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ECON2061: ECONOMETRICS

Please ensure you check the module availability box for each module outline, as not all modules will run in each academic year. Each module description relates to the year indicated in the module availability box, and this may change from year to year, due to, for example: changing staff expertise, disciplinary developments, the requirements of external bodies and partners, and student feedback. Current modules are subject to change in light of the ongoing disruption caused by Covid-19.

Type Open
Level 2
Credits 20
Availability Available in 2023/24
Module Cap
Location Durham
Department Economics

Prerequisites

  • Principles of Economics (ECON1011) AND EITHER Economic Methods (ECON1021) OR Calculus I (MATH1061) AND Linear Algebra I (MATH1071) AND Probability I (MATH1597) AND Statistics I (MATH1617)

Corequisites

  • None.

Excluded Combinations of Modules

  • None.

Aims

  • To enable students to identify and apply appropriate econometric methods to answer economic questions.
  • To enable students to interpret the results of econometric analyses.
  • To enable students to understand and critically evaluate econometric analyses from the economics literature.
  • To build on the material of Economic Methods.

Content

  • Topics covered are likely to include:
  • Linear Regression
  • Hypothesis Tests on Regression Coefficients
  • Nonlinear Regression Functions
  • Assessing Validity of Regression Analyses
  • Regression with Panel Data
  • Regression with Binary Variables
  • Instrumental Variables Regression
  • Introduction to Regression with Time Series Data

Learning Outcomes

Subject-specific Knowledge:

  • Understand and perform regression analysis

Subject-specific Skills:

  • ability to set in context results from empirical research
  • ability to conduct and manage a small-scale empirical project using econometric analysis

Key Skills:

  • Written Communication: the summative assessment includes both a written report and a written examination.
  • Problem Solving: the exercises will require students to use the basic material to solve problems tested in the summative assessment
  • Numeracy: students are expected to perform econometric tests and interpret empirical work to the level of their knowledge.
  • Computer Literacy: the project will be word-processed and the analysis assignment will require the use of an econometric package.

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

  • Teaching is by lectures, seminars and computer practicals. Learning takes place through attendance at lectures, preparation for and participation in seminars, computer practicals, and private study. Summative assessment is by means of an in-person examination and assignment. Formative assessment is by means of a piece of written work to prepare for the exam.

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Lectures201 per week2 hours40 
Revision Lectures21 per week in Term 32 hours4 
Seminars63 in Term 1, 3 in Term 2 1 hour6Yes
Computer Practicals21 in Term 1, 1 in Term 21 hour2Yes
Preparation and Reading148 
Total200 

Summative Assessment

Component: ExaminationComponent Weighting: 80%
ElementLength / DurationElement WeightingResit Opportunity
One in-person written examination 2 hours100Same
Component: AssignmentComponent Weighting: 20%
ElementLength / DurationElement WeightingResit Opportunity
One written assignment1500 words max100Same

Formative Assessment

One written piece of work to prepare students for the summative exam.

More information

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