ECON61001
Econometric Methods
15
Semester 1
Postgraduate Taught
Level 6
Alastair Hall
Unit coordinator
Economics
1
FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 '
European Credit Transfer & Accumulation System Rating : 7.5
<p>The aim of this course is to equip students with a firm grounding in the methods and practice of estimation and inference in econometric models.</p>
<p>The aim of this course is to equip students with a firm grounding in the methods and practice of estimation and inference in econometric models.</p>
<p>The aim of this module is to equip students with a firm grounding in the methods and practice of estimation and inference in econometric models.</p>
<p>On completion of this unit successful students will be able to undertake well-founded empirical, data-based work. This is a skill required in all modern positions for economists. The skills learned here also form the basis for any empirical research activity (in the dissertation or any post-university academic or commercial research activities).</p>
<p>Students will be able to:</p><ul><li>Understand the manipulation and use of matrices and vectors and their application in econometrics</li><li>Understand how to conduct estimation and inference in both time series and cross-section applications of the linear model, employing standard least squares, instrumental variables and robust inferential techniques</li><li>Understand the construction of advanced estimation procedures such as Maximum Likelihood and Generalized Methods of Moments estimators and associated inferential procedures with applications to economic problems</li></ul>
<p>Students will be able to explain the advantages and disadvantages of using particular estimation techniques in economic applications</p>
<p>Knowledge of programming in R.</p><p>Analysing data by applying econometric methods in R.</p><p>Applying descriptive and inferential statistics.</p>
<p>Statistical modelling.</p><p>Data analysis.</p>
<p>Provisional</p><p>1. The Classical Linear Regression Model</p><p>2. Large sample analysis of OLS</p><p>3. Inference in regression models estimated from cross-section data</p><p>4. Inference in regression models estimated from time series data</p><p>5. Instrumental Variable estimation</p><p>6. Maximum Likelihood and Binary Choice Models</p><p>7. Generalized Method of Moments</p>
<p>Lectures, tutorials and practical and guided self-study.</p>
0
Other
100%
<p>Formative Assessment:</p><p>Tutorial Exercises</p><p>Summative Assessment:</p><p>Final exam - 2 hours (60%)</p><p>Midterm - 50 minutes (20%)</p><p>Pre-Session statistics test (10%)</p><p>Computer/analytical assignments (10%)</p>
ECON60901
Introduction to Quantitative Methods in Economics
Pre-Requisite
Compulsory
ECON61001
Econometric Methods
Pre-Requisite
Compulsory
ECON60901 is a Co-Requisite for ECON61001
MSc Economics
MSc Economics
PGDT Taught Component
Mandatory
MSc Financial Economics
MSc Financial Economics
PGDT Taught Component
Mandatory
N
<p>Lecture notes will be provided.</p><p>A secondary source for all aspects of the course is:</p><p>William H. Greene, 2017, Econometric Analysis, 8th Edition, Pearson Higher Education Publishing Company.</p><p>Please note that the course will involve linear algebra from the start. So for those of you whose undergraduate Econometrics course was based on a text such as Jeff Wooldridge’s “Introductory Econometrics”, the presentation of the mathematical arguments will be more similar to his Appendices D and E than in the main part of his text. The Pre-session Mathematics and Statistics courses will review linear algebra but it is strongly recommended you review this material in advance. Additional resources are available on the ECON61001 Blackboard site.</p>
Lectures
20
Practical classes & workshops
10
Tutorials
10
0
110
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