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Research Methods I

Module description

This module provides an introduction to the techniques involved in optimization.

Full module specification

Module title:Research Methods I
Module code:BEEM136
Module level:M
Academic year:2022/3
Module lecturers:
  • Dr Szabolcs Deak - Convenor
Module credit:15
ECTS value:



Only available to MRes Economics PhD pathway



Duration of module: Duration (weeks) - term 1:


Module aims

This module aims to provide a thorough introduction to the techniques involved in optimisation required to take PhD level Economics courses. Topics include advanced calculus, dynamic programming, difference equations and linear algebra.

ILO: Module-specific skills

  • 1. demonstrate and derive rigorous mathematical proofs.
  • 2. work with abstract mathematical concepts.
  • 3. solve economic optimisation problems.

ILO: Discipline-specific skills

  • 4. read and work with current economic research papers.
  • 5. critically analyse the logic of economic arguments.
  • 6. use and analyse economic models.

ILO: Personal and key skills

  • 7. demonstrate numeracy skills and handle logical and structured problem analysis.
  • 8. demonstrate inductive and deductive reasoning.
  • 9. apply essential research skills.

Learning activities and teaching methods (given in hours of study time)

Scheduled Learning and Teaching ActivitiesGuided independent studyPlacement / study abroad

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled learning and teaching activities22Lectures
Scheduled learning and teaching activities10Tutorials
Guided independent study118Reading, preparation for classes and assessments

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
Practice ProblemsVaries1-9Oral/Written

Summative assessment (% of credit)

CourseworkWritten examsPractical exams

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Examination702 hours1-9Oral/Written
Average of bi-weekly problem sets30Bi-weekly problem sets with at most 3 questions each1-9Oral/Written

Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Examination (70%)Examination (70%) ( 2 hours)1-9August examination period
Average of bi-weekly problem setsSingle problem set1-9August examination period

Re-assessment notes

If you pass the module overall you will not be referred in either component – even if you have not passed one of the components.

Syllabus plan

  • Basics of linear algebra: determinant, linear dependence and rank of a matrix, inverse of a matrix, determinant of a matrix, eigenvalues and eigenvectors, trace of a matrix, quadratic forms
  • Calculus: differentiation, integration, Taylor expansion, concavity and convexity, quasi-concavity and quasi-convexity
  • Optimization: unconstrained optimization, constrained optimization with equality constraints (Lagrange), constrained optimization with inequality constraints (Kuhn-Tucker)
  • Comparative statics and fixed points: envelope theorem, implicit function theorem, correspondences, fixed point theorems
  • Dynamic programming
  • First-order differential equations

Indicative learning resources - Basic reading

  • Knut Sydsæter, Peter Hammond, Arne Størm, and Andrés Carvajal (2016): Essential Mathematics for Economic Analysis, 5th edition, Pearson
  • Knut Sydsaeter, Peter Hammond, Atle Seierstad, and Arne Strøm (2008): Further Mathematics for Economic Analysis, 2nd edition, Pearson
  • Daniel Leonard and Ngo van Long (1991): Optimal Control Theory and Static Optimization in Economics, Cambridge University Press
  • Jianjun Miao (2014): Economic Dynamics in Discrete Time, MIT Press

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