-line learning environment on MyUnihub Student e-mail and internet access Visiting speakers seminar series

18. JACS code (or other relevant coding system) 19. Relevant QAA subject benchmark group(s) L100 Economics (2007), QAA Master s Degrees in Business and Management (2007), Master s Degree characteristics (2010) 20. Reference points QAA Guidelines for programme specifications QAA Framework for Higher Education Qualifications (FHEQ) QAA Subject Benchmark in Economics QAA Codes of Practice Middlesex University Regulations Middlesex University Mission and Vision Middlesex University and Business School Learning, Teaching and Assessment Strategy Middlesex University Learning Framework Programme Design Guidance, 2012 21. Other information Please note programme specifications provide a concise summary of the main features of the programme and the learning outcomes that a typical student might reasonably be expected to achieve if s/he takes full advantage of the learning opportunities that are provided. More detailed information about the programme can be found in the rest of your programme handbook and the university regulations.

Appendix 2: Curriculum Map Curriculum map for MSc Behavioural Economics in Action This section shows the highest level at which programme outcomes are to be achieved by all graduates, and maps programme learning outcomes against the modules in which they are assessed. Programme learning outcomes Knowledge and understanding Practical skills A1 Equilibrium predictions in strategic situations. C1 Program basic environments in Z-tree. A2 Individual s behaviour and decision making process in both the labour and financial markets. C2 Search, prepare and manipulate experimental data for regression analysis using econometric software. A3 Locating, handling, presenting, analysing and interpreting data. C3 Identify real problems with real-world applications. A4 Modelling economic relationships using regression analysis. C4 Design and execute an experiment. A5 Designing experiments to examine human behaviour and/or with policy implications. C5 Run an experiment in the field. Cognitive skills Graduate Skills B1 Use economic and psychological reasoning to explain firm s and individual s behaviour in the labour market. D1 Manipulate numerical data. B2 Determine the most appropriate sampling methods and tests to help with experimental design and interpreting results. D2 Use communication and information technology to acquire, analyse and communicate information, including acknowledgement, and referencing of sources. B3 Differentiate behavioural approaches to decision making of consumers and firms from the traditional approach. D3 Communicate effectively: using quantitative and qualitative information, together with analysis, arguments and commentary, in a form appropriate to the intended audience. B4 Critically evaluate related theoretical and/or empirical literature. D4 Have the capacity for independent and self-managed learning.

Programme outcomes A1 A2 A3 A4 A5 B1 B2 B3 B4 C1 C2 C3 C4 C5 D1 D2 D3 D4 Highest level achieved by all graduates 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 Module Title Module Code by Level Programme outcomes A1 A2 A3 A4 A5 B1 B2 B3 B4 C1 C2 C3 C4 C5 D1 D2 D3 D4 Behavioural Economics ECS4001 X X X X X X Data Analysis ECS4002 X X X X X X Experimental Economics ECS4003 X X X X X Behavioural Markets ECS4004 X X X X X Practice ECS4005 X X X Dissertation ECS4006 X X X X X X X