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EC226: Econometrics 1

  • Jeremy Smith

    Module Leader
  • Kenichi Nagasawa

    Module Lecturer
30 CATS - Department of Economics
Summer Module
Autumn Module

Principal Aims

This module provides students with a thorough understanding basic principles of econometrics. You will be exposed to a range of different econometric tools. You will gain an understanding of simple OLS, the limitations of the application of OLS, potential alternative estimators for the different type of data one might encounter including: cross-sectional data sets, time series data set and panel data sets.. You will gain skills and techniques to analyse problems from an intuitive, graphical and statistical perspective applying your knowledge to real world data.

Principal Learning Outcomes

Acquired the tools of quantitative methods necessary to study core and optional second and third year modules in economics for single honours courses in EconomicsThe teaching and learning methods that enable students to achieve this learning outcome are: Lectures and classes The summative assessment methods that measure the achievement of this learning outcome are: Test, exam, problem set and assignment (group work)

Developed further their techniques of statistical methods; generated a thorough understanding of the statistical techniques as well as a critical appreciation of them.The teaching and learning methods that enable students to achieve this learning outcome are: Lectures and classes The summative assessment methods that measure the achievement of this learning outcome are: Test, exam, problem set and assignment (group work)

Developed their understanding of statistical (econometric) software and economics databases.The teaching and learning methods that enable students to achieve this learning outcome are: Lectures and classes The summative assessment methods that measure the achievement of this learning outcome are: Problem set and assignment (group work)

Further developed their communication skills in presenting and analysing data. The teaching and learning methods that enable students to achieve this learning outcome are: Classes. The summative assessment methods that measure the achievement of this learning outcome are: Assignment (group work), problem set.

Syllabus

The module will typically cover the following topics:Linear regression model. Least squares estimation. Dummy variables. Linear Restrictions. Classical Linear Regression Model Assumptions. Breakdown of CLRM assumptions. Errors in variables. Heteroscedasticity and implications for OLS. Structural change. Incorrect functional form and implications for OLS. Instrumental variable estimation. Dynamic models with lagged dependent variable. Serial Correlation and implications for OLS. Types of autocorrelation. Nonstationarity and Cointegration. Panel data models. Limited dependent variable models.

Context

Core Module
L100 - Year 2, L116 - Year 2, L1PA - Year 1, L1P5 - Year 1, R3L4 - Year 2, R2L4 - Year 2, R1L4 - Year 2, LM1D (LLD2) - Year 2, R9L1 - Year 2, R4L1 - Year 2
Optional Core Module
GL11 - Year 2, V7MR - Year 2, GL12 - Year 2
Optional Module
GL12 - Year 4, V7ML - Year 2, V7ML - Year 3, V7MP - Year 2, V7MP - Year 3, V7MM - Year 4
Restrictions
May not be combined with modules EC203-30
Part-year Availability for Visiting Students
Available in the Autumn term only (1 x test, 1 assignment 12 CATS) and in the Autumn and Spring term together 2 x test, 2 x assignments and problem sets 24 CATS)

Assessment

Assessment Method
Coursework (40%) + 3 hour examination (summer) (60%)
Coursework Details
Test (15%), Group Project (15%), 5 x online multiple choice question tests (5%), Group work assignment (5%), 3 hour examination (summer) (60%)
Exam Timing
N/A

Exam Rubric

Time Allowed: 3 Hours, plus 15 minutes reading time during which notes may be made (on the question paper) BUT NO ANSWERS MAY BE BEGUN.

Answer ALL EIGHT questions from Section A (52 marks total), and THREE questions from Section B (16 marks each). Answer Section A questions in one booklet and Section B questions in a separate booklet.

Approved pocket calculators are allowed. Statistical Tables and a Formula Sheet are provided.

Read carefully the instructions on the answer book provided and make sure that the particulars required are entered on each answer book. If you answer more questions than are required and do not indicate which answers should be ignored, we will mark the requisite number of answers in the order in which they appear in the answer book(s): answers beyond that number will not be considered.

Previous exam papers can be found in the University’s past papers archive. Please note that previous exam papers may not have operated under the same exam rubric or assessment weightings as those for the current academic year. The content of past papers may also be different.

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