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ECON47715: MICROECONOMETRICS

It is possible that changes to modules or programmes might need to be made during the academic year, in response to the impact of Covid-19 and/or any further changes in public health advice.

Type Tied
Level 4
Credits 15
Availability Available in 2024/2025
Module Cap None.
Location Durham
Department Economics

Prerequisites

  • None

Corequisites

  • Econometric Analysis (ECON41515)

Excluded Combinations of Modules

  • None

Aims

  • to build upon the knowledge gained in Econometric Analysis and provide students with the specific advanced technical skills (both theoretical and practical) necessary to understand the methods employed by micro econometricians;
  • to provide students with the tools required to conduct policy evaluation using microeconomic cross section and panel datasets.

Content

  • Topics may include:
  • Static and dynamic models for panel data: random-effects approach, fixed-effects approach
  • Limited dependent variable models: discrete response, censored regression, sample selection
  • Treatment effect models: regression-based methods, alternative methods (e.g. matching)

Learning Outcomes

Subject-specific Knowledge:

  • have an advanced knowledge of the principles and methods of modern microeconometrics;
  • have extended and deepened their understanding of econometrics gained in Econometric Analysis, and improved their critical judgement and discrimination in the choice of techniques applicable to complex situations;
  • have extended their understanding of the application of econometric methods and interpretation of the results at an advanced level;
  • have extended their understanding of the use of econometric tools to conduct advanced empirical investigations into complex specialised issues.

Subject-specific Skills:

  • have further practised problem-solving skills in econometrics at an advanced level and the use of econometric software.

Key Skills:

  • Written Communication;
  • Planning, Organising and Time Management;
  • Problem Solving and Analysis;
  • Using Initiative;
  • Numeracy;
  • Computer Literacy.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • A combination of lectures, seminars, computer classes and guided reading will contribute to achieving the aims and learning outcomes of this module. Fortnightly seminars will discuss applications of the econometric techniques and fortnightly computer classes will introduce students to implementation of the methods in statistical software package(s), using micro data. The summative assignment will involve students writing an empirical report using techniques covered in the module, applied to micro data. This will test students' knowledge and critical understanding of the material covered in the module, their analytical and problem-solving skills.

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Lectures101 per week2 hours20 
Seminars4Fortnightly1 hour4Yes
Computer classes4Fortnightly1 hour4Yes
Preparation & Reading122 
Total150 

Summative Assessment

Component: ProjectComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
Written Project3000 words maximum100Same

Formative Assessment

Students prepare answers to questions in advance of seminars, these are discussed during the seminar with feedback given by the lecturer. 'Indicative answers' are also presented during the seminar and posted on Learn Ultra. Feedback on discussions is available with teaching staff during consultation hours, or via e-mail.

More information

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Current Students: Please contact your department.