Durham University
Programme and Module Handbook

Undergraduate Programme and Module Handbook 2025-2026

Module ECON2061: Econometrics

Department: Economics

ECON2061: Econometrics

Type Tied Level 2 Credits 20 Availability Available in 2025/2026 Module Cap Location Durham
Tied to L100
Tied to L106
Tied to L109
Tied to L103
Tied to L104
Tied to L105
Tied to L130
Tied to L136
Tied to L139
Tied to L133
Tied to L134
Tied to L135
Tied to L125
Tied to LL12
Tied to LL02
Tied to LL01
Tied to VL52
Tied to VLL6
Tied to VLLA
Tied to CFG0
Tied to CFC0
Tied to FGC0
Tied to LMVA
Tied to LMV0

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 Combination 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 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

Activity Number Frequency Duration Total/Hours
Lectures 20 1 per week 2 hours 40
Revision Classes 2 1 per week in Term 3 2 hours 4
Seminars 6 3 in Term 1, 3 in Term 2 1 hour 6
Practicals 2 1 in Term 1, 1 in Term 2 1 hour 2
Preparation and Reading 148
Total 200

Summative Assessment

Component: Examination Component Weighting: 80%
Element Length / duration Element Weighting Resit Opportunity
On Campus Written Examination 2 hours 100% Same
Component: Assignment Component Weighting: 20%
Element Length / duration Element Weighting Resit Opportunity
Assignment 1500 words max 100% Same

Formative Assessment:

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


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University